Copyright TechTarget - All rights reserved https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Mon, 17 Aug 2026 14:38:56 GMT https://www.techtarget.com/it-infrastructure editor@techtarget.com <p>Many organizations remain unprepared for the rapid growth of AI-generated content and synthetic datasets across enterprise environments, leaving them equally unprepared to govern that data effectively and within compliance boundaries.</p> <p>Governance frameworks are lagging behind AI, even as AI-generated and other algorithmically&nbsp;generated <a href="https://www.techtarget.com/it-strategy/definition/What-is-synthetic-data-Examples-use-cases-and-benefits">synthetic data</a> permeate across business functions. Governance is now a strategic business issue, not just an IT concern. Executives should establish governance best practices before operational and regulatory complexity increases. IT leaders investing in AI need to construct an AI data lifecycle policy and establish scalable governance.</p> <section class="section main-article-chapter" data-menu-title="Why AI-generated and synthetic data require governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why AI-generated and synthetic data require governance</h2> <p>AI-generated data and synthetic data differ fundamentally from traditional data. Traditional data originates from real-world business activities, customer interactions, transactions, sensors or human-created content. It is the data generated by years of doing business.</p> <p>AI-generated data is produced by machine learning models, including text, images, code, audio or analytics. It is often derived from prompts or existing data. For enterprises, AI-generated data accelerates content creation, software development, customer support and decision-making.</p> <p>Synthetic data is artificially created to statistically resemble real data without directly representing actual individuals or events. Synthetic data enables a host of practices, such as AI model training, <a href="https://www.techtarget.com/searchbusinessanalytics/tip/Synthetic-data-vs-real-data-for-predictive-analytics">software testing</a>, analytics and data sharing while reducing privacy risks, protecting sensitive information and improving compliance. Together, they expand opportunities for innovation but require stronger governance over provenance, quality, security and lifecycle management.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/when_to_use_synthetic_data-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/when_to_use_synthetic_data-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/when_to_use_synthetic_data-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/when_to_use_synthetic_data-f.png 1280w" alt="When to use synthetic data. " data-credit="TT" height="347" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Four synthetic data use cases are based on data accessibility and representativeness: edge cases, model validation, data scarcity, and privacy and security. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>These data sources are increasingly important to business innovation, but they include significant risks for IT leaders to mitigate.</p> </section> <section class="section main-article-chapter" data-menu-title="How machine-generated content creates risk"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How machine-generated content creates risk</h2> <p>Unmanaged AI-generated content presents operational, legal and <a href="https://www.techtarget.com/searchSecurity/tip/Data-sovereignty-compliance-challenges-and-best-practices">compliance risks</a> that cannot be ignored. These risks span the organization, making them a strategic governance imperative.</p> <p>Specific risk examples include:</p> <ul class="default-list"> <li><b>Data provenance and authenticity</b>. Organizations must be able to demonstrate where AI-generated content originated, which model produced it, when it was created and whether it has been modified. Without provenance, trust and auditability suffer.</li> <li><b>Regulatory compliance</b>. AI-generated and synthetic data may still fall under regulations such as GDPR and the <a href="https://www.techtarget.com/ai/opinion/Everything-you-need-to-know-about-the-new-EU-AI-Act">EU AI Act</a> if personal information is involved or if AI outputs impact regulated decisions. Governance enables transparency, traceability and accountability.</li> <li><b>Retention and deletion obligations</b>. AI-generated content should follow the same retention, archival and <a href="https://www.techtarget.com/searchDataBackup/tip/Increase-backup-efficiency-with-a-data-destruction-policy">disposal policies</a> as other business records. Unmanaged data increases <a href="https://www.techtarget.com/searchdatacenter/tip/AI-capacity-planning-Balancing-flexibility-performance-and-risk">storage costs</a> and compliance risks.</li> <li><b>Intellectual property</b>. AI outputs may contain copyrighted or proprietary material, creating ownership disputes or licensing concerns.</li> <li><b>Third-party AI vendor risk</b>. External AI platforms can introduce contractual, <a href="https://www.techtarget.com/searchcloudcomputing/tip/A-data-sovereignty-primer-for-cloud-admins">data residency</a>, security and privacy risks. Organizations should define vendor governance requirements and understand how providers store, use and retain submitted data.</li> </ul> <p><a href="https://www.techtarget.com/searchsecurity/tip/Beyond-the-perimeter-The-shift-to-data-centric-protection">Enterprises face challenges</a> with proving origin and authenticity, yet they must be prepared to undergo audits and prove regulatory compliance. Building an AI lifecycle policy and governing data deliberately helps ensure these obligations are met.</p> </section> <section class="section main-article-chapter" data-menu-title="Building an AI data lifecycle policy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Building an AI data lifecycle policy</h2> <p>A practical AI data lifecycle policy should establish governance from the moment AI-generated or synthetic data is created until it is securely disposed of. All aspects of the data's lifecycle require management to ensure privacy, compliance and auditability.</p> <p>Specific lifecycle events include:</p> <ul class="default-list"> <li><b>Inventory AI-generated data</b>. Identify where AI-generated and synthetic data is created, processed, shared and stored across enterprise applications, cloud platforms and third-party AI services. Maintain an up-to-date inventory to <a href="https://www.techtarget.com/it-strategy/tip/14-tips-for-CIOs-managing-shadow-IT-activities">reduce shadow IT</a>.</li> <li><b>Classify data by risk and business value</b>. Categorize data using a risk-based approach that accounts for sensitivity, intended use, regulatory requirements and business impact. Different AI-generated data requires differing levels of governance.</li> <li><b>Capture provenance and metadata</b>. Record the generating model, prompts or source inputs, creation data, version history, ownership and any subsequent modifications to datasets. The goal is to support transparency, reproducibility and audits.</li> <li><b>Define retention and disposal policies</b>. Determine how long different classifications of AI-generated data should be retained, archived or deleted to meet legal, operational and storage requirements.</li> <li><b>Control access and usage</b>. Apply role-based <a href="https://www.techtarget.com/searchsecurity/tip/CISOs-guide-to-centralized-vs-federated-security-models">access controls</a>, encryption, monitoring and usage policies to prevent unauthorized access or misuse.</li> <li><b>Review, adapt and refine governance</b>. Regularly assess governance policies as AI models, business processes and regulations evolve. Monitor compliance through periodic audits, governance metrics and policy reviews to ensure the framework remains effective and aligned with organizational risk tolerance.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Data governance improves capabilities"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data governance improves capabilities</h2> <p>Strong governance of AI-generated and synthetic data accelerates innovation rather than restricting it. It also avoids operational and compliance issues that distract the organization from its business objectives.</p> <p>Examples of how data governance speeds up innovation include:</p> <ul class="default-list"> <li>Enabling faster software testing and AI-assisted development.</li> <li>Reducing privacy risks by limiting the use of production data.</li> <li>Implementing <a href="https://www.forbes.com/councils/forbestechcouncil/2026/01/30/governance-by-design-how-to-engineer-trust-in-the-age-of-ai/">governance-by-design</a> rather than governance after deployment.</li> <li>Using AI governance tools to automate lineage, policy enforcement and monitoring.</li> </ul> <p>Measure success with governance KPIs such as provenance coverage, policy compliance rates, audit results and the percentage of AI-generated data under lifecycle management.</p> </section> <section class="section main-article-chapter" data-menu-title="Wrap up: Governance should scale with AI adoption"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Wrap up: Governance should scale with AI adoption</h2> <p>AI-generated and synthetic data must be managed as strategic enterprise assets with both associated value and risk. Organizations that establish clear ownership, risk-based policies and lifecycle governance now will be better prepared for evolving regulations and future technologies while enabling responsible AI innovation.</p> <p><i>Damon Garn owns Cogspinner Coaction and provides freelance IT writing and editing services. He has written multiple CompTIA study guides, including the Linux+, Cloud Essentials+ and Server+ guides, and contributes extensively to TechTarget Editorial, The New Stack and CompTIA Blogs.</i></p> </section> CIOs need a lifecycle policy for AI generated and synthetic data. Learn how to set lifecycle policies and manage the risks of this type of data. https://cdn.ttgtmedia.com/rms/onlineimages/storage_g1197646065.jpg https://www.techtarget.com/it-infrastructure/tip/Tips-for-the-governance-of-AI-generated-and-synthetic-data Mon, 17 Aug 2026 14:14:00 GMT <p>A series of prominent organisations including UK fossil fuel giant Shell, Dutch consumer and health tech multinational Philips, and the US’ General Electric (GE), are probing security breaches after being ‘named and shamed’ by the <a href="https://www.computerweekly.com/news/366642957/ICO-fines-Cl0p-victim-South-Staffs-Water-over-data-breach" target="_blank" rel="noopener">Cl0p/Clop</a> cyber extortion gang.</p> <p>Cl0p, which has a long history of targeting blue chip firms by compromising commonly used enterprise platforms, named all three organisations among close to 50 others in an update to its dark web leak site.</p> <p>All of the victims appear to have been compromised via a critical zero-day flaw in PTC’s Windchill PDMLink and FlexPLM product lifecycle management software packages, tracked as <a href="https://nvd.nist.gov/vuln/detail/CVE-2026-12569" target="_blank" rel="noopener">CVE-2026-12569</a>.</p> <p>Identified and patched in June and added to Cisa’s <a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog?field_cve=CVE-2026-12569" target="_blank" rel="noopener">Known Exploited Vulnerabilities</a> (Kev) catalogue shortly thereafter, the flaw becomes exploitable by chaining a pre-authentication information disclosure issue in the FlexPLM WSDL endpoint with a server-side issue in Windchill’s login servlet.</p> <p>Ultimately, according to members of the <a href="https://ransom-isac.org/blog/clop-windchill-flexplm-exploitation/" target="_blank" rel="noopener">Ransom-ISAC</a> anti-ransomware community, these conditions enabled the threat actors to deploy webshells, achieve unauthenticated remote code execution (RCE), and exfiltrate their victims’ data.</p> <p>Ransom-ISAC’s Brandon Parsons wrote that Cl0p’s campaign seems to have begun on or around 20 July, when the gang starting emailing multiple users at the affected organisations from randomly compromised accounts.</p> <p>Parsons observed: “This extortion approach is consistent with what we observed with <a href="https://www.computerweekly.com/news/366645849/Cosmetics-giant-Estee-Lauder-victim-of-mass-Oracle-breach" target="_blank" rel="noopener">the Oracle EBS campaign last year</a>, except for the use of new email addresses.”</p> <p>In statements shared with the media, Shell, Philips and GE all confirmed they were in the process of investigating the claims, but none of them named the Cl0p operation specifically.</p> <p>Shell told <i>Reuters </i>it was “working with security teams and relevant experts” on its investigation, while GE said it had “initiated our cyber response protocols and are working to assess the potential issue”.</p> <p>A spokesperson for Philips went further, saying: “Philips has identified and contained an attempted cyber security compromise of a specific enterprise server related to internal data.”</p> <p>According to Cl0p’s unverified claims, the gang has stolen 89GB of data from Shell, 15.5GB from Philips, and 391GB from GE. In Shell’s case this information allegedly includes engineering drawings, photos of oil facilities, scans of test projects and other project plans.</p> <section class="section main-article-chapter" data-menu-title="Cl0p’s tactics work"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Cl0p’s tactics work</h2> <p>As Ransom-ISAC’s analysts observed, Cl0p’s activity in this latest wave of breaches strongly echoes previous campaigns conducted by the gang, targeting the likes of Acellion, Oracle, and perhaps most famously <a href="https://www.computerweekly.com/news/366560872/MOVEit-incident-spurred-UK-decision-makers-to-spend-big-on-cyber" target="_blank" rel="noopener">Progress Software</a>.</p> <p>Three years on from its infamous attack on Progress’ MOVEit file transfer tool, which hit thousands of companies, Cl0p still cleaves to its simple and highly effective ‘business’ model, foregoing traditional encryption ransomware in favour of compromising widely-used software products to target multiple downstream customers, stealing their data, and exposing it if not paid.</p> <p><a title="https://www.cybaverse.co.uk/" href="https://www.cybaverse.co.uk/" target="_blank" rel="noopener">CybaVerse</a> chief technology officer (CTO) Simon Phillips said the developing incident had the potential to be another huge data breach along the lines of Cl0p's previous attacks.</p> <p>“Given Cl0p’s reputation of launching mass attacks, all organisations showing on the leak site must take steps to investigate these claims. They must monitor for unauthorised access and identify if any data has been exfiltrated from their systems,” he said.</p> <p>“Furthermore, any organisation using either PTC Windchill PDMlink or PTC FlexPLM should apply the patches as a priority.”</p> <p>Phillips added: “[A] key question this raises is around vulnerabilities in software, and customer organisations continuing to face the financial repercussions when they are exploited by attackers.</p> <p>“As an industry, we need to rethink how we evaluate security and vendors, looking beyond individual vulnerabilities and identifying broader trends. Vendors with recurring vulnerabilities in critical components, such as those found in internet-facing infrastructure, should be flagged as high-risk.”</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about cyber crime</h3> <ul class="default-list"> <li>AI is accelerating cyber attacks by criminals and hostile states, with attackers faster, more persistent and increasingly collaborative, say experts <a href="https://www.computerweekly.com/news/366643943/Infosecurity-Europe-2026-AI-turbo-charging-cyber-crime-and-response" target="_blank" rel="noopener">speaking at Infosecurity Europe 2026</a>.</li> <li>Computer Weekly reveals for the first time how French cyber spies hacked EncroChat phones <a href="https://www.computerweekly.com/news/366649396/Revealed-Cyber-spies-used-malware-from-GitHub-to-hack-EncroChat-cryptophone-network" target="_blank" rel="noopener">used by organised crime groups</a>.</li> <li>Authorised payment fraud has moved way beyond being a consumer protection issue, <a href="https://www.computerweekly.com/news/366646916/Payment-fraud-a-fully-fledged-transnational-security-threat-says-think-tank" target="_blank" rel="noopener">says the Royal United Services Institute</a>.</li> </ul> </div> </div> </section> Multinational giants such as Philips and Shell may have been affected after the Cl0p cyber extortion gang hacked a popular piece of PLM software. https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/security-hacker-cyber-crime-adobe.jpg https://www.computerweekly.com/news/366648757/Multiple-organisations-investigating-fresh-wave-of-Cl0p-breaches Mon, 17 Aug 2026 14:04:00 GMT <p>Constructing a new data center does not begin with architectural plans. It starts with community communication that educates neighbors and opposition leaders.</p> <p>Data center development affects technology, strategy, infrastructure, capital investment, regulatory relationships, reputation and community trust. Communication helps to reduce uncertainty and surface concerns while decisions remain flexible.</p> <p>This article examines why early education matters and what communities need to know about new data centers. It prepares IT leaders to explain the benefits and trade-offs in terms that matter to community members.</p> <section class="section main-article-chapter" data-menu-title="Preparing the message"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Preparing the message</h2> <p>Modern <a href="https://www.techtarget.com/searchDataCenter/feature/Guide-to-understanding-the-various-types-of-data-centers">data centers</a>, especially those centered around AI, are no longer invisible technology infrastructure. Their scale makes issues such as electricity demand, water use, <a href="https://www.techtarget.com/searchdatacenter/feature/The-increasing-concern-of-data-center-land-acquisition">land use</a>, <a href="https://www.techtarget.com/searchdatacenter/tip/Understanding-the-impact-of-data-center-noise-pollution">noise</a>, construction traffic and economic impact highly visible. Different stakeholders may evaluate the same data center project through different lenses.</p> <ul class="default-list"> <li><b>Technology leaders:</b> Capacity, resilience, <a href="https://www.techtarget.com/searchdatacenter/tip/Enhance-operations-with-decentralized-data-centers">performance</a> and security.</li> <li><b>Community leaders:</b> Infrastructure, quality of life, economic benefits and <a href="https://www.techtarget.com/searchDataCenter/tip/Decarbonizing-data-centers-Turning-sustainability-into-strategy">environmental effects</a>.</li> <li><b>Regulators:</b> Compliance, planning, utilities and public interest.</li> </ul> <p>Whether a data center's impact is positive or negative depends on perspective. For IT leaders, this means community opposition is a risk to mitigate.</p> <p>Begin by linking community concerns to executive-level consequences. These include permitting or approval delays, schedule uncertainty, additional mitigation costs and reputational exposure. Risks also include heightened scrutiny from regulators, investors, customers and employees. Proactive communication is essential to risk management and project continuity, not just to reputation management.</p> <p>Delayed communication can allow uncertainty and assumptions to fill the information gap. Early engagement enables organizations to provide a clear, accurate message that can:</p> <ul class="default-list"> <li>Establish fact-based conversations.</li> <li>Surface concerns before project parameters are fixed.</li> <li>Give leaders time to explain technical trade-offs.</li> <li>Identify stakeholders who need specific information.</li> </ul> <p>Communication helps organizations improve preparedness and decision quality. Technology executives need ownership of the underlying facts, trade-offs, concerns and strategic rationale to communicate value accurately.</p> </section> <section class="section main-article-chapter" data-menu-title="The community value proposition"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The community value proposition</h2> <p>IT leaders should articulate the data center's local value proposition, not just its <a href="https://www.techtarget.com/searchdatacenter/tip/Monetizing-modern-data-centers-Strategies-for-IT-leaders">business rationale</a>. Where possible, articulate specific, measurable benefits to enhance credibility. Clearly distinguish projections from commitments.</p> <p>Potential areas to address include:</p> <ul class="default-list"> <li>Direct and indirect employment.</li> <li>Local tax revenue.</li> <li>Infrastructure investment.</li> <li>Local vendors and economic activity.</li> <li><a href="https://www.techtarget.com/searchdatacenter/tip/Preparing-for-the-data-center-talent-shortage">Workforce development</a> and technical training.</li> <li>Potential improvements to regional digital infrastructure.</li> </ul> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The essential message is what the project means for the community, rather than simply why the company needs this facility. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Avoid presenting economic benefits as a reason communities should overlook legitimate concerns.</p> <p>The essential message is what the project means for the community, rather than simply why the company needs this facility.</p> </section> <section class="section main-article-chapter" data-menu-title="Understanding and communicating key technical drivers"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Understanding and communicating key technical drivers</h2> <p>The message must translate technical realities into community and business implications. Concerns typically span several standard areas, and it is up to IT leaders to provide specific information to address them.</p> <h3>Power and grid requirements</h3> <p>Explain that high-density computing, AI workloads and always-on infrastructure can require substantial electrical capacity. Distinguish between facility requirements, existing grid capacity and potential utility or <a href="https://www.techtarget.com/it-infrastructure/news/366643122/Soma-Energy-launches-to-optimize-AI-data-center-energy-use">grid upgrades</a>.</p> <p>Where possible, clarify who is responsible for infrastructure investments.</p> <h3>Water, cooling and environmental considerations</h3> <p>Explain how cooling <a href="https://www.techtarget.com/it-infrastructure/tip/How-do-data-centers-use-and-manage-water">systems impact water</a> and <a href="https://www.techtarget.com/it-infrastructure/tip/How-much-energy-do-data-centers-consume">energy consumption</a>. Note where impacts depend on cooling design, climate, water sources and operating conditions. Avoid presenting one cooling technology as universally superior; cooling approaches will vary by data center.</p> <h3>Land, noise, traffic and physical footprint</h3> <p>Translate specific infrastructure decisions into tangible local impacts. Explain how facility design, equipment placement, landscaping and operating practices can affect the surrounding community. Distinguish between temporary construction and ongoing operational considerations.</p> <h3>Reliability and security</h3> <p>Communicate why redundancy, <a href="https://www.techtarget.com/it-infrastructure/tip/Data-center-power-backup-options-to-deal-with-downtime">backup power</a>, physical security and network resilience add infrastructure and cost. Connect these requirements to the organization's responsibility to maintain critical digital systems.</p> <p>Each technical explanation should answer the question, "Why does this matter to the community?"</p> </section> <section class="section main-article-chapter" data-menu-title="Establishing a communication strategy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Establishing a communication strategy</h2> <p>Establish a clear communication strategy that emphasizes transparency and prepares the organization for resistance.</p> <h3>Communication strategies</h3> <p>Establishing a clear communication strategy is crucial. Select a communication approach using one of three approaches:</p> <ul class="default-list"> <li><b>Announcement-led.</b> Communicate primarily when a project becomes public. Offers a lower initial effort but greater risk of appearing reactive.</li> <li><b>Information-led.</b> Educate stakeholders about data center infrastructure before specific project decisions. Builds a baseline understanding and reduces unfamiliarity.</li> <li><b>Dialog-led.</b> Combine education with structured opportunities for questions and feedback. Creates opportunities to identify concerns and potentially improve plans.</li> </ul> <h3>Transparency versus uncertainty</h3> <p>Executives may have concerns that early communication will expose plans that are not yet finalized. Leaders can clearly distinguish and explain what is known, what has been evaluated and what remains uncertain. They also identify the factors that drive decisions. Organizations should communicate when additional information will be available.</p> <p>Proactive communication does not require disclosure of confidential or preliminary information.</p> <h3>Preparing for friction</h3> <p>Strong communication will not eliminate all disagreement. Leaders should anticipate scenarios such as misinformation, organized opposition, unexpected infrastructure concerns and changes to project scope. The objective is not to prevent every objection, but to ensure the organization can respond with facts, consistency and credibility.</p> </section> <section class="section main-article-chapter" data-menu-title="Community-centered communication as a strategic capability"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Community-centered communication as a strategic capability</h2> <p>Create a community-centered communication strategy using a three-pronged approach.</p> <h3>Understand stakeholders before developing the message</h3> <p>Identify audiences with different interests and information needs, including residents, local officials, regulators, utilities, businesses, environmental organizations and potential employees. Avoid assuming that one general-purpose message will address every concern.</p> <h3>Establish executive ownership and governance</h3> <p>Coordinate technology, facilities, sustainability, legal, communications, government affairs and executive leaders. Establish a shared source of truth for technical facts, commitments, assumptions and project updates. Define who can make commitments and who is responsible for addressing emerging issues.</p> <h3>Build a two-way information loop</h3> <p>Treat questions and concerns as useful inputs rather than potential hurdles or objections. Categorize issues the organization can address or mitigate versus constraints it cannot change. Listening to a concern does not mean promising the requested outcome.</p> </section> <section class="section main-article-chapter" data-menu-title="The first steps toward communication"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The first steps toward communication</h2> <p>Establish the direction and business objectives before the project narrative. Begin with the organization's broader infrastructure needs and long-term objectives. Explain why resilient computing capacity matters to customers, employees and business continuity.</p> <p>Build a plain-language technical story containing concise explanations of:</p> <ul class="default-list"> <li>Power and grid requirements.</li> <li>Water and cooling.</li> <li>Noise.</li> <li>Traffic and construction.</li> <li>Land use.</li> <li>Economic contribution.</li> <li>Environmental considerations.</li> <li>Reliability and security.</li> </ul> <p>Engage in communication with the community while meaningful decisions remain possible.</p> <ul class="default-list"> <li>Start education before plans are fully finalized.</li> <li>Clearly label assumptions, preliminary plans and firm commitments.</li> <li>Create channels for stakeholder questions and feedback.</li> </ul> <p>Measure understanding and risk by tracking more than communication reach, such as:</p> <ul class="default-list"> <li>Recurring questions.</li> <li>Unresolved concerns.</li> <li>Stakeholder participation.</li> <li>Changes resulting from substantive feedback.</li> <li>Emerging project or reputational risks.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Final thoughts"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Final thoughts</h2> <p>Data center development is more than a technical deployment; it is a community-facing business decision that can face significant opposition. This opposition creates roadblocks, delays and reputational damage. Clear communication begins before the project becomes controversial.</p> <p>CIOs, CTOs and infrastructure leaders should ask:</p> <ul class="default-list"> <li>"What would our community need to understand if we explained this project before asking for its support?"</li> <li>"Which concerns could we address while the project is still flexible?"</li> </ul> <p>A strategic communication approach means educating early, explaining trade-offs honestly, listening before decisions harden and communicating throughout the process.</p> <p><em>Damon Garn owns Cogspinner Coaction and provides freelance IT writing and editing services. He has written multiple CompTIA study guides, including the Linux+, Cloud Essentials+ and Server+ guides, and contributes extensively to TechTarget Editorial, The New Stack and CompTIA Blogs.</em></p> </section> Effective communication is essential in data center development. Engaging the community early addresses concerns and prepares IT leaders for stakeholder interactions. https://cdn.ttgtmedia.com/rms/onlineimages/collab_a306983505.jpg https://www.techtarget.com/it-infrastructure/tip/Building-trust-Engaging-communities-in-data-center-development Mon, 17 Aug 2026 12:18:00 GMT <p>Hybrid work models have fundamentally changed endpoint management priorities, making flexibility and remote access essential. As enterprise decision-makers evaluate their endpoint strategies to improve efficiency while managing costs, they face the question of whether each employee still requires a traditional managed PC.</p> <p>The answer is increasingly complex. The costs associated with migrating to Windows 11, along with expenses related to hardware refresh cycles, are straining resources and budgets. Additionally, the need to support remote, hybrid and temporary employees, along with <a href="https://www.techtarget.com/enterprise-software/tip/Understanding-BYOD-policy-enforcement-and-creation">BYOD initiatives</a>, adds to the challenge.</p> <p>Fortunately, alternatives to traditional hardware exist. Cloud PCs, desktop as a service (DaaS) platforms and virtual desktop infrastructure (VDI) each offer different trade-offs in cost, security, scalability, management complexity and <a href="https://www.techtarget.com/searchitoperations/feature/How-digital-employee-experience-strategy-drives-productivity">user experience</a>. The challenge is determining which option best fits which use case.</p> <p>This article is designed to help CIOs and the administrators who advise them determine when cloud PCs make sense as an alternative to physical devices.</p> <section class="section main-article-chapter" data-menu-title="How do cloud PCs, DaaS and VDI platforms differ?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How do cloud PCs, DaaS and VDI platforms differ?</h2> <p>The three terms are closely related but describe different aspects of virtual desktop delivery. Understanding their relationship requires distinguishing between deployment models and service types.</p> <p>DaaS and VDI are deployment models that differ by the hosting infrastructure, with cloud PCs being a type of DaaS offering.</p> <h3>DaaS</h3> <p>With DaaS, a cloud provider delivers and supports the virtual desktop infrastructure. Cloud-hosted desktops simplify endpoint management by shifting responsibility to cloud service providers, freeing up enterprise IT teams to focus on other concerns. Organizations consume desktops as a subscription without maintaining the underlying platform. The approach reduces operational overhead while retaining many benefits of virtual desktops.</p> <h3>VDI</h3> <p>With VDI, the organization's IT team builds and maintains the virtual desktop platform, typically in an on-premises or private cloud environment. This requires expertise in servers, storage, networking and virtualization, which <a href="https://www.techtarget.com/searchCIO/tip/The-CIOs-guide-to-skills-based-workforce-planning">might be challenging to find</a>. VDI offers the most control but adds the greatest management complexity.</p> <h3>Cloud PCs</h3> <p>Cloud PCs are a subset of DaaS. For example, each <a href="https://www.techtarget.com/searchvirtualdesktop/tip/Comparing-Windows-365-vs-Azure-Virtual-Desktop">Windows 365 Cloud PC</a> user connects to a persistent, dedicated desktop with fixed resources. Cloud PCs offer organizations simplicity and predictable licensing while providing users with a PC-like experience.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/virt_desktop-vdi_vs_daas-f.png 1280w" alt="Chart comparing VDI vs. DaaS" data-credit="Informa TechTarget" height="247" width="560"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Cloud PCs, DaaS and virtual desktop examples"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Cloud PCs, DaaS and virtual desktop examples</h2> <p>Cloud PCs are hosted by a provider and streamed to devices over a network. Users receive a consistent desktop system without using high-performance local hardware.</p> <p>Consider the key examples for each category.</p> <h3>Cloud PC platforms</h3> <ul class="default-list"> <li>Windows 365 Cloud PCs provide fully managed Windows desktops that operate in the cloud.</li> </ul> <h3>DaaS and cloud virtual desktop services</h3> <ul class="default-list"> <li>Amazon Workspaces supports both Windows and Linux desktop environments. &nbsp;</li> <li>Citrix DaaS provides an enterprise-grade virtual desktop delivery.</li> </ul> <h3>Cloud VDI platforms</h3> <ul class="default-list"> <li>Azure Virtual Desktop provides scalable virtualization for Windows desktops.</li> <li>VMware Horizon Cloud offers hybrid and multi-cloud desktop options.</li> </ul> <h3>Cloud-hosted Mac environments</h3> <ul class="default-list"> <li>MacStadium offers dedicated macOS cloud infrastructure. &nbsp;</li> <li><a href="https://www.techtarget.com/searchCloudComputing/tip/How-to-launch-an-Amazon-EC2-Mac-instance">Amazon EC2 Mac</a> instances operate on Apple hardware in AWS.</li> </ul> <p>Cloud PCs are usually associated with Windows, although persistent cloud desktops also exist for Linux. Due to Apple's licensing, <a href="https://www.techtarget.com/searchvirtualdesktop/tip/Understanding-the-DaaS-options-for-Macs">macOS cloud desktops</a> are more specialized, typically delivered as cloud-hosted Mac instances running on dedicated Apple hardware.</p> </section> <section class="section main-article-chapter" data-menu-title="When cloud PCs make sense -- and when they don't"> <h2 class="section-title"><i class="icon" data-icon="1"></i>When cloud PCs make sense -- and when they don't</h2> <p>Organizations should evaluate each approach based on relevant business considerations and technical implications, recognizing that a hybrid approach often delivers the best results. The decision often comes down to understanding the fundamental differences between traditional and cloud-based models.</p> <p>The traditional hardware refresh cycle follows a <a href="https://www.techtarget.com/whatis/definition/CAPEX-capital-expenditure">Capex</a> approach, which requires a significant upfront investment and ongoing management overhead. While this approach offers maximum control, it introduces procurement complexity, supply chain security risks, imaging requirements and device replacement challenges.</p> <p>Cloud PCs operate on an <a href="https://www.techtarget.com/whatis/definition/OPEX-operational-expenditure">Opex</a> model, offering faster scaling, easier onboarding and offboarding, simplified endpoint management and improved remote user support.</p> <p>Many organizations evaluate Windows-based cloud PC options during a hardware refresh cycle, when attention naturally shifts to endpoint costs, workflow changes, new applications and updated security and compliance standards.</p> <p>Organizations should evaluate cloud PC options across six key areas:</p> <ul class="default-list"> <li><b>Financial model<a name="_Hlk234475741"></a>. </b>Spending shifts to an Opex model using predictable subscription pricing.</li> <li><b>Total cost. </b>Reduces hardware spending but adds recurring subscription costs. Organizations should monitor license utilization to avoid paying for inactive users.</li> <li><b>Business agility and scalability. </b>New desktops can be provisioned or retired in minutes, making it easier to manage growth or add contractors and seasonal workers. Cloud PCs enhance remote-first organizations and rapidly expanding teams.</li> <li><b>User experience. </b>Delivers a <a href="https://www.techtarget.com/searchitoperations/tip/Strategies-to-boost-DEX-scores-and-employee-productivity">consistent experience</a> across devices but requires reliable network connectivity and sufficient cloud resources.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Technical considerations"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Technical considerations</h2> <p>For IT administrators, migrating users to cloud PCs changes the operational model, but it does not eliminate desktop management or support.</p> <p>Provisioning is faster, with standardized desktops and applications available quickly, reducing imaging and deployment effort. For example, Microsoft's <a target="_blank" href="https://learn.microsoft.com/en-us/windows-365/enterprise/provisioning" rel="noopener">automated process for provisioning Windows 365</a> consists of creating and configuring the <a href="https://www.techtarget.com/it-infrastructure/definition/What-is-a-virtual-machine-VM-and-how-does-it-work">virtual machine</a>, installing software, applying custom configurations and then adding the user's Active Directory account to allow logins.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Traditional hardware refreshes remain practical for power users, offline work and specialized workloads. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Infrastructure administration also shifts. The cloud provider manages the underlying platform. In-house IT talent focuses on identity, policies, endpoint access, applications and user support, using tools such as Microsoft Intune to manage both physical devices and Windows 365 Cloud PCs. Security operations must adapt to a cloud-first model, with strong emphasis on identity, conditional access, data controls and compliance monitoring.</p> <p>Centralized desktops can also simplify recovery and improve business continuity metrics. However, IT teams must monitor <a href="https://www.techtarget.com/searchNetworking/tip/Why-network-modernization-is-crucial-for-business-continuity">network performance</a>, cloud resource allocation and application compatibility. Implementing additional services, such as <a target="_blank" href="https://learn.microsoft.com/en-us/windows-365/enterprise/introduction-windows-365-reserve" rel="noopener">Windows 365 Reserve</a>, can help prevent outages from affecting users.</p> <p>Neither approach is inherently better. Traditional hardware refreshes remain practical for power users, offline work and specialized workloads. However, they require larger upfront investments. Cloud PCs excel in teams that prioritize operational agility, rapid provisioning, simplified management and support for distributed workforces. However, cloud costs can appear misleading and unpredictable if organizations overprovision or fail to reclaim unused licenses.</p> <p>Often, the ideal strategy is a <a href="https://www.techtarget.com/searchVirtualDesktop/opinion/PC-as-a-service-is-an-alternative-and-a-complement-to-DaaS?utm_source=chatgpt.com">hybrid approach</a> that balances cost, flexibility and enterprise needs while improving ROI.</p> </section> <section class="section main-article-chapter" data-menu-title="Cloud PC governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Cloud PC governance</h2> <p>Effective governance is essential to cloud PC management. While governance for traditional devices centers on long-term asset planning, procurement, refresh cycles and capital budgeting, the concerns for cloud PC deployments differ.</p> <p>Cloud PC governance needs subscription management, user eligibility and cost optimization. IT leaders must establish policies for provisioning, deprovisioning and reclaiming licenses to prevent unnecessary spending. The model offers greater flexibility to scale with changing workforce needs but requires ongoing oversight of recurring operational costs.</p> <p>Both approaches require governance that aligns endpoint investments with business priorities, workforce strategy and risk tolerance.</p> </section> <section class="section main-article-chapter" data-menu-title="Key questions IT leaders should ask before choosing an endpoint strategy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Key questions IT leaders should ask before choosing an endpoint strategy</h2> <p>The decision to adopt cloud PCs should be driven by workforce needs and corporate objectives rather than technology trends. IT leaders should begin by asking questions related to the organization's needs and infrastructure, including the following:</p> <ul type="disc" class="default-list"> <li>What percentage of users truly need high-performance local hardware?</li> <li>How predictable is workforce growth?</li> <li>Are contractors, temporary workers or seasonal employees a significant portion of the workforce?</li> <li>Which licensing model best fits the organization?</li> <li>Does the IT team already have centralized management for physical devices that can also manage cloud PCs?</li> <li>Does the current network offer adequate performance for cloud-delivered PCs?</li> <li>Will existing governance practices effectively manage licensing and avoid overprovisioning?</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Implementation strategy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Implementation strategy</h2> <p>Organizations should deploy cloud PCs strategically using pilot programs, phased rollouts and proactive change management to support successful adoption and implementation.</p> <p>As workforce needs continue to evolve, the right endpoint strategy has grown into a business decision with technical implications. Start by matching available technologies to specific user needs, balancing cost, performance, security and operational efficiency. A comprehensive, strategic evaluation positions the organization for greater agility, security and scalability tomorrow.</p> <p><em>Damon Garn owns Cogspinner Coaction and provides freelance IT writing and editing services. He has written multiple CompTIA study guides, including the Linux+, Cloud Essentials+ and Server+ guides, and contributes extensively to TechTarget editorial, The New Stack and CompTIA Blogs.</em></p> </section> Hybrid work is reshaping endpoint management. Learn when cloud PCs, DaaS and VDI make sense versus traditional hardware and how to balance cost, flexibility and performance needs. https://cdn.ttgtmedia.com/rms/onlineimages/cloud_g1265279914.jpg https://www.techtarget.com/enterprise-software/feature/When-cloud-PCs-make-more-sense-than-another-hardware-refresh Mon, 17 Aug 2026 12:00:00 GMT <p>As next-generation satellite networks transform connectivity at sea, the maritime satellite communications market is entering a new phase of growth with non-geostationary satellite orbit (NGSO) networks having changed the economics and performance of maritime connectivity, according to research from Novaspace.</p> <p>The 14^th version of the <a href="https://nova.space/hub/product/prospects-for-maritime-satellite-communications/"><em>Maritime satellite communications</em></a> report from the independent consulting and market intelligence firm dedicated to the global space sector noted that the maritime satellite communications market is undergoing its most significant transformation in decades.</p> <p>Specifically, it said the rapid adoption of NGSO constellations, evolving customer expectations, increasing bandwidth requirements and changing regulatory environments are reshaping how connectivity is delivered across commercial and recreational fleets worldwide.</p> <p>In all, the study calculated that global maritime satellite service revenues are projected to grow from $2.28bn in 2025 to $3.79bn by 2035, driven by accelerating adoption of NGSO services and increasing demand for always-on connectivity across commercial and recreational fleets.</p> <p>The report forecasts that the global fleet of very small aperture terminal (VSAT)-equipped vessels will surpass 600,000 by 2035, with growth increasingly fuelled by smaller vessels adopting broadband connectivity to support digital operations, regulatory compliance, crew welfare, safety and operational efficiency.</p> <p>Moreover, as maritime digitalisation accelerates, satellite capacity demand is expected to increase nearly fivefold over the next decade, from&nbsp;the current 500 Gbps to approximately 2.5 Tbps by 2035, reflecting said Novaspace the growing reliance on bandwidth-intensive applications across the maritime industry.</p> <p>The report identifies NGSO adoption as the primary driver of market transformation. Although deployment timelines have been modestly affected by delays to <a href="https://www.computerweekly.com/news/366640878/Delta-in-flight-connectivity-takes-off-with-Amazon-Leo">Amazon’s LEO constellation</a>, NGSO service revenues are still expected to reach&nbsp;$3.25bn by 2035. Lower-cost terminals, simplified installation, improved network performance and increasingly competitive service offerings continue to accelerate adoption across all major vessel segments.</p> <p>Novasapce was adamant that this shift was rapidly changing the competitive landscape. NGSO services represented 48% of maritime satellite service revenues in 2025 and are forecast to account for 86% by 2035. At the same time, NGSO systems are expected to support approximately 98% of total maritime satellite capacity demand, reshaping <a href="https://www.computerweekly.com/news/366645087/SES-Tototheo-global-expand-multi-orbit-maritime-services">how connectivity is delivered at sea</a>.</p> <p>Yet despite this transformation, the report found that GEO satellite networks will continue to play an important role. Many commercial operators are adopting multi-orbit connectivity strategies that combine GEO and NGSO services to improve resilience, global coverage and service continuity. Rather than replacing GEO, the market is evolving toward integrated, hybrid network architectures.</p> <p>“NGSO networks have fundamentally changed the economics and performance of maritime connectivity,” said Vishal Patil, senior consultant at Novaspace. “Over the next decade, they will become the backbone of maritime communications, delivering higher capacity, lower latency, more flexible services and a significantly improved user experience for vessel operators worldwide.”</p> <p>The study came after Novaspace released a report showing that the <a href="https://www.computerweekly.com/news/366640784/Starlink-reshapes-satellite-communications-as-industry-enters-terabit-era">satellite communications market has expanded rapidly over the past three years</a> or so, with what it referred to as the <a href="https://www.computerweekly.com/news/366618875/Starlink-gains-higher-orbit-in-Europe">Starlink</a> effect further accelerating demand and reshaping the satellite connectivity market.</p> <p>The eighth edition of&nbsp;Novaspace’s&nbsp;<em><a href="https://nova.space/hub/product/high-throughput-satellites/">High throughput satellites</a>&nbsp;</em>(HTS) report offered a strategic look at the evolving HTS landscape, covering capacity supply, demand dynamics across verticals, market drivers and the infrastructure investments shaping the future of satellite connectivity.&nbsp;In all, it found global demand for capacity reaching 218Tbps by 2034, while service revenues are set to more than double to $76bn over the same period.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about maritime communications</h3> <ul class="default-list"> <li><a href="https://www.computerweekly.com/news/366645087/SES-Tototheo-global-expand-multi-orbit-maritime-services">SES, Tototheo global expand multi-orbit maritime services</a>: Space solutions company expands partnership with connectivity and technology firm promising to deliver worldwide maritime customers with consistent, reliable connectivity that supports critical vessel operations.</li> <li><a href="https://www.computerweekly.com/news/366646478/SES-to-enable-communications-for-Starlab-commercial-space-station">SES to&nbsp;enable communications for Starlab commercial space station</a>: Next-generation, AI-enabled commercial space station developer teams with satellite operator to provide always-on low orbit relay services supporting real-time mission awareness.</li> <li><a href="https://www.computerweekly.com/news/366639282/AIDA-Cruises-fleet-sets-sail-with-OpenRoaming-for-Wi-Fi-connectivity">AIDA Cruises fleet sets sail with OpenRoaming for Wi-Fi connectivity</a>: Global wireless ecosystem consortium&nbsp;deploys technology for cruise ship operator with Wi-Fi for all passengers and staff, as well as 24/7 cruise operations, safety, guest services and entertainment.</li> <li><a href="https://www.computerweekly.com/news/366643392/Ericsson-Net-Feasa-deliver-maritime-connectivity-with-4G-5G-agentic-AI">Ericsson, Net Feasa deliver maritime connectivity with 4G, 5G, agentic AI</a>: Partnership looks to provide the maritime industry with reliable, secure connectivity, integrated with agentic AI-driven tech in use cases including reefer monitoring, dangerous goods handling and early heat detection.</li> </ul> </div> </div> Novaspace forecasts VSAT-equipped vessel fleet will exceed 600,000 as demand for digital operations, crew welfare and high-capacity connectivity accelerates https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Satellite-space-Earth-adobe-hero.jpg https://www.computerweekly.com/news/366648984/Non-geostationary-satellite-orbit-services-reshape-maritime-connectivity Mon, 17 Aug 2026 11:55:00 GMT <p>Research from operator <a href="https://www.vodafonethree.com/">VodafoneThree</a> has found British workers lack the connectivity confidence to work effectively on the go, but could unlock more than three weeks’ worth of currently unproductive time a year.</p> <p>Specifically, the study found that by running their lives more effectively from their mobile phones, British workers could deliver a potential £115bn productivity boost to the economy.</p> <p>The research was conducted by <a href="https://censuswide.com/">Censuswide</a>, among a sample of 2,000 UK adults aged over 18 with data collected between 15 and 19 June 2026. Modelling on the economic impact of improved mobile working used data from the UK Office of National Statistics (ONS) to estimate the potential gross value added to the economy of further working time.</p> <p>Fundamentally, a third of the UK feels unable to leave their home or office <a href="https://www.computerweekly.com/news/366644058/Wi-Fi-7-gains-ground-but-advanced-Wi-Fi-standards-lag-in-Europe">Wi-Fi</a>, and almost half (46%) spend most of their working day at a desk as a result. This lack of flexibility extends beyond the working week, with more than a third (34%) saying their weekend to-do list would be shorter if they could be more productive on the go.</p> <p>On average, Brits waste almost two hours of productivity a week on commuting, and over an hour sitting in waiting rooms and waiting to pick up children or dependents. Overall, this unproductive time totals more than 10 hours a week, more than France, Germany, Spain, Australia, Singapore, Hungary and South Korea.</p> <p>The research also showed that if the UK matched the mobile working mentality of Hungary, the most productive on-the-go nation in the study, people could claw back 22 days a year. The biggest time savings could come from accessing and collaborating on work documents, taking calls on commutes and joining remote NHS consultations from phones.</p> <p>Almost half (43%) of employed Brits say they would prioritise working on the move if they felt confident in the quality of the UK’s networks, including collaborating with AI (16%) and rescheduling <a href="https://www.computerweekly.com/news/366618659/Vodafone-claims-video-call-over-satellite-landmark">video calls</a> while they are out of the office (16%).</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about UK mobile</h3> <ul class="default-list"> <li><a href="https://www.computerweekly.com/news/366646694/UK-emergency-services-struggle-with-unreliable-connectivity">UK emergency services struggle with unreliable connectivity</a>: Survey reveals a stark 5G adoption gap in UK emergency services, where connectivity is recognised as mission-critical, yet only 22% use 5G routers while 44% remain reliant on mobile hotspots.</li> <li><a href="https://www.computerweekly.com/news/366648612/EE-maintains-UK-mobile-quality-leadership">EE maintains UK mobile quality leadership</a>: Report assessing UK mobile performance in the first half of 2026 finds BT-owned leading provider fends off growing competition to lead in nation-wide market testing.</li> <li><a href="https://www.computerweekly.com/news/366645957/VodafoneThree-calls-for-policy-changes-to-drive-UK-mobile-growth">VodafoneThree calls for policy changes to drive UK mobile growth</a>: Mobile network operators in the UK are battling with energy costs, planning red tape and regulations, all of which are impacting their investment plans.</li> <li><a href="https://www.computerweekly.com/news/366639059/UK-government-calls-for-review-into-mobile-market">UK government calls for review into mobile market</a>: UK government creates programme to anticipate how the mobile market, and technologies that underpin it, will evolve over the next decade.</li> </ul> </div> </div> <p>Modelling from Development Economics estimated that improved connectivity could save the NHS more than 35 million missed remote appointments a year, a potential saving of £1.36bn a year.</p> <p>The study also highlighted how these benefits could also extend to weekends. Respondents said that time saved from being more productive on their mobile devices could cut their weekend to-do lists (34%) by helping them book all GP appointments through apps or their phones (23%), pay utility bills (27%) and buy tickets (16%).</p> <p>“Boosting the UK’s productivity doesn’t have to mean spending more hours behind our desks,” said Andrea Donà, chief network officer at VodafoneThree. “But to change the way the nation works, we need mobile networks that keep us connected to colleagues, technology and essential services on the move.</p> <p>“Our <a href="https://www.computerweekly.com/news/366631519/Ericsson-Nokia-join-VodafoneThree-11bn-network-build-out">£11bn network investment</a> is already helping communities across the UK to be more connected, productive and prosperous,” he said. “But to truly catch up with the rest of Europe and beyond, we have to treat our mobile networks as Critical National Infrastructure. The UK government is rightly taking this issue seriously. With improvements to the planning system and regulations fit for the digital economy, our networks can help to make public services more accessible, close digital divides and lay the foundations for growth.”</p> Research from leading UK mobile operator reveals the need to boost mobile connectivity confidence in the UK https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Vodafone-first-UK-5G-OpenRAN-site-hero.png https://www.computerweekly.com/news/366649206/Connectivity-confidence-could-add-1155bn-to-UK-economy Mon, 17 Aug 2026 11:45:00 GMT <p>In conversations with physicians during patient interactions, patients may bring up social determinants of health challenges, such as housing or food instability, transportation barriers or financial strain.</p> <p>Sometimes AI scribes, which are increasingly used to record patient visits, do help to support SDOH data capture and allow this data to become part of a patient's EHR. But not always.</p> <p>As Maxim Topaz, Ph.D., associate professor of nursing at Columbia University and senior research scientist at the Center for Homecare Policy and Research at VNS Health, noted, AI scribes are suitable for capturing verbal exchanges clearly with a microphone, but social issues are sometimes missed.</p> <p>"Social needs are often the part of a visit that is said quietly, said indirectly, said in a second language, or not said in words at all," Topaz said. "That mismatch is where most of the&nbsp;SDOH&nbsp;risk sits."</p> <p>Currently, Topaz sees ambient scribes widening the gap in capturing SDOH data. He estimated that <a href="https://www.nature.com/articles/s41746-025-01895-6">30% of physician practices use AI scribes today</a>, and most systems discard the audio and transcript shortly after the note is generated.</p> <p>"Without that audit trail, you cannot even measure whether social needs are being captured or quietly lost," Topaz noted.</p> <p>However, Kristine Lee, M.D., associate executive director and chief transformation officer for The Permanente Federation, believes that ambient scribes can also be helpful in capturing SDOH data.</p> <p>"AI scribes [can be configured to] capture the full context of a visit, ensuring social needs are documented so care teams can flag challenges, such as food insecurity and housing instability, and route patients to essential social services," Lee says.</p> <p>Thus, AI scribes can help or hinder SDOH data capture, and it is currently up to healthcare providers to avoid the pitfalls.</p> <section class="section main-article-chapter" data-menu-title="How AI scribes are amplifying SDOH challenges"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How AI scribes are amplifying SDOH challenges</h2> <p>Large language models that are trained on standard collections of medical text and guidelines could fail to document patients' psychosocial needs unless they are designed to factor in social determinants of health, according to Lee.</p> <p>When LLMs fail to identify SDOH, that could leave patient data incomplete in EHRs, as a <a href="https://www.nature.com/articles/s41746-023-00970-0">2024 study</a> in <i>npj Digital Medicine</i> explained.</p> <p>"SDOH are rarely documented comprehensively in structured data in the electronic health records (EHRs), creating an obstacle to research and clinical care," the study stated.</p> <p>That's because SDOH data in clinic notes is generally in the form of "free text" or unstructured data, and when this data can't be incorporated completely into an EHR, that creates barriers to data access for research and clinical care, the <i>npJ Digital Medicine </i>authors wrote.</p> <p>Meanwhile, Topaz noted the wide gap between what doctors and patients discuss in a visit and the information that ends up in the EHR.</p> <p>For instance, in a home healthcare study he conducted with several other authors, <a href="https://pubmed.ncbi.nlm.nih.gov/35663115/">about 50.5% of patient problems and 20.8% of interventions</a> discussed during a patient visit never made it into the EHR, according to Topaz.</p> <p>The reason? They were considered out of the immediate scope of the visit.</p> <p>"Social needs are exactly the kind of content that gets dropped that way," Topaz said. "An ambient scribe sits on top of that same conversation, so it inherits whatever is raised or missed in the room and then makes its own decision about what is relevant enough to chart."</p> <p>He explained that unless an EHR system is deliberately designed to highlight social needs, the program simply replicates the existing gap rather than closing it.</p> <p>Another key problem with the speech recognition capabilities of AI scribes is that they don't always transcribe speech accurately for people with accents or those who cannot speak English fluently.</p> <p>"Our own work and others' have shown these systems transcribe Black patients, and patients with accents or limited English proficiency, less accurately than White, native-English speakers," Topaz said.</p> <p>In addition, social needs are often communicated indirectly or nonverbally, and the AI system cannot pick up visual cues as a clinician or in-person scribe could.</p> <p>"A [human] scribe from the same community may also recognize cultural and social context that the model simply does not," he added.</p> <p>Additionally, a <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC12460601/">2025 study</a> by Topaz and others in <i>npj Digital Medicine</i> found that filtering algorithms could cause ambient scribes to worsen documentation gaps. AI filters could eliminate certain SDOH data, like housing instability information, that would be clinically important to include.</p> <p>"Each of these failures lands hardest on the patients who already carry the most social risk, which is the textbook way a disparity gets wider," he said.</p> </section> <section class="section main-article-chapter" data-menu-title="But ambient scribes can also help address SDOH issues"> <h2 class="section-title"><i class="icon" data-icon="1"></i>But ambient scribes can also help address SDOH issues</h2> <p>Though ambient scribes pose risks in terms of widening care gaps, they also offer benefits that could address SDOH challenges.</p> <p>For example, AI scribes allow physicians to spend more time speaking with patients, enabling them to build a rapport, which could encourage patients to share SDOH information with providers, according to Lee.</p> <p>In fact, at the Permanente Medical Group in Northern California,&nbsp;<a target="_blank" href="https://permanente.org/analysis-ai-scribes-save-physicians-time-improve-patient-interactions-and-work-satisfaction/" rel="noopener">39% of patients said</a>&nbsp;their doctors spent more time speaking directly to them when using AI scribe technology, Lee said, citing the results of a <a href="https://catalyst.nejm.org/doi/full/10.1056/CAT.25.0040">study</a> she co-authored in <i>NEJM Catalyst</i>. These direct interactions allowed patients to feel safer to share details of SDOH vulnerabilities with their physicians.</p> <p>Lee further noted that AI scribes can be configured to capture the full context of patient visits to ensure social needs are documented. The scribes used at the Permanente Medical Group are customized to flag patient challenges, such as food insecurity and housing instability, and can direct patients to social services.&nbsp;</p> <p>"We are looking forward to advanced input EHR technology to incorporate these more fully to make it easier for clinical teams to respond appropriately," she said.</p> <p>The <i>NEJM Catalyst</i> study also revealed how AI scribes reduce physician workload. It saves users more than 15,700 hours, which is equal to 1,794 working days, over one year, compared with non-users of AI scribes.</p> <p>The extra time also allows physicians to address SDOH issues directly with patients, according to Lee.</p> <p>"By reclaiming thousands of hours once spent on documentation, physicians can focus more on proactive, personalized care for vulnerable populations," Lee said.</p> </section> <section class="section main-article-chapter" data-menu-title="How to avoid AI scribe pitfalls in addressing SDOH"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How to avoid AI scribe pitfalls in addressing SDOH</h2> <p>Providers use AI scribes not knowing if they will ultimately widen or close an SDOH gap, according to Topaz.</p> <p>"There is a genuine upside case. Ambient capture could catch a housing or food-insecurity comment that a rushed clinician would never have stopped to type," Topaz said. "That only happens if the model is built to recognize and keep that content, if the transcription is accurate for the patient who is speaking, and if the clinician actually reviews the note."</p> <p>Here are steps that health IT leaders can take to reduce the chances of AI scribes amplifying SDOH gaps.</p> <p><b>Screening step: </b>Topaz recommended that providers add a structured, "intentional" screening step to check for SDOH gaps. He also advised that AI scribes serve as a supplement to provider workflows rather than a replacement.</p> <p>Lee explained that this screening step is required for Permanente physicians and clinicians.</p> <p>"The technology is designed to produce a draft," Lee said. "Clinicians remain the final medical decision-makers and are responsible for ensuring medical, legal and billing accuracy of the record."<br><br>She added that physicians and clinicians at Kaiser Permanente are required to review, edit and approve all AI-generated notes.</p> <p>"This helps catch omissions of structural psychosocial needs or contextual nuances," Lee said.</p> <p>Topaz also advised that clinicians be trained to review AI notes for omissions of SDOH data. Omissions are more difficult to spot than obvious mistakes, he added, so having this screening process in place will be helpful to identify missing data.</p> <p><b>Audit trail: </b>Topaz suggested keeping an audit trail to determine whether social needs are being captured correctly or lost.</p> <p>"If the audio or transcript disappears instantly, you have given up the ability to verify a note or investigate a complaint, so push for systems that keep traceable references back to the source," he said.</p> <p><b>Adapt AI scribes to healthcare settings:</b> Adjusting AI scribes to a specific type of practice could enable them to become more attuned to SDOH needs and create notes accordingly, Lee noted.</p> <p><b>"</b>A community health center managing chronic conditions and complex&nbsp;social determinants of health&nbsp;needs requires a different note structure than an urgent care clinic," she explained.</p> <p><b>Involve patients and community members in decision-making: </b>Keeping patients and community members involved in decisions about how tools are deployed and who signs off on them could help resolve questions and concerns about how scribe recordings of vulnerable populations are used, Topaz suggested.</p> <p>By following these tips, healthcare providers can help bridge the gap between ambient scribes and SDOH.</p> <p><i>Brian T. Horowitz started covering health IT news in 2010 and the tech beat overall in 1996.</i></p> </section> Despite their advantages for clinician productivity, AI scribes could worsen social determinants of health problems; still, there are steps providers can take to address these issues. https://cdn.ttgtmedia.com/rms/onlineimages/ehr_g866433760.jpg https://www.techtarget.com/searchhealthit/feature/AI-scribes-may-miss-critical-SDOH-data-Heres-how-to-close-the-gap Mon, 17 Aug 2026 11:05:00 GMT <p>Autonomous infrastructure comprises AI-driven, self-managing policy-based systems for IT operations. It shifts from rigid automation to data-driven decision-making. Modern IT ops require increasing AI autonomy to achieve the best results. The critical intersection is:</p> <ul class="default-list"> <li>Complexity of hybrid and multi-cloud environments.</li> <li>Advances in AI and observability.</li> <li>Pressure to reduce costs and improve resilience while maintaining agility.</li> </ul> <p>IT professionals now act as governors, not just operators. However, new risks in security, data and accountability must be actively managed. Organizations that invest in governance, data quality and workforce evolution will unlock their full value while avoiding systemic risk.</p> <section class="section main-article-chapter" data-menu-title="Automation value and risk"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Automation value and risk</h2> <p>For IT leaders, balancing value against risk now means shifting some risks from human control to system autonomy.</p> <p>Where autonomy delivers value:</p> <ul class="default-list"> <li><b>Availability and resilience</b>. Reduce downtime using <a href="https://www.techtarget.com/searchitoperations/tip/Self-healing-IT-systems-Benefits-challenges-and-use-cases">self-healing systems</a> and predictive remediation.</li> <li><b>Cost optimization.</b> Enable dynamic resource allocation and scaling with less manual intervention.</li> <li><b>Operational efficiency.</b> Provide lower incident volume, faster resolution and reduced administrative effort.</li> </ul> <p>Where risk emerges:</p> <ul class="default-list"> <li><b>Decision transparency.</b> Limited explainability of AI-driven actions and challenges in root cause analysis.</li> <li><b>Failure propagation at scale.</b> Misconfigured policies or faulty models can cascade rapidly.</li> <li><b>Security implications.</b> AI control planes are high-value targets. Autonomous responses may unintentionally disrupt services and expose them to adversarial inputs or model manipulation.</li> <li><b>Data dependency and quality.</b> Watch reliance on accurate telemetry and historical data, as well as biased or incomplete data that can drive flawed decisions.</li> <li><b>Vendor lock-in and interoperability constraints.</b> Proprietary orchestration platforms and difficulty integrating across legacy and multi-cloud environments.</li> </ul> <p>Autonomous infrastructure delivers measurable gains but changes the risk catalog. New governance practices are required to protect operations.</p> </section> <section class="section main-article-chapter" data-menu-title="Governance enables safe autonomy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Governance enables safe autonomy</h2> <p>Governance is critical for autonomous infrastructure. The organization is shifting from a traditional manual or automated operational approach to a policy-driven control system that relies on <a target="_blank" href="https://cloudsecurityalliance.org/blog/2026/01/28/levels-of-autonomy" rel="noopener">AI-based autonomy</a>. Governance ensures this autonomy enhances, not replaces, accountability. Some core governance principles include:</p> <h3>Human-in-the-loop oversight</h3> <ul class="default-list"> <li>Define autonomy tiers, including advisory, supervised and fully autonomous. Not every system requires full autonomy, especially when risk increases.</li> <li>Require approval for high-impact actions and novel scenarios, allowing human decision-making to override autonomy.</li> </ul> <h3>Auditability and observability</h3> <ul class="default-list"> <li>Establish full traceability of decisions, inputs and actions to foster trust and prove compliance.</li> <li>Configuring logging for compliance, forensics and continuous improvement.</li> </ul> <h3>Policy-as-code framework</h3> <ul class="default-list"> <li>Encode business intent, including cost thresholds, performance goals and risk tolerance.</li> <li>Align system behavior with enterprise priorities.</li> </ul> <p>AI-driven controls require additional management policies to meet compliance goals and reduce risk. Governance must implement these policies by:</p> <ul class="default-list"> <li>Establishing clear ownership of autonomous decisions.</li> <li>Aligning autonomy with enterprise AI ethics standards.</li> <li>Constructing guardrails to block unintended or non-compliant actions.</li> </ul> <p>Technical control mechanisms include "circuit breakers" to halt unsafe behavior before it disrupts operations or cascades across systems. Sandboxed testing and simulation before deployment also reduces unintended consequences and demonstrates due diligence.</p> <p>Governance directives will define escalation paths for anomalies, enabling humans to enter the loop and evaluate potentially disruptive behavior. Governance is the scaling mechanism for trust. Organizations that formalize it early will adopt autonomy faster, more safely and with better compliance.</p> </section> <section class="section main-article-chapter" data-menu-title="Redefining IT ops"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Redefining IT ops</h2> <p>Evolving an enterprise environment to an autonomous infrastructure requires changing roles and updating measurement practices.</p> <p><b>Changing IT roles and skills</b></p> <ul class="default-list"> <li>Shift from manual operators or automation authors to policy designers, automation architects and system governors.</li> <li>Increased demand for hybrid expertise consisting of infrastructure, data management, AI and governance skills.</li> </ul> <p><b>Changing metrics</b></p> <ul class="default-list"> <li>Move away from measuring ticket volume and mean time to resolution.</li> <li>Opt for autonomous resolution rate, policy effectiveness, and business-aligned reliability outcomes.</li> </ul> <p>The primary transformation is not technical; it's organizational and cultural. It includes relying on cross-functional DevOps, <a href="https://www.techtarget.com/searchsecurity/tip/Streamline-SecOps-with-SOAR-workflows-and-playbooks">SecOps</a> and <a href="https://www.techtarget.com/searchcloudcomputing/tip/The-business-case-for-FinOps-to-control-cloud-spending">FinOps</a> teams. Organizations must foster trust in autonomous systems and satisfy resistance to role changes across teams. Allocate resources for change management and employee <a href="https://www.techtarget.com/searchCloudComputing/tip/How-to-use-AI-to-bridge-the-cloud-skills-gap">upskilling</a>.</p> </section> <section class="section main-article-chapter" data-menu-title="Strategic implications and adoption path"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Strategic implications and adoption path</h2> <p>Realizing the competitive advantages offered by autonomous infrastructures will depend on how quickly and safely it is adopted. Benefits depend on safe, guided adoption. Poor implementation raises risks; good governance increases rewards.</p> <p>Carefully consider and allocate resources for the following economic and investment realities while simultaneously recognizing benefits:</p> <ul class="default-list"> <li><b>Upfront costs</b>. Platforms, integration and training.</li> <li><b>ROI drivers. </b>Reduced downtime, labor efficiency and optimized infrastructure spend.</li> <li><b>Trade-offs.</b> Prioritize build versus buy decisions for autonomous systems, as well as flexibility versus vendor dependence decisions.</li> </ul> <h3>Adoption roadmap</h3> <p>Begin with low-risk, high-value domains such as observability, incident triage or cost optimization, where outcomes are measurable and reversible. Establish clean data pipelines and a unified telemetry platform.</p> <p>Progress through the following three maturity stages:</p> <ol class="default-list"> <li><b>Assisted automation.</b> Human-led, AI-supported.</li> <li><b>Semi-autonomous.</b> Policy-bound execution with oversight.</li> <li><b>Autonomous domains.</b> Fully self-managing within guardrails.</li> </ol> <p>Companies should establish governance and policy controls early. Also, use pilot programs to build trust, validate ROI and refine escalation models before attempting a broader rollout.</p> <p><i>Damon Garn owns Cogspinner Coaction and provides freelance IT writing and editing services. He has written multiple CompTIA study guides, including the Linux+, Cloud Essentials+ and Server+ guides, and contributes extensively to TechTarget Editorial, The New Stack and CompTIA Blogs.</i></p> </section> Autonomous infrastructure is not just implementing new technology; it completely redefines IT's role. Success depends on balancing speed, safety and accountability. https://cdn.ttgtmedia.com/rms/onlineimages/disaster_recovery_g175031469.jpg https://www.techtarget.com/it-infrastructure/tip/How-autonomous-infrastructure-alters-IT-operations Mon, 17 Aug 2026 10:40:00 GMT <p>In recent years, the AI boom has completely changed data center economics. While organizations naturally gravitate toward managing <a href="https://www.techtarget.com/searchdatacenter/tip/How-much-energy-do-data-centers-consume">energy consumption</a> costs tied to compute, storage can also be a significant contributor to workload TCO. Organizations that treat energy efficiency as a primary goal when designing their storage architecture may be able to lower operating costs, increase rack densities and more easily satisfy the organization's sustainability objectives. In some cases, aggressively managing storage power consumption now might even put off expensive facility upgrades for a time.</p> <section class="section main-article-chapter" data-menu-title="How AI workloads are driving data center power concerns"> <h2 class="section-title"><i class="icon" data-icon="1"></i>How AI workloads are driving data center power concerns</h2> <p>Historically, one of the biggest challenges for data center operators has been accommodating all of an organization's IT resources without running out of floor space. After all, nobody wants to shoulder the cost of a data center expansion or the construction of a new facility. Today, however, the availability of sufficient <a href="https://www.techtarget.com/data-technologies/feature/Power-constrained-data-architecture-curbing-AI-ambitions">electricity is becoming a bigger operational constraint</a> than floor space.</p> <p>AI servers consume far more power than the servers used to host traditional workloads. According to <a href="https://www.socomec.us/en-us/solutions/business/data-centers/understanding-power-consumption-data-centers">some estimates</a>, "Traditional data centers operate at 5-10 kW per rack, while AI-optimized facilities now require 60+ kW per rack within the same square foot footprint." Most of the datacenters built before the AI boom were never designed to accommodate such demand, and utility expansions can take years to complete.</p> <p>Simply put, power has gone from being an operating expense to becoming a business constraint. Hence, organizations must take immediate steps to ensure that they are using the available power efficiently. Every watt of power that is being consumed by storage resources is a watt that cannot be allocated to the AI infrastructure.</p> </section> <section class="section main-article-chapter" data-menu-title="What Does Storage Actually Contribute to Your data center Power Bill?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>What Does Storage Actually Contribute to Your data center Power Bill?</h2> <p>Like any piece of data center hardware, storage arrays consume power. Even a relatively small storage appliance can easily consume over 100 watts. Of course, larger arrays consume more power. According to <a href="https://www.solved.scality.com/data-center-power-efficiency/">Solved Magazine</a>, a 2U SAN might contain 20 to 40 drives and consume 2 to 5 KW of power. As an example, the Dell PowerMax 8500's power consumption varies based on its configuration. However, the smallest number <a href="(https:/www.delltechnologies.com/asset/en-us/products/storage/technical-support/powermax-2500-8500-spec-sheet.pdf">given by Dell</a> is 7.124 kVA (approximately 5.6 KW).</p> <p>If these numbers sound high, it's worth remembering that in an enterprise-class environment, storage hardware does far more than just hosting drives. Functions such as erasure coding and encryption consume significant compute resources, which in turn increase power consumption.</p> <p>It's also worth considering that the storage hardware itself is only half of the story. As the storage hardware consumes power, it releases heat as a byproduct. This thermal load forces cooling systems to work harder, further increasing power consumption. In other words, every watt consumed becomes heat that has to be removed.</p> </section> <section class="section main-article-chapter" data-menu-title="Intelligent Tiering as an Energy Strategy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Intelligent Tiering as an Energy Strategy</h2> <p>AI workloads generally require access to vast inference, analytics or training datasets amounting to many terabytes (TB) or even petabytes, so the need for storage hardware certainly isn't going away. Even so, it may be possible to drive down costs through <a href="https://www.techtarget.com/it-infrastructure/tip/Why-storage-tiering-is-necessary-now-more-than-ever">intelligent storage tiering</a>.</p> <p>Storage tiering was introduced at a time when flash storage offered extremely limited capacity with a very high cost per gigabyte. The idea was that not all data requires the same level of performance. Hence, frequently accessed "hot" data could be placed on high-performance SSDs, while occasionally used "warm" data could reside on less expensive, higher-capacity spinning media. Rarely accessed "cold" data could be moved to cheap archival disks or even kept offline.</p> <p>As flash storage prices began to decline, many organizations moved their performance-sensitive workloads to all-flash arrays, with traditional HDD/SSD tiering being used less frequently for primary workloads. However, intelligent tiering is beginning to see a resurgence thanks to the need for reducing power consumption in the data center.</p> <p>Simply put, higher-performance storage tends to use more power, and because it is consuming more power, it also produces more heat. This is not necessarily to say that an SSD uses more power than a spinning disk. In some cases, an SSD might actually use a bit less power than spinning media.</p> <p>What needs to be considered, however, are metrics such as watts per IOPS, watts per transaction, watts per TB, or watts per workload. An all-flash array might have no trouble accommodating cooler data. Still, if power efficiency is a priority, then that data might be better suited to higher-capacity HDD-based storage or archival tiers -- some of which can reduce power consumption by spinning down inactive drives.</p> <p>This means that rather than placing an entire data set on high-performance storage, it may be more efficient to reserve the flash media for the data that is being actively used. Typically, only a fraction of the overall data is in use at any given moment, meaning that cooler data can be stored on slower but more energy-efficient tiers. And if some of the less frequently used data suddenly becomes important, it can be automatically moved to the high-performance tier, where it will remain until it "cools off."</p> <p>Storage tiering can also sometimes reduce hardware acquisition costs by ensuring only frequently used data occupies expensive high-performance storage. It can also reduce power costs by keeping infrequently used data on lower-power, lower-cost storage that requires less energy and cooling. This, in turn, ensures that less energy is being consumed by storage, thereby making that excess energy available for use with AI workloads.</p> </section> <section class="section main-article-chapter" data-menu-title="Balancing ESG Goals with Storage Needs"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Balancing ESG Goals with Storage Needs</h2> <p>Organizations that design their storage architecture for operational efficiency might discover that their efforts naturally support ESG reporting, as reduced power consumption is objectively measurable and easy to document. In the case of an AI data center, however, the business justification for reducing power consumption might have less to do with meeting ESG goals and more to do with preventing a limited supply of power (or a limited power and cooling budget) from becoming an operational constraint.</p> <p>In the AI era, those responsible for storage must look beyond performance and capacity planning. Today, storage decisions play a pivotal role in reducing an organization's <a href="https://www.techtarget.com/searchdatacenter/definition/TCO">TCO</a> while also ensuring that limited data center power supplies can be used where they will deliver the greatest business value.</p> <p><i>Brien Posey is a former 22-time Microsoft MVP and a commercial astronaut candidate. In his more than 30 years in IT, he has served as a lead network engineer for the U.S. Department of Defense and a network administrator for some of the largest insurance companies in America.</i></p> </section> AI has turned power into a bottleneck, making energy-efficient storage design and intelligent tiering central to cutting down on watts and freeing capacity for AI. https://cdn.ttgtmedia.com/rms/onlineimages/disaster_recovery_a257795847.jpg https://www.techtarget.com/it-infrastructure/tip/Energy-Efficient-Storage-Architecture-in-the-AI-Era Mon, 17 Aug 2026 10:39:00 GMT <p>The Natural History Museum’s (NHM’s) “living laboratory” garden has collected more than 11 million <a href="https://www.computerweekly.com/resources/Infrastructure-as-a-Service-IaaS">environmental data records</a> in its first year, feeding readings from more than 50 sensors into the Museum’s Amazon Web Services (AWS)-powered Data Ecosystem.</p> <p>The sensors in the Nature Discovery Garden continuously capture temperature and humidity to track microclimate variation, underwater acoustic recordings from the pond, birdsong and ambient urban noise such as traffic.</p> <p>During June’s heatwave, soil sensors in the garden’s woodland areas recorded temperatures 10°C cooler than the paved areas of the Darwin Centre Courtyard, giving researchers evidence for how trees, shade, soil moisture and permeable surfaces can help cities adapt to rising temperatures.</p> <p>The readings feed a Data Ecosystem built on AWS cloud technologies, which collects, processes and shares millions of observations from sensors, imagery and other scientific sources. In practice, that means an <a href="https://www.computerweekly.com/feature/Natural-History-Museum-deploys-sensor-network-to-decode-urban-biodiversity-with-AWS">internet of things (IoT) data pipeline</a> in which devices publish telemetry to a message broker such as AWS IoT Core, streamed through a service such as Kinesis into an <a href="https://www.computerweekly.com/feature/Storage-technology-explained-What-is-S3-and-what-is-it-good-for">S3</a>-based <a href="https://www.computerweekly.com/feature/Cloud-data-lakes-Where-do-they-fit-and-what-are-their-benefits">data lake</a>, then processed, catalogued and analysed with tools such as Athena and SageMaker – including machine learning models that classify birdsong and other acoustic recordings.</p> <p>Ed Baker (pictured), acoustic biology researcher at the Natural History Museum, said: “We call the Museum gardens a living laboratory, and the sensor network and AWS Data Ecosystem have made this a reality. By collecting millions of data points, from temperature and humidity to birdsong and underwater sound, we can build a far richer picture of how urban nature responds to various pressures and becomes more resilient to future environmental challenges.”</p> <p>The museum is now expanding the network into its Evolution Garden, an area with higher visitor footfall and a contrasting planting style, to study how visitor activity and habitat design influence biodiversity.</p> <p>Long-term monitoring since 1995 has recorded more than 3,500 species in the gardens, with a further 90 identified since they reopened in 2024, including the emperor moth and the small red-eyed damselfly.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about cloud and sustainability</h3> <ul class="default-list"> <li><a href="https://www.computerweekly.com/feature/Natural-History-Museum-deploys-sensor-network-to-decode-urban-biodiversity-with-AWS">Natural History Museum deploys sensor network to decode urban biodiversity with AWS</a>: We look at how the Museum’s sensor network and AWS Data Ecosystem turn a London garden into a living laboratory for urban biodiversity research.</li> <li><a href="https://www.computerweekly.com/news/366644373/Data-dive-Dodgy-data-derails-datacentre-water-debate">Data dive: Dodgy data derails datacentre water debate</a>: We investigate how poor-quality data undermines claims about datacentre water consumption.</li> </ul> </div> </div> <p>The project is part of a wider pattern of deployments of environmental sensor networks allied to cloud data platforms. <a href="https://www.technologyreview.com/2022/08/19/1057848/array-of-things-goes-global/">In Chicago, the Array of Things</a> deployed hundreds of urban sensing nodes publishing open data through a cloud portal; in Germany, the <a href="https://www.nature4.org/">Ammod automated multisensor stations and the Nature 4.0 project</a> combine networked sensors with machine learning for biodiversity monitoring. The NHM reports that its Data Ecosystem has scaled to accommodate a 200% increase in use since the network was switched on.&nbsp;</p> <p>Hilary Tam, sustainability leader for EMEA at AWS, said: “The Natural History Museum is showing what’s possible when science and cloud technology come together. As the sensor network grows, the AWS-powered Data Ecosystem is able to scale to enable researchers to connect millions of environmental observations, revealing patterns that would otherwise remain invisible.”</p> <p>For enterprise IT leaders, the project is a reminder that the sensor-to-data-lake-to-machine-learning architecture is now cheap and standard enough to run in a museum garden, and so increasingly available for smart-city and infrastructure monitoring. But the hard part is not collection – it’s curation.</p> <p>As Computer Weekly has reported, <a href="https://www.computerweekly.com/news/366644373/Data-dive-Dodgy-data-derails-datacentre-water-debate">poor-quality data can derail environmental analysis</a>, and the same rigour around sustainable IT and its environmental footprint applies to any organisation turning sensor telemetry into decisions.</p> More than 50 sensors feed temperature, humidity and acoustic readings into the Museum’s AWS Data Ecosystem, which found woodland soils stayed 10°C cooler in June’s heatwave https://cdn.ttgtmedia.com/rms/computerweekly/Ed-Baker-Acoustic-Biology-Researcher-NHM.jpg https://www.computerweekly.com/news/366648981/Natural-History-Museums-living-laboratory-logs-11-million-environmental-records-in-first-year Mon, 17 Aug 2026 10:30:00 GMT <p>Four health systems are getting closer to real-time prior authorizations with a new feature from Epic.</p> <p>Announced ahead of the Epic Systems Users Group Meeting, the health IT giant said Ochsner Health, Froedtert ThedaCare, Denver Health and Summit Health are now using an <a href="https://www.techtarget.com/it-infrastructure/definition/What-is-an-API-application-programming-interface">application programming interface</a> to check prior authorization requirements automatically for major insurers, including UnitedHealthcare, Aetna and Network Health.</p> <p>Epic dubbed the new API the Coverage Requirements Discovery, or CRD, which aggregates prior authorization requirements within the EHR system at the time a clinician places an order or a staff member schedules an appointment.</p> <p>The company said the API will eliminate the need for manual work, such as phone calls, faxes and re-entering information into separate insurance portals -- all of which have been major pain points in the prior authorization process for providers.</p> <p>"At Ochsner Health, we're excited to implement the Prior Authorization API, which transforms a traditionally manual, time-consuming process into a streamlined experience for our care teams," Melissa Woods, Ochsner Health’s assistant vice president of revenue cycle and financial clearance, said in a <a href="https://www.epic.com/epic/post/payers-providers-and-epic-launch-real-time-prior-authorization-checks/">statement</a> earlier today.</p> <p>The API will cut administrative burden and increase efficiency while mitigating delays in patient care, Woods added.</p> <p>The CRD API also meets a requirement in a <a href="https://www.techtarget.com/healthcarepayers/feature/Whats-ahead-for-prior-authorizations-as-new-requirements-loom">new federal interoperability rule</a> mandating the use of APIs for the prior authorization process, Epic said.</p> <p>Most Medicare Advantage, Medicaid and Affordable Care Act Marketplace insurers will need to use standardized APIs from <a href="https://www.techtarget.com/searchhealthit/definition/Health-Level-7-International-HL7">Health Level Seven International</a>, which leverage the <a href="https://www.techtarget.com/searchhealthit/definition/FHIR-Fast-Healthcare-Interoperability-Resources">Fast Healthcare Interoperability Resources</a> technical standard. The impacted payers must implement the APIs by January 1, 2027.</p> <p>Currently, the APIs, which function as digital pipelines for electronic data exchange between parties, are in a testing and implementation phase. The Centers for Medicare and Medicaid Services is actively working with 29 early adopters of the APIs, including leading EHR companies such as Epic, Oracle Health and athenahealth. Froedtert ThedaCare and <a href="https://www.techtarget.com/revcyclemanagement/feature/Prior-authorization-automation-hinges-on-human-connection">Ochsner Health</a> are also part of the first group to pilot the APIs.</p> <p>The four health systems are now live with the prior authorization API from Epic five months ahead of the regulatory deadline, Epic stated. Sixteen more payers are also currently testing it, according to the announcement.</p> <p>These partnerships make real-time prior authorizations possible, suggested Imran Andrabi, president and CEO of Froedtert ThedaCare. The API allows patients and clinicians to focus on needed care, he continued.</p> <p>Collaboration through the CMS' early adopter demonstration of the required APIs has been critical to enabling faster, more efficient prior authorizations, according to Amy Trainor,&nbsp; system vice president and chief information officer at Ochsner Health.</p> <p>Trainor said in a previous interview with <i>RevCycle Management</i> that the demonstration supports real-time communication with other stakeholders in the prior authorization process in a single channel. This has addressed one of the major obstacles of innovation for this process: finding the right person to speak to on the other end.</p> <p>"I feel like this is why it's working so much better than it had in the past. It's not that my team or the payer team didn't know how to create a FHIR API connection; it's that they didn't know who to talk to," she said.</p> <p>The prior authorization process has been notoriously burdensome for payers and providers, prompting the CMS to home in on improvements through regulation. About 50 health insurers also <a href="https://www.techtarget.com/healthcarepayers/news/366626091/Major-health-plans-pledge-to-simplify-prior-authorizations">took a pledge in partnership with the federal government to fix prior authorization requirements</a> through 2027.</p> <p>However, providers remain skeptical about the progress payers have touted with their pledge, saying they have <a href="https://www.techtarget.com/revcyclemanagement/feature/What-providers-really-need-to-streamline-prior-authorizations">yet to feel the on-the-ground effects of the efforts</a>, including reducing the number of services subject to the requirements and enhancing communications around determinations.</p> <p>The upcoming CMS requirements provide the accountability needed to make real progress with prior authorizations, they say.</p> <p><i>Jacqueline LaPointe is an Executive Editor at Xtelligent Healthcare Media, covering revenue cycle management, healthcare payers, health policy and health IT since 2016.</i></p> Epic announced a new prior authorization API that four health systems are currently using to give clinicians and staff real-time access to requirements at the time of scheduling. https://cdn.ttgtmedia.com/rms/onlineimages/virtual%20health_g1274403122.jpg https://www.techtarget.com/revcyclemanagement/news/366649207/Health-systems-test-real-time-prior-auths-through-Epic Mon, 17 Aug 2026 10:29:00 GMT <p>Supplier segmentation is only useful if it changes decisions.</p> <p>A supplier category should not be just a label in a procurement system or spreadsheet. It should tell the business how much attention a supplier needs, who owns the relationship, how often the relationship should be reviewed and what risks require escalation.</p> <p>That matters because companies do not have unlimited bandwidth for supplier management. Some suppliers are strategic because they support critical operations, are difficult to replace or help create business value. Others are preferred, transactional or basic suppliers that might require oversight but not the same level of executive attention or collaboration.</p> <p>The purpose of segmentation is to make those differences visible before the business must act under pressure. Companies need to know which suppliers require deeper planning, which require regular risk review and which can be managed through standard purchasing controls.</p> <p>That visibility depends on supplier relationship data, because <a href="https://www.techtarget.com/enterprise-software/feature/Supplier-resilience-depends-on-relationship-data">supplier resilience depends on relationship data</a>, not just scorecards and KPIs.</p> <p>Segmentation is where that relationship data becomes operational. It must guide how the company assigns resources, sets review cycles and decides which supplier relationships require executive attention.</p> <section class="section main-article-chapter" data-menu-title="Supplier segmentation is a governance issue"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Supplier segmentation is a governance issue</h2> <p>Supplier segmentation is <a href="https://www.techtarget.com/searcherp/feature/Supplier-segmentation-lessons">more than a numerical exercise</a> or an operational spreadsheet. It is a strategic governance issue owned by procurement and supply chain leadership.</p> <p>In this context, governance means the company has a clear model for deciding how suppliers are categorized, who owns those decisions, how often those categories are reviewed, what actions follow from each category and who is accountable when supplier risk changes.</p> <p>That matters because supplier segmentation should change behavior. A strategic supplier should not receive the same attention as a basic supplier, nor should a difficult-to-replace supplier be managed the same way as a supplier that provides a routine product or service. A supplier that carries high operational risk should not be treated the same way as one with little effect on continuity.</p> <p>The point is not to make every supplier strategic. That would only spread attention too thin. The point is to know which relationships deserve scarce management bandwidth before disruption forces the company to make rushed decisions.</p> <p>Supplier relationship bandwidth is finite. The relationships that receive the most effort should be the ones that matter most to the business daily, and especially in a crisis.</p> </section> <section class="section main-article-chapter" data-menu-title="Technology can centralize supplier signals"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Technology can centralize supplier signals</h2> <p>Technology can help collect and organize the information needed to make those distinctions.</p> <p>ERP systems can show purchasing history, invoices, payments, material dependencies and business impact. Supply chain management (<a href="https://www.techtarget.com/searcherp/definition/supply-chain-management-SCM">SCM</a>) systems can help surface inventory, capacity, logistics, lead time and continuity risks. Procurement and supplier relationship management systems can track contracts, supplier status, sourcing decisions, compliance requirements, communication history and performance reviews. Analytics tools can identify patterns, trends and emerging risk signals.</p> <p>That technology connection is important because <a href="https://www.techtarget.com/searcherp/feature/What-role-do-ERP-systems-play-in-supply-chain-management">ERP systems in supply chain management</a> often hold operational and financial data that shape supplier decisions. Purchase orders, inventory levels, production requirements, invoices, payment history and demand signals can all affect how a company understands supplier importance.</p> <p>But supplier data rarely lives in one place. <a href="https://www.techtarget.com/searcherp/definition/supply-chain-visibility-SCV">Supply chain visibility</a> often depends on connecting information from ERP, SCM, warehouse management, transportation management and other systems. The more fragmented those signals are, the harder it is for procurement and supply chain leaders to know which supplier relationship requires attention.</p> <p><a href="https://www.techtarget.com/searcherp/definition/supply-chain-analytics">Supply chain analytics</a> can help by identifying patterns and trends that are difficult to see manually. For example, analytics might show changes in lead times, recurring quality issues, shifts in delivery reliability or early signs of capacity risk. But those signals only matter if the organization has a process for deciding what they mean.</p> <p>That is where <a href="https://www.techtarget.com/searcherp/feature/How-ERP-and-supply-chain-platforms-protect-profits">ERP and supply chain platforms</a> can support resilience. They can help companies connect supplier exposure to inventory, production, customer commitments and financial impact. They can also give decision-makers a more complete view of how supplier risk affects the business.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/supplier_relationship_management_system-f.png"> <img data-src="https://www.techtarget.com/rms/onlineimages/supplier_relationship_management_system-f_mobile.png" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/supplier_relationship_management_system-f_mobile.png 960w,https://www.techtarget.com/rms/onlineimages/supplier_relationship_management_system-f.png 1280w" alt="Diagram showing how supplier relationship management relates to customer relationship management, warehouse management, transportation management and supply chain management systems." height="336" width="560"> <figcaption> <i class="icon pictures" data-icon="z"></i>Supplier relationship management depends on information from multiple enterprise systems, including supply chain, warehouse, transportation and CRM systems. </figcaption> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Governance determines whether the data changes action"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Governance determines whether the data changes action</h2> <p>Technology does not make the decision by itself. Governance determines whether the data changes the action.</p> <p>A dashboard can show that a strategic supplier has rising lead times. An analytics tool can flag a trend. An ERP or SCM system can show where the supplier supports critical operations. But none of that improves resilience unless someone is accountable for deciding what happens next.</p> <p>That might mean escalating the supplier relationship to executive leadership. It might mean increasing communication with the supplier. It might mean changing inventory plans, finding alternate capacity, reviewing contract terms or asking internal teams to align around a shared response.</p> <p>Supplier segmentation should therefore be tied to action. If a supplier is strategic, the company should know who owns the relationship, how often it is reviewed, and which risk signals require escalation. If a supplier is preferred, the company should know what level of monitoring and collaboration is appropriate. If a supplier is transactional or basic, the company should know what standard controls are enough.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Governance determines whether the data changes action. </figure> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Segmentation should also connect to broader <a href="https://www.techtarget.com/searcherp/feature/7-techniques-to-build-supply-chain-resilience">supply chain resilience strategies</a>. Companies need backup options, inventory planning, visibility, risk monitoring and supplier communication.</p> <p>Segmentation helps decide where those efforts deserve the most attention.</p> </section> <section class="section main-article-chapter" data-menu-title="Supplier resilience needs relationship ownership"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Supplier resilience needs relationship ownership</h2> <p>Supplier segmentation is not only a sourcing problem. It is an ownership problem.</p> <p>A company can identify strategic suppliers, build scorecards, collect risk signals and centralize supplier information, but still fail to improve resilience if no one is accountable for using that information. Supplier relationship data needs owners, review cycles and decisions tied to it.</p> <p>That means each important supplier relationship needs clear accountability. The company should know who owns the relationship, who reviews the supplier's category, who monitors changes in risk and performance and who decides when a supplier issue requires escalation.</p> <p>Ownership also must extend beyond procurement. Finance, operations, legal, compliance and business units all affect how a supplier experiences the relationship. If those teams send different signals, delay decisions or treat a strategic supplier like an ordinary vendor, the supplier category will not match the company's behavior.</p> <p>Those responsibilities make supplier relationship data operational. Without them, the data can sit in a system without changing behavior.</p> <p><a href="https://www.techtarget.com/searcherp/feature/Supplier-relationship-management-benefits">Strong supplier relationship management benefits</a> do not come from collecting more information for its own sake. They come from using that information to make supplier relationships clearer, more consistent and more resilient. Better data can improve visibility. Better relationships can improve communication. Better ownership can make sure both are used before disruption becomes a crisis.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading"></h3> <h3 class="splash-heading">Supplier relationship data checklist</h3> <p>Supplier relationship data should help companies answer the following questions:</p> <ul class="default-list"> <li>Is the supplier strategic, preferred, transactional or basic?</li> <li>How difficult would the supplier be to replace?</li> <li>What business process, product or customer commitment depends on the supplier?</li> <li>What risks are tied to the supplier?</li> <li>How well does the supplier communicate before problems escalate?</li> <li>Does the supplier view the company as a priority customer?</li> <li>Who owns the relationship internally?</li> <li>Are procurement, finance, operations and business units aligned?</li> <li>What supplier feedback has the company collected?</li> <li>What action should happen if the supplier's risk or importance changes?</li> </ul> </div> </div> </section> <section class="section main-article-chapter" data-menu-title="Supplier categories should not be static"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Supplier categories should not be static</h2> <p>Supplier segmentation should not be a one-time exercise. A supplier's importance can change as the business changes, as risk changes or as the supplier relationship itself changes.</p> <p>A supplier that once seemed transactional could become more important if demand shifts, if alternate suppliers leave the market or if a product line becomes more dependent on that supplier's capabilities. A strategic supplier might become less central if the company changes its product strategy, modifies its manufacturing footprint or adds new sourcing options.</p> <p>That is why supplier categories need review cycles. Procurement and supply chain leaders should revisit supplier classifications regularly and when major changes occur. Those reviews should include performance data, relationship data, risk signals, business impact and supplier feedback.</p> <p>The goal is not to predict every disruption. It is to make sure supplier categories still reflect how the business actually depends on each supplier. If the category no longer matches the risk, value or operational importance of the relationship, the company might be making supplier decisions from outdated information.</p> <p>That is the real test of supplier segmentation. It should affect who owns the relationship, how often the supplier is reviewed, what risk signals require escalation and what action the business takes when conditions change.</p> <p>Supplier segmentation works only when it changes decisions. Otherwise, it is just a label.</p> <p><em>James Alan Miller is a veteran technology editor and writer who leads Informa TechTarget's Enterprise Software group. He oversees coverage of ERP &amp; Supply Chain, HR Software, Customer Experience, Communications &amp; Collaboration and End-User Computing topics.</em></p> </section> Supplier segmentation helps teams turn supplier relationship data into decisions about ownership, review cycles, risk signals and escalation. https://cdn.ttgtmedia.com/rms/onlineimages/collab_a240557247.jpg https://www.techtarget.com/enterprise-software/feature/Supplier-segmentation-is-only-useful-if-it-changes-decisions Mon, 17 Aug 2026 09:52:00 GMT <p>As AI seeps into the bedrock of enterprise operations, it becomes more akin to critical infrastructure than a mere add-on tool. And when AI is part of core operations, the question of who controls these enterprise systems becomes more critical than ever.</p> <p><a target="_blank" href="https://hai.stanford.edu/ai-index/2026-ai-index-report" rel="noopener">According</a> to "The 2026 AI Index Report" from Stanford HAI, organizational AI adoption reached 88% in 2026. Yet increasing adoption rates don't mean the average business owns its entire AI stack, and vendors and governments are increasingly shaping access to AI products. Moreover, businesses that operate globally must comply with the <a href="https://www.techtarget.com/ai/tip/Global-AI-legislation-and-regulation-tracker">regulations of multiple government entities</a>.</p> <p>Having <i>sovereign </i>AI in business means an organization can develop, deploy and govern AI independently of external infrastructure, hardware and models. Local implementation and oversight ensure the utmost control over governance and compliance, and greater assurance that systems will continue to work despite political or vendor disruptions.</p> <p>Defining sovereignty is inherently complex. Enterprises must take into consideration a web of regulations, physical architectures, cross-border data flows and operational choices -- all within a fragmented global landscape and competing definitions. Writers in Stanford HAI's essay "AI Sovereignty's Definitional Dilemma" <a target="_blank" href="https://hai.stanford.edu/news/ai-sovereigntys-definitional-dilemma" rel="noopener">explained</a> the conundrum as follows:</p> <p>"The fact that sovereignty is used to describe both states' struggles over geopolitical autonomy and regulatory oversight and companies' efforts to secure organizational governance further complicates attempts to define AI sovereignty," the essay said.</p> <p>Recently, boardrooms have taken AI sovereignty into their own hands. But complete sovereignty is challenging, especially for multinational businesses that rely on third-party technologies. So, many businesses are choosing <i>selective </i>AI sovereignty: opting in to sovereign implementation where it matters most to them, thereby safeguarding investments from compliance issues, vendor lock-in and unpredictable government interventions without forfeiting innovation.</p> <p>"We're going from experimentation projects to real projects," said Eric Helmer, senior vice president and CTO of Rimini Street, a global third-party enterprise software company. "Now is the time to take a step back and build what is needed for an AI sovereignty model."</p> <section class="section main-article-chapter" data-menu-title="Fragmented regulations push enterprises toward sovereign AI"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Fragmented regulations push enterprises toward sovereign AI</h2> <p>Disparate regulations and increasingly stringent compliance requirements have brought the question of sovereign AI to the forefront. In Europe in particular, the <a href="https://www.techtarget.com/ai/opinion/Everything-you-need-to-know-about-the-new-EU-AI-Act">EU AI Act</a> and its comprehensive regulations, which have <a href="https://www.techtarget.com/searchenterpriseai/news/366646620/EU-AI-Act-compliance-deadline-is-here-What-to-watch">recently begun to take effect</a>, are prompting many global enterprises to prioritize sovereign AI.</p> <p>There's substantial momentum on sovereign AI in Europe right now because of the AI Act, said Mark Beccue, principal analyst at Omdia, a division of Informa TechTarget. Compliance with those regulations is a huge driver of sovereign AI discussions for businesses.</p> <p>For example, Omdia's 2026 report, "The Great Repatriation: Why Enterprises Must Act Now to Ensure AI Sovereignty," found that 51% of respondents said compliance with EU AI Act regulations was very important in accelerating their sovereign AI investment decisions. Additionally, 47% said compliance with extra or additional regulations from national jurisdictions within the EU was very important.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> [Operating in multiple countries] really complicates things for these companies. </figure> <figcaption> <strong>Mark Beccue</strong>Principal analyst, Omdia </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Compared with growing AI compliance requirements in Europe, AI regulations in the U.S. are murky at best. The Trump administration's first slew of executive orders aimed primarily at reducing stringent rules on AI development and use -- such as the government's <a href="https://www.techtarget.com/ai/feature/Who-wins-and-loses-with-Trumps-AI-executive-order">late 2025 EO, which limited states' abilities</a> to set their own AI regulations. More recently, a <a href="https://www.techtarget.com/ai/news/366644013/Trump-AI-order-targets-frontier-model-prerelease-review">June 2026 executive order</a> established a framework for voluntary pre-release access evaluations for frontier models.</p> <p>But with no set federal regulations yet, the U.S. approach to AI might be more fragmented than other global frameworks. To complicate matters, many companies don't operate in only one jurisdiction. Multinational companies often have offices, servers, data or infrastructure in jurisdictions with different AI regulatory requirements, making total compliance a major headache.</p> <p>"[Operating in multiple countries] really complicates things for these companies," Beccue said. "The biggest worry they have is they don't want this to slow down their AI momentum, so they're looking at ways to meet the compliance needs of these various jurisdictions and not let it slow them down."</p> <p>While the unique risks of AI bring added complexity, meeting the compliance needs of various governing bodies isn't entirely new for many enterprises. For example, in the world of ERP, handling data for a global company has historically been complicated, Helmer said. Some laws require certain data to remain within a country, and businesses must also contend with industry-specific compliance requirements.</p> <p>"We're used to those regulations," Helmer said. "It complicates things even more when you bring in the world of automated agents."</p> </section> <section class="section main-article-chapter" data-menu-title="Political and vendor disputes complicate the conversation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Political and vendor disputes complicate the conversation</h2> <p>In the last few months, the Trump administration's interactions with major AI vendors have sparked debate over government involvement in the AI market. The added tension has also driven sovereign AI discussions in the boardroom, aimed at mitigating the risk of product blockage due to government intervention or vendor disputes.</p> <p>Anthropic's June <a href="https://www.techtarget.com/ai/news/366642478/Claude-Mythos-Preview-and-the-new-rules-of-cybersecurity">release of Claude Mythos</a> and Fable 5 was live for only three days before a U.S. government <a target="_blank" href="https://www.cnbc.com/2026/06/12/anthropic-disables-access-to-fable-5-and-mythos-5-to-comply-with-government-directive.html" rel="noopener">export control directive</a> forced the AI vendor to restrict access to foreign nationals both inside and outside of the U.S. The government<b> </b>cited concerns about national security, but the ripple effect raised other questions: What happens when a government embargoes access to a widely used model?</p> <p>"We're certainly having conversations around sovereign implementation, especially with certain regions [and] some of the different confrontations and conflicts going on around the world," said Jill Knesek, CISO at BlackLine, a financial operations and accounting automation platform.</p> <p>As part of its <a href="https://www.techtarget.com/ai/news/366641233/The-ethical-implications-of-Anthropics-feud-with-the-Pentagon">ongoing feud with Anthropic</a>, the Trump administration pivoted to OpenAI models for federal use cases and requested that the AI vendor limit the release of GPT-5.6 to "trusted partners," according to a CNBC <a target="_blank" href="https://www.cnbc.com/2026/06/26/openai-limits-new-ai-models-to-trusted-partners-request-us-government.html" rel="noopener">report</a>. The model access issues here are twofold: Government contractors, some of which built ecosystems around Claude, had to <a target="_blank" href="https://www.reuters.com/business/us-treasury-ending-all-use-anthropic-products-says-bessent-2026-03-02/" rel="noopener">switch to OpenAI models</a>. Enterprise users also had to reckon with the possibility that their access to third-party models could be limited or revoked entirely in the future.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> We have to be aware of [government interventions]. We have to be able to understand how we can shift and maintain our capabilities if [blockages] occur. </figure> <figcaption> <strong>Jill Knesek</strong>CISO, BlackLine </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>The Trump administration has also recently contemplated restricting access to Chinese AI models and hardware, citing national security concerns. <a target="_blank" href="https://www.axios.com/2026/07/20/ai-us-china-open-source-kimi" rel="noopener">For example</a>, Moonshot AI's Kimi K3 sent the U.S. government and Silicon Valley into a tailspin, with the White House and lobbying AI vendors, such as OpenAI, quickly suggesting future bans on foreign products. The government is also <a target="_blank" href="https://www.reuters.com/world/trump-administration-drafting-ban-chinese-data-center-devices-sources-say-2026-08-04/" rel="noopener">considering</a> import restrictions on Chinese data center devices.</p> <p>"Different countries are setting up different rules, and everyone is worried about national security," said Darrell West, a senior fellow at the Brookings Institution's Center for Technology Innovation. "The question of what countries you buy models from is important." For example, not only do businesses need to evaluate the <a href="https://www.techtarget.com/ai/feature/Kimi-K3-Chinese-open-weight-models-challenge-AI-status-quo">pros and cons of Chinese open-weight models</a>, but they also need to consider possible government interventions, he added.</p> <p>Interventions in the AI market highlight an enterprise blind spot and a new dimension to <a href="https://www.techtarget.com/ai/tip/7-best-practices-to-avoid-AI-vendor-lock-in">vendor lock-in</a>. When government disputes cause service disruptions, businesses that rely entirely on a single vendor's models expose themselves to risk.</p> <p>"We have to be aware of [government interventions]," Knesek said. "We have to be able to understand how we can shift and maintain our capabilities if [blockages] occur. Depending on what country we're doing business in, or our customers are doing business in, we also have to think about other nations and how they're going to react and respond."</p> <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/mQ7Dq9qEZH8?autoplay=0&amp;modestbranding=1&amp;rel=0&amp;widget_referrer=null&amp;enablejsapi=1&amp;origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0"></iframe> </div> </section> <section class="section main-article-chapter" data-menu-title="Enterprise considerations for the sovereign AI stack"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Enterprise considerations for the sovereign AI stack</h2> <p>It's nearly impossible to be completely sovereign, especially for AI. To find a middle ground between completely open strategies and 100% local implementation, many businesses are turning to <i>selective </i>or <i>hybrid </i>AI sovereignty, in which certain aspects of their AI strategy are sovereign, while other aspects use cross-border components out of necessity.</p> <p>"When you talk about AI sovereignty, there are a lot of parts and pieces," Knesek said. "Some of them are almost impossible to get for an enterprise. We're talking about [AI sovereignty], but more in a hybrid sense, not 'all in,' because that would be very complex. We are still going to be reliant on some third-party capabilities."</p> <p>To achieve this hybrid autonomy, businesses focus on several distinct layers. Which to prioritize comes down to selectivity, with each business taking stock of its risk profiles and AI needs. To get started, businesses can focus on four areas: data control, model portability, <a href="https://www.techtarget.com/ai/tip/LLM-build-vs-buy-A-decision-framework-for-LLM-adoption">build-versus-buy frameworks</a> and compliance management.</p> <h3>Data control</h3> <p>Data sovereignty encompasses not only where data lives but also who has authority over it, including which laws apply and who has control. <a href="https://www.techtarget.com/searchenterpriseai/tip/How-to-navigate-data-sovereignty-for-AI-compliance">Data sovereignty for AI</a> is crucial because AI uses massive amounts of data for training and inference, sometimes touching multiple data repositories, servers and systems to answer a query or complete an autonomous action.</p> <p>Sovereign AI is all about data control, said Peter Liebert, CISO of Clari/Salesloft, an AI-driven revenue orchestration company. "Are you able to control the data flow, who accesses it, whether it's a model accessing it [and] what level of permissions that model has? Ensuring that you have visibility and provide the adequate access that's needed … that's a big component of [sovereignty]."</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> We have a zero-data-retention policy with all of our AI vendors, which is a critical core component of how we maintain our own sovereignty. </figure> <figcaption> <strong>Peter Liebert</strong>CISO, Clari/Salesloft </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>As one of the first steps of sovereign AI frameworks, many businesses look to their data sovereignty practices for AI workloads. "You obviously have to build in the AI sovereignty on top of that data sovereignty," Knesek said. "They're merging together nicely in that sense."</p> <p>One major way Clari/Salesloft is approaching data control is through its zero-data-retention policy, Liebert said. "We have a zero-data-retention policy with all of our AI vendors, which is a critical core component of how we maintain our own sovereignty," Liebert said. "We don't allow any of our own data or customer data to be fed into any of the AI solutions for training, et cetera. It doesn't matter what company we go with -- that is a hard requirement."</p> <h3>Model portability and model-redundant architecture</h3> <p>Businesses are increasingly considering model control as a key differentiator for sovereign AI. Especially as a response to increased vendor disruption and government intervention, having control over AI model access can be make-or-break for enterprise environments.</p> <p>"Right now, there's very little portability of models," West said. "For example, if you buy one company's model and invest hours building an AI agent on that model, you can't really export your data and models you've built to another provider."</p> <p>Limited model portability can be problematic for a business when facing vendor disruptions, government interventions, geopolitical events or AI model security incidents.</p> <p>To compensate for reduced model portability, many businesses are turning to flexible model architecture, sometimes referred to as model-redundant architecture<i>. </i>By building a flexible architecture that isn't dependent on a single vendor or model, businesses can change courses more quickly and swap out models in the event of vendor or political disruption.</p> <p>"We're segmenting out the different components of our overall AI stack," Liebert said. "We have the ability now to have different products in each one of those [sections of the stack] that are custom-tuned so that the model is interchangeable. That portability allows us to be a little bit more flexible in how we're doing things."</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> When it comes to sovereignty and governance and compliance, it's [asking] what do you need to have inside your own data walls? What can [be] SaaS or an outsourced model? </figure> <figcaption> <strong>Eric Helmer</strong>Senior vice president and CTO, Rimini Street </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Increased model portability through a model-redundant architecture gives businesses greater purchasing leverage, Helmer added. If businesses can swap out models, vendors can't as easily keep them locked in their systems, making vendors more likely to work with businesses on opportunistic deals.</p> <p>Model portability helps AI market vendors remain competitive, too, West said. "If you can't change companies in terms of the models you're using or the AI agents you've built, that's very anti-competitive," he said.</p> <h3>Build-versus-buy frameworks</h3> <p>Part of building a flexible AI stack means choosing from varying tech options: local builds, third-party models and <a href="https://www.techtarget.com/ai/feature/Open-source-AI-What-it-means-for-enterprise-innovation">open source</a>. A large part of sovereign AI is a build-versus-buy conversation, with businesses choosing what areas they need to invest in for optimal control versus areas where they are comfortable using third-party or open source products.</p> <p>"When it comes to sovereignty and governance and compliance, it's [asking] what do you need to have inside your own data walls? What can [be] SaaS or an outsourced model?" Helmer said. "I don't think you have to have one or the other. I think we're going to have some sort of hybrid approach."</p> <p>BlackLine is always considering whether to build an agent internally or buy one, Knesek said. The balance lies between its commitment to customers to deliver good products and its need for control, given government decisions and competing regulations.</p> <p>"Anything that we're implementing, we want to have full control of," Knesek said. "We want to know that the products and the tools and the agents we're building are all coded internally and have gone through proper rigor, and that we can maintain them without having them leverage outside public-type tools."</p> <p>Aside from building models and infrastructure internally when possible, some businesses are approaching the "buy" part of the build-versus-buy conversation by adopting a multi-third-party model approach, choosing multiple vendors and models for different areas of the stack.</p> <p>A November 2025 Omdia study, "Emerging Trends in AI Models: Opportunities and Risk Amid the Rapid Evolution," asked respondents about their use of AI models and providers. The study found that, on average, 54% of respondents used two to three model providers, and 44% used three to five generative AI models.</p> <p>"Lots of these companies are using lots and lots of models," Omdia's Beccue said. "You don't see a lot of people locking in on certain things that they can't really replace pretty easily."</p> <p>Clari/Salesloft has "planted [its] flag," so to speak, with two AI vendors, Liebert said. This brings advantages, such as access to the latest models and preferred pricing on tokens. However, avoiding vendor lock-in is still an important part of the equation.</p> <p>"We still have to be careful and not get locked in too much with one [tool], because we know absolutely without a shadow of a doubt that in one year the industry can be completely different. We are flexible to the greatest extent possible, but we also need to make sure that there is a level of stability," he said.</p> <h3>Compliance management</h3> <p>Compliance with regulations is often the primary instigator of sovereign AI discussions. It can be tricky for businesses to reconcile varying regulatory standards across industries and regions worldwide.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> The ISO 42001 is something that we feel very strongly about. We believe, as an international standard, it'll hold up to most regulations around the globe. </figure> <figcaption> <strong>Jill Knesek</strong>CISO, BlackLine </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>As part of its sovereign AI strategies, BlackLine views compliance management as an identify-the-highest-bar scenario, Knesek said. By choosing to comply with the most comprehensive or strict regulatory bar it can find, it has some assurance of compliance. That way, any new jurisdictions or requirements will hopefully fall at or below BlackLine's current compliance level, she said.</p> <p>For BlackLine, the highest regulatory bar was the <a target="_blank" href="https://www.iso.org/home/insights-news/resources/iso-42001-explained-what-it-is.html" rel="noopener">ISO 42001</a>. ISO 42001 is an international standard for AI management systems, providing requirements for businesses on the development and use of their AI systems. It helps businesses implement AI governance that complies with prevailing regulations and manage risks.</p> <p>"We need to be able to demonstrate that we've got the rigor and the governance and compliance controls internally to be able to build [AI] in a safe and secure fashion," Knesek said. "The ISO 42001 is something that we feel very strongly about. We believe, as an international standard, it'll hold up to most regulations around the globe. [It] was a very good investment, and it's built a very strong foundation. And so far, we think that's probably still the high bar."</p> <p>Some businesses are also opting to navigate AI regulations on a case-by-case basis. The goal of scaling AI is to have platforms and technology in different areas of the world doing similar things while being subject to different rules, which is difficult, Brookings' West said. However, businesses can often assess how to navigate national laws to scale AI while remaining compliant.</p> <p>For example, a business serving customers in a country where its operations don't align with prevailing regulations can sometimes locate its cloud or data center in another country, West said. By shifting the bulk of its services outside the country's jurisdiction, the business can gain some control over regulatory requirements.</p> <p>However, governments are beginning to demand that data be stored in the country where AI operations occur, creating new geopolitical tensions as smaller countries lobby for new AI data centers, West added. In the future, the bulk of data centers -- largely in the U.S., Europe and China -- might disperse across more jurisdictions, each with its own regulatory requirements.</p> <p>"Global companies need to think about what's most important to them and what's most important in the future of their business and choose jurisdictions that are most favorable to them on those dimensions," he said.</p> <p><i>Olivia Wisbey is a site editor for Informa TechTarget's AI &amp; Emerging Tech group. She has experience covering AI, machine learning and other emerging technologies.</i></p> </section> With increasingly defined regulations to comply with and political tensions growing, business leaders are adopting AI sovereignty practices to weather the storm. https://cdn.ttgtmedia.com/rms/onlineimages/map_globe_g1040067936.jpg https://www.techtarget.com/ai/feature/The-hybrid-future-of-enterprise-AI-sovereignty Mon, 17 Aug 2026 09:44:00 GMT <p>As of Aug. 2, the EU AI Act assesses penalties for the first time against AI oversights stemming from poor data management. The Act places the onus of compliance squarely on data teams and applies to any organization that interacts with EU residents.</p> <p>A clear problem is that most organizations didn't institute their data infrastructure with such documentation in mind because it wasn't previously required. Now that the Act's obligations for transparency, general purpose AI (GPAI) models and AI literacy are in force, there's a divide between what it penalizes and where most data governance programs actually stand.</p> <p>By examining which specific data management mechanisms are required and where most data governance programs fall short, data teams can identify concrete actions to rectify these shortfalls.</p> <section class="section main-article-chapter" data-menu-title="Data management requisites"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data management requisites</h2> <p>Originally, the AI Act mandated high-risk Annex III systems to be fully compliant by August 2, 2026. The <a href="https://www.techtarget.com/searchenterpriseai/news/366646620/EU-AI-Act-compliance-deadline-is-here-What-to-watch">May 2026 Digital Omnibus</a> agreement tabled many of those requirements until December 2027. The components that took effect Aug. 2 still demand rigorous data management.</p> <p>Under Article 50's transparency requirements, data teams must mark AI-manipulated depictions of real people and deepfakes as AI-generated. Chatbots and similar conversational applications must inform people they're interacting with AI, unless it's obvious, and users must be told when biometric categorization or emotion recognition is in use.</p> <p>GPAI model providers, including teams who substantively tailor foundation models or build applications heavily reliant on them, must keep technical documentation under Annex XI, <a href="https://www.techtarget.com/ai/tip/Explore-the-role-of-training-data-in-AI-and-machine-learning">furnish training data summaries</a>, and confirm the data adheres to EU copyright law under a documented policy. Data literacy is also required of all users and operators of AI systems.</p> </section> <section class="section main-article-chapter" data-menu-title="Governance shortcomings"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Governance shortcomings</h2> <p>For data teams, the biggest obstacle to EU AI Act compliance is AI governance itself. <a href="https://www.gartner.com/en/documents/7854881">A 2025 Gartner survey</a> on how organizations handle cybersecurity risk found that nearly 90% lacked AI governance programs. Although that figure represents only one slice of the enterprise, it still indicates how immature AI governance is today. Many organizations run AI governance tied to specific employees or projects. Meeting the Act's transparency and GPAI mandates becomes far easier when the roles, rules and responsibilities for governing AI systems are <a href="https://www.techtarget.com/data-technologies/opinion/Data-governance-fails-without-CFO-ownership">formalized, documented and spread</a> throughout the enterprise.</p> <p>Many users and operators of AI systems know their own tooling but <a href="https://www.techtarget.com/ai/tip/How-to-keep-data-silos-from-damaging-your-AI-projects">not what runs in other departments</a> or serves other customers. Compliance with the Act's GPAI and transparency requirements all but requires data teams to maintain a comprehensive inventory of which AI systems the organization operates, along with their data dependencies and formal documentation of both -- a demand that falls hardest on GPAI model providers.</p> <p>Noncompliance penalties for GPAI models are €15M or 3% of global turnover, whichever is higher. Systemic risk GPAI models are trained with 10²⁵ FLOPs of compute and require adversarial testing such as red teaming, cybersecurity protections and energy consumption data disclosures. Data teams without complete inventories of AI assets can't meet this requirement.&nbsp;&nbsp;&nbsp;&nbsp;</p> <p>Siloed, employee-tied governance undermines transparency even more directly when it comes to labeling model outputs as AI-generated. When only individual employees hold that knowledge, it rarely reaches end users, even if they pass it to a manager or colleague. The Act requires that knowledge be readily available to the general public when people interact with these systems, as well as to internal users. Noncompliance penalties are €7.5M or 1.5% of global turnover, whichever is higher.</p> </section> <section class="section main-article-chapter" data-menu-title="Remediation"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Remediation</h2> <p>Applying the fundamentals of data governance to their AI instances lets data teams close these gaps. The first step is to classify AI assets fully: the models themselves, their use and users, training data, data models, taxonomies, and data sources. That inventory is what the Act's GPAI documentation and transparency obligations assume already exists. Without it, a data team cannot show which systems are in scope, let alone document them.</p> <p>Typically, only a few key employees hold this institutional knowledge. However, data teams can formalize it through enterprise architecture to map these systems, and through regex, machine learning, and other statistical methods to discover, classify and tag them.&nbsp;</p> <p>Next, data teams should categorize the AI assets by <a href="https://axis-intelligence.com/eu-ai-act-enforcement-guide/">the EU AI Act risk tier</a>: minimal risk, limited risk with transparency requirements, high risk, and prohibited. The tier a system falls into determines which obligations attach to it. A limited-risk chatbot triggers Article 50's disclosure rules, while a systemic GPAI model pulls in adversarial testing and energy reporting. These tiers inform next steps, particularly the immediate documentation of GPAI models and public disclosures when people are interacting with AI systems.</p> <p>The tiers require data teams to update existing governance policies or write new ones. Splitting those policies into two distinct sets helps: one set for the public's interactions with AI systems, another for internal work, such as <a href="https://www.techtarget.com/whatis/definition/red-teaming">red teaming</a> or cybersecurity for systemic GPAI models. Legal counsel can tell an organization whether their use of GPAI models classifies it as a model provider, even if it didn't build the model.</p> <p>In many cases, deployments of dynamic agents can automate parts of the transparency requirements, including <a href="https://www.techtarget.com/searchenterpriseai/feature/How-watermarking-AI-content-benefits-businesses">watermarking content as AI-generated</a> or triggering workflows to inform end users they're interacting with AI.</p> <p><i>Jelani Harper is a data industry analyst and journalist covering data management,&nbsp;AI&nbsp;and enterprise IT for more than a decade. He is a research&nbsp;lead&nbsp;at Blue Badge Insights, writing analyst reports for&nbsp;GigaOm&nbsp;and articles for VentureBeat and The New Stack.&nbsp;&nbsp;</i>&nbsp;</p> </section> Most enterprises govern AI in siloed, employee-tied pockets, but the EU AI Act assumes formalized enterprise-wide governance. That gap drives the risk data teams now face. https://cdn.ttgtmedia.com/rms/onlineimages/legal_g1065824400.jpg https://www.techtarget.com/data-technologies/feature/Where-data-teams-fall-short-on-governance-for-the-EU-AI-Act Mon, 17 Aug 2026 09:30:00 GMT <p>Matt Pocock’s skills remained No. 1 for the week of Aug. 9–16 with 8,231 stars gained. &nbsp;</p> <p>orca entered at No. 2, while agency-agents reached No. 3 and pi climbed from No. 10 to No. 5. &nbsp;</p> <p><a target="_blank" href="https://github.com/public-apis/public-apis" rel="noopener">Public-apis</a> made a notable jump to No. 4, while Agent-Reach fell from No. 4 to No. 13 and taste-skill dropped from No. 8 to No. 18. &nbsp;</p> <p>AI-For-Beginners, graphify, build-your-own-x and generative-ai-for-beginners were among the repositories that dropped out of the top 20.&nbsp;</p> <section class="section main-article-chapter" data-menu-title="Top 20 GitHub repos this week"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Top 20 GitHub repos this week</h2> <p>GitHub users star a project when they want to bookmark it, like it or show appreciation to the creator of the repo. In this way, stars act as a proxy for developer community interest. While any attention-based ranking mechanism is prone to manipulation, IT leaders can still make use of this information. GitHub star growth can signal emerging tools, or tools that teams might ask for next. Star growth metrics also give a window into developer demand, highlighting shadow IT that developers might be experimenting with. Experimenting with <a href="https://www.darkreading.com/application-security/openclaw-ai-runs-wild-business-environments">fast-growing repos can introduce security vulnerabilities</a>, so knowledge of repos in-high demand can help direct the attention of security teams. The top repo list, in aggregate, can also show what <i>types </i>of projects overall are gaining traction in the developer community.</p> <p><iframe title="GitHub weekly trending repositories" aria-label="Table" id="datawrapper-chart-Z6fmP" src="https://datawrapper.dwcdn.net/Z6fmP/3/" scrolling="no" frameborder="0" style="width: 0; min-width: 100% !important; border: none;" height="935" data-external="1"></iframe></p> <p> <script type="text/javascript">window.addEventListener("message",function(a){if(void 0!==a.data["datawrapper-height"]){var e=document.querySelectorAll("iframe");for(var t in a.data["datawrapper-height"])for(var r,i=0;r=e[i];i++)if(r.contentWindow===a.source){var d=a.data["datawrapper-height"][t]+"px";r.style.height=d}}});</script> </p> <p><i>Ben Lutkevich is an award-winning technology writer and editor.</i></p> </section> GitHub Stars are a proxy for developer interest. Weekly GitHub star growth highlights fast-rising repos, giving early insight into adoption trends, risks and strategic opportunities. https://cdn.ttgtmedia.com/visuals/digdeeper/3.jpg https://www.techtarget.com/it-infrastructure/tip/What-repos-are-trending-on-GitHub Mon, 17 Aug 2026 09:15:00 GMT <p><span style="font-weight: 400">AI pervades across every industry, every organisation, every technology platform and every application.</span></p> <p><span style="font-weight: 400">As such, we must accept that AI permeates throughout every discipline of the software application development lifecycle and enterprise IT stack.</span></p> <p><span style="font-weight: 400">Not officially known as ITSMAI, but AI in IT Service Management (ITSM) is the focus of Atomicwork, a company that defines itself an ITSM and ESM platform specialist with an AI workforce to run it.</span></p> <p><span style="font-weight: 400">The company has now partnered with benchmarks-as-a-service specialist New Measure to create ITSMBench, a benchmark designed to evaluate how effectively models from OpenAI, Anthropic, xAI, Z.AI and other frontier specialists and agent frameworks perform real-world ITSM work.&nbsp;</span></p> <section class="section main-article-chapter" data-menu-title="Realistic agent measurement"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">Realistic agent measurement</span></h2> <p><span style="font-weight: 400">By recreating the systems, workflows, and ambiguity that define modern enterprise service desks, the companies say ITSMBench gives the software engineers “a realistic way” to measure what AI agents can actually accomplish today.</span></p> <p><span style="font-weight: 400">“Frontier models are brilliant at writing code, but they are completely blind to the hidden security landmines inside enterprise workflows,” said </span><a href="https://www.linkedin.com/in/amnigos/"><span style="font-weight: 400">Vijay Rayapati</span></a><span style="font-weight: 400">, co-founder and CEO of Atomicwork. “ITSMBench proves that blindly trusting an AI agent right now is an invitation for an enterprise security breach.”</span></p> <p><span style="font-weight: 400">Built jointly by Atomicwork and New Measure, ITSMBench recreates enterprise environments using 42 mocked software systems backed by nearly 1,800 database tables and more than 2,000 REST endpoints.&nbsp;</span></p> </section> <section class="section main-article-chapter" data-menu-title="Service desks, 89 varieties"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">Service desks, 89 varieties</span></h2> <p><span style="font-weight: 400">The benchmark evaluates 89 service desk tasks spanning the kinds of L2 and L3 investigations enterprises handle every day, including identity and access management, devices, networking, security operations, infrastructure, and engineering escalations.&nbsp;</span></p> <p><span style="font-weight: 400">For the uninitiated and those unfamiliar with the L Support system…</span></p> <ul class="default-list"> <li style="font-weight: 400"><span style="font-weight: 400">L1 Support: Front-line IT support that handles basic user requests, routine troubleshooting, and initial triage.</span></li> <li style="font-weight: 400"><span style="font-weight: 400">L2 Support: Advanced IT support that investigates complex technical issues, system configurations, and escalated tickets.</span></li> <li style="font-weight: 400"><span style="font-weight: 400">L3 Support: Expert-level IT support that resolves deep system issues, structural bugs, and enterprise escalations.&nbsp;</span></li> </ul> <p><span style="font-weight: 400">Every environment, task, and evaluation is open source, allowing researchers and enterprises to reproduce results and build on the benchmark.</span></p> <p><span style="font-weight: 400">Initial evaluations show that today’s frontier models exhibit distinct strengths and weaknesses with different harnesses:</span></p> <ul class="default-list"> <li style="font-weight: 400">Grok 4.5 leads at tool discovery, finding the right APIs 83.0% of the time, but ranks near the bottom on actually finishing the job.</li> <li style="font-weight: 400">Opus 5 performs best on execution, completing 63.5% of tasks once the right tools are in hand, despite having the weakest discovery rate at 70.2%.</li> <li style="font-weight: 400">GPT-5.6 Sol splits the difference, landing between Grok 4.5 and Opus 5 across discovery and execution.</li> <li style="font-weight: 400">GLM-5.2 is far cheaper, costing $0.25 per trial, but trails both Opus 5 and GPT-5.6 Sol on execution.</li> </ul> <p><span style="font-weight: 400">The benchmark also demonstrates that agent frameworks can materially affect both accuracy and cost, and that models frequently stop investigating after finding a plausible explanation instead of verifying the true root cause.&nbsp;</span></p> </section> <section class="section main-article-chapter" data-menu-title="No single model solved the set"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">No single model solved the set</span></h2> <div id="attachment_5058" style="width: 260px" class="wp-caption alignright"> <img loading="lazy" decoding="async" aria-describedby="caption-attachment-5058" class="wp-align wp-image-5058 " src="https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/CEO-300x300.jpg" alt="" width="250" height="250" srcset="https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/CEO-300x300.jpg 300w, https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/CEO-150x150.jpg 150w, https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/CEO.jpg 400w" sizes="(max-width: 250px) 100vw, 250px"> <p id="caption-attachment-5058" class="wp-caption-text">Rayapati: ITSMBench proves that blindly trusting an AI agent right now is an invitation for an enterprise security breach.</p> </div> <p><span style="font-weight: 400">Even when agents identify the correct resolution, they often leave related systems, records, or follow-up actions incomplete. Across the benchmark, 73 of 89 tasks were successfully completed at least once by at least one model, although no single model solved the full set.</span></p> <p><span style="font-weight: 400">“Enterprise service management demands more than reasoning,” said </span><a href="https://www.linkedin.com/in/arushi-gandhi/"><span style="font-weight: 400">Arushi Gandhi</span></a><span style="font-weight: 400">, CEO at New Measure. “One model fits all is seldom the right answer. Enterprises that want an AI-run service desk need to optimise for accuracy, cost, and time to resolution at the same time.”</span></p> <p><span style="font-weight: 400">Gandhi says that getting this challenge right takes a constellation of orchestrated models.&nbsp;</span></p> <p><span style="font-weight: 400">The ITSMBench benchmark, methodology, benchmark results, and open source environments are available at </span><a href="https://www.atomicwork.com/itsm-bench"><span style="font-weight: 400">itsm-bench</span></a><span style="font-weight: 400">.</span></p> </section> <section class="section main-article-chapter" data-menu-title="What should developers think next?"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">What should developers think next?</span></h2> <p><span style="font-weight: 400">For software engineering and IT operations teams, ITSMBench may feel like something of a reality check i.e. it could show teams that placing over-reliance on a single frontier model for end-to-end service automation is not always (or, perhaps, never, if we’re honest) the most sensible move… largely because reasoning power does not equate to operational thoroughness and comprehensiveness by any measure.</span></p> <p><span style="font-weight: 400">On the road ahead, software engineers may now be far quicker to ask how quickly they are able to architect and deploy multi-model (and multi-modal) multi-agent frameworks with the right tools and disciplined root-cause verification within approved guardrails.</span></p> <p><img loading="lazy" decoding="async" class="wp-align alignnone wp-image-5059" src="https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/bottom.png" alt="" width="580" height="292" srcset="https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/bottom.png 1360w, https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/bottom-300x151.png 300w, https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/bottom-1024x515.png 1024w, https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/bottom-768x386.png 768w" sizes="(max-width: 580px) 100vw, 580px"></p> </section> AI pervades across every industry, every organisation, every technology platform and every application. As such, we must accept that AI permeates throughout every discipline of the software ... https://www.computerweekly.com/blog/Open-Source-Insider/Atomicwork-New-Measure-lay-down-new-standard-for-AI-evaluation-in-ITSM Mon, 17 Aug 2026 09:10:16 GMT <p>In a move that will see the creation of the UK’s “largest” independent connectivity and managed technology services providers, positioned to help organisations accelerate their digital ambitions through a single trusted technology partner, ARO and TalkTalk Business have announced their merger.</p> <p>With approximately 650 employees and annual revenues of around £200m, <a href="https://aro.tech/">ARO</a> describes itself as an enterprise performance partner, delivering sustainable competitive advantages to clients, employees and customers. It deploys cloud technologies with service and has partnerships with global tech leaders such as Microsoft, Dell and Aruba.</p> <p>The company currently has 8,000 customers and manages over 100,000 mobile devices, 60,000 hosted telecom seats and deliver secures connectivity for more than 4,500 companies.</p> <p>The merger is claimed to bring together two highly complementary businesses with stated shared ambitions to help organisations navigate increasingly complex technology challenges. It is subject to final approval under the National Security Investment Act (NSI), a process which is expected to be concluded by the end of the summer.</p> <p>The merged company between ARO and the former business arm of leading UK telecoms provider <a href="https://www.computerweekly.com/news/252513303/TalkTalk-switch-to-full-fibre-benefits-climate">TalkTalk</a> will combine ARO’s expertise in cloud, cyber security and managed IT services with TalkTalk Business’s established expertise in connectivity, networking and communications to create a broader end-to-end technology proposition for customers across the UK.</p> <p>Together, the combined group will have a combined customer base of more than 70,000 organisations which, assert the two firms, will have the scale, expertise and resources to accelerate investment in technology, service delivery and innovation, strengthening its ability to support customers at every stage of their digital transformation journey.</p> <p>Initially, both companies will continue to operate under their existing brands and from their current office locations. The firms said this is to ensure continuity for customers, employees and partners while integration plans progress.</p> <p>ARO believes the merger represents an opportunity to extend its impact as part of a larger organisation with expanded capabilities, greater scale and increased capacity for investment, enabling it to support customers with an even broader range of technology solutions.</p> <p>For <a href="https://www.talktalk.business/connectivity/leased-lines">TalkTalk Business</a>, the merger is seen as marking a significant milestone in its evolution into a managed technology services provider following its separation from TalkTalk Group in February 2026. It builds on the recent acquisition of Planet IT and brings together complementary expertise that further strengthens its ability to support customers with integrated connectivity, cloud, cyber security and managed IT services.</p> <p>Commenting on the move, ARO CEO Ciaran Rafferty called the merger a defining moment for both ARO and TalkTalk Business. “Together, we are creating a business with the scale, expertise and ambition to become a leading independent provider of connectivity and managed technology services in the UK,” he said.</p> <p>“By bringing together our complementary strengths, we are creating a stronger partner with broader capabilities, deeper expertise and greater capacity to invest in innovation, service delivery and long-term customer success.”</p> <p>TalkTalk Business CEO Ruth Kennedy added: “This merger represents another important step in our transformation into a leading managed services provider and brings together two highly complementary businesses to create a leading independent technology partner for UK organisations.</p> <p>“The market is evolving rapidly, with organisations increasingly seeking technology partners that can combine strategic expertise, operational excellence and broad service capabilities at scale. This combination creates a business that is uniquely positioned to meet those expectations and support customers across every stage of their technology journey. We are creating a platform with the scale to invest, innovate and grow. Together, we have an exciting opportunity to play a leading role in the future of the UK technology services market.”</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about business communications</h3> <ul class="default-list"> <li><a href="https://www.computerweekly.com/news/366643464/Record-fibre-connections-but-BT-posts-mixed-2026-financial-year">Record fibre connections but BT posts mixed 2026 financial year</a>: UK’s leading communications provider claims solid FY26, with highs in FTTP connections and cost control, but sees headwinds on broadband business<a href="https://www.computerweekly.com/news/366643464/Record-fibre-connections-but-BT-posts-mixed-2026-financial-year">.</a></li> <li><a href="https://www.computerweekly.com/news/366614092/Poor-communication-is-biggest-hurdle-to-business-collaboration">Poor communication is biggest hurdle to business collaboration</a>: Study finds firms are wasting hours of time to make a decision as a result of poor collaboration practices, with over two-fifths of workers having to redo work due to poor guidance on project requirements.</li> <li><a href="https://www.computerweekly.com/news/366640321/Ofcom-sets-out-regulation-to-push-UK-gigabit-broadband-to-final-phase">Ofcom sets out regulation to push UK gigabit broadband to ‘final phase’</a>: UK communications regulator lays down regulation required to drive full-fibre roll-out through its end phase to universal access across the country, aiming to allow businesses to&nbsp;unlock economic&nbsp;gains.</li> <li><a href="https://www.techtarget.com/it-strategy/feature/Key-sustainability-communications-strategies-for-businesses">Key sustainability communications strategies for businesses</a>: Sustainability communications are key to reaching lower carbon emissions and other environmental goals. Learn practices that help improve outcomes and ways to avoid greenwashing.</li> </ul> </div> </div> Enterprise arm of comms provider and tech services provider unite to create one of the UK’s largest independent providers of connectivity and managed technology services https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Handshake-merger-adobe.jpg https://www.computerweekly.com/news/366649495/TalkTalk-Business-ARO-merge-to-boost-business-connectivity Mon, 17 Aug 2026 06:50:00 GMT <p><em>This is a guest post for the Computer Weekly Developer Network written by&nbsp; <a href="https://www.linkedin.com/in/paulquigleypce/">Paul Quigley</a>, chief strategic relations officer at Airsys Cooling Technologies.</em></p> <p><em>Airsys Cooling Technologies is known for its mission-critical HVAC solutions designed specifically for global digital infrastructure, including hyperscale datacentres and telecommunications networks.</em></p> <p><em><span style="font-weight: 400"> Quigley writes in full as follows…</span></em></p> <p><span style="font-weight: 400">The edge computing conversation usually begins with latency. </span></p> <p><span style="font-weight: 400">Moving compute closer to where data is generated reduces the delay and bandwidth involved in sending everything back to a central cloud. That remains important, but agentic AI is creating a more consequential requirement: moving decision-making closer to where action occurs.</span></p> <blockquote> <p><span style="font-weight: 400">Traditional AI inference largely answers a request. An AI agent can observe conditions, retrieve information, reason through several steps, use tools, initiate an action and then assess the result. In a factory, hospital, utility network, transport system or smart building, that action may affect a physical process. Depending on a distant data centre for every step can introduce delay, connectivity risk and questions over where sensitive operational data is processed.</span></p> </blockquote> <p><span style="font-weight: 400">The edge is no longer merely where data is filtered. It is increasingly where operational authority is exercised.</span></p> <section class="section main-article-chapter" data-menu-title="The cloud pervades"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The cloud pervades</h2> <p><span style="font-weight: 400">This does not mean the cloud disappears. It means agentic systems will become distributed. Some model training, large-scale computation and fleet-wide orchestration will remain centralised, while local agents, data and tools operate at the edge. AWS is already defining local and distributed agentic patterns around latency, data residency, compliance and operational complexity.</span></p> <p><span style="font-weight: 400">A useful comparison is the electricity grid. Large generating stations did not remove the need for infrastructure closer to the user. Electricity travels through a layered network of transmission systems, substations and local distribution, with transformation, switching and protection taking place progressively closer to demand.</span></p> <div id="attachment_12420" style="width: 292px" class="wp-caption alignright"> <img loading="lazy" decoding="async" aria-describedby="caption-attachment-12420" class="wp-align wp-image-12420 size-full" src="https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/1618403487203.jpg" alt="" width="282" height="282" srcset="https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/1618403487203.jpg 282w, https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/1618403487203-150x150.jpg 150w" sizes="(max-width: 282px) 100vw, 282px"> <p id="caption-attachment-12420" class="wp-caption-text">Quigly: Productisation should not be confused with commoditisation – a repeatable platform can still carry considerable engineering value.</p> </div> <p><span style="font-weight: 400">Agentic AI may develop in much the same way. The cloud will continue to provide central scale, while edge data centres increasingly act as digital substations, bringing processing, control and operational authority closer to the equipment, people and systems they serve.</span></p> </section> <section class="section main-article-chapter" data-menu-title="The agentic edge"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The agentic edge</h2> <p><span style="font-weight: 400">The physical consequence is easy to overlook. The agentic edge will require more than a small inference device mounted inside a cabinet. Many installations will combine GPUs, CPUs, local storage and networking with the systems needed for security, validation, observability and remote control.</span></p> <blockquote> <p><span style="font-weight: 400">Thousands of geographically distributed sites cannot each be treated as bespoke construction projects, nor can they depend upon permanent local technical staff. Fully managed edge computing therefore cannot stop at software orchestration. Power, cooling, fire protection, physical security, monitoring and service architecture must also become repeatable and remotely manageable.</span></p> </blockquote> <p><span style="font-weight: 400">The likely result is a transition from project to product: the edge data centre as a mission-critical infrastructure appliance, factory-engineered, tested before deployment and configured for its particular application. The Open Compute Project already publishes specifications for prefabricated, all-in-one edge data centres, including a design supporting up to 90kW of IT load.</span></p> <p><span style="font-weight: 400">Productisation should not be confused with commoditisation – a repeatable platform can still carry considerable engineering value.</span></p> <blockquote> <p><span style="font-weight: 400">Consider the cooling systems used to protect MRI equipment. A proven platform may be manufactured repeatedly and scaled, yet it remains a highly engineered, mission-critical system because the application demands precise thermal performance, reliability and serviceability. Its value lies not merely in its components, but in protecting expensive equipment and the medical services that depend upon it.</span></p> </blockquote> <p><span style="font-weight: 400">Edge data centres can follow the same path: increasingly standardised and scalable, yet differentiated by the performance, resilience and application expertise engineered into them.</span></p> <p><span style="font-weight: 400">Their location may also create another opportunity. Europe is already moving data-centre heat recovery from a sustainability aspiration towards a formal design consideration. Under the EU Energy Efficiency Directive, Member States must ensure that data centres with a total rated energy input exceeding 1MW utilise waste heat or other heat-recovery applications unless this is technically or economically infeasible.</span></p> </section> <section class="section main-article-chapter" data-menu-title="Repurposed waste heat"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Repurposed waste heat</h2> <p><span style="font-weight: 400">In June 2026, 14 European industry associations also agreed to develop a model connecting datacentre operators, energy stakeholders and public authorities, including the integration of waste heat into district-heating systems.</span></p> <blockquote> <p><span style="font-weight: 400">Many edge facilities will sit below that regulatory threshold, but their proximity to factories, hospitals, campuses, commercial buildings or residential developments may make local heat reuse more practical. The challenge is not simply producing heat. It is placing useful heat near a real and reasonably consistent demand for it.</span></p> </blockquote> <p><span style="font-weight: 400">Agentic AI will not merely move more computing closer to users. It will force software orchestration, physical infrastructure and thermal design to converge. The winners will not simply deliver a box. They will deliver a configurable, remotely managed and application-ready platform – standardised enough to scale, but engineered well enough to deserve mission-critical status.</span></p> <p><em><span style="font-weight: 400">Paul Quigley works closely with customers and partners across the AI and digital infrastructure landscape. Since joining Airsys in 2021, he has helped lead the company’s expansion into the AI and hyperscale datacentre market, contributing to cumulative revenue growth exceeding 1,700% through 2026.</span></em></p> <p><img loading="lazy" decoding="async" class="wp-align alignnone wp-image-12419" src="https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/Screen-Shot-2026-08-17-at-11.32.17.565-AM.png" alt="" width="580" height="164" srcset="https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/Screen-Shot-2026-08-17-at-11.32.17.565-AM.png 1730w, https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/Screen-Shot-2026-08-17-at-11.32.17.565-AM-300x85.png 300w, https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/Screen-Shot-2026-08-17-at-11.32.17.565-AM-1024x289.png 1024w, https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/Screen-Shot-2026-08-17-at-11.32.17.565-AM-768x217.png 768w, https://itknowledgeexchange.techtarget.com/cwdn/files/2026/08/Screen-Shot-2026-08-17-at-11.32.17.565-AM-1536x434.png 1536w" sizes="(max-width: 580px) 100vw, 580px"></p> </section> This is a guest post for the Computer Weekly Developer Network written by  Paul Quigley, chief strategic relations officer at Airsys Cooling Technologies. Airsys Cooling Technologies is known for ... https://www.computerweekly.com/blog/CW-Developer-Network/Edge-series-Advanced-Cooling-Systems-How-agentic-AI-is-reshaping-the-edge-datacentre Mon, 17 Aug 2026 06:42:09 GMT <p>Over 150 4G mast upgrades are now live across the UK’s national parks, including the Yorkshire Dales and Eryri, Snowdonia, as part of the continued roll-out of the UK government’s Shared Rural Network (SRN) programme that has provided extended 4G coverage across over 5,684 square kilometres, in areas that previously only had limited access to mobile coverage or none at all.</p> <p>Launched in 2020, the&nbsp;<a href="https://www.computerweekly.com/news/252472883/UK-government-proposes-13bn-scheme-to-improve-rural-mobile-coverage">£1.3bn SRN scheme</a> is a joint initiative between the government and the UK’s mobile network operators – EE and Virgin Media O2 (VMO2), as well as&nbsp;<a href="https://www.computerweekly.com/news/366633582/VodafoneThree-network-sharing-unlocks-significant-coverage-improvements">Three and Vodafone before their merger</a>&nbsp;– to extend 4G connectivity to 95% of the UK’s landmass by the end of 2025. The founding principle is that through both public and private investment, new and existing phone masts will be built or upgraded across the UK to close down so-called&nbsp;<a href="https://www.computerweekly.com/news/366558677/Stark-digital-comms-divide-between-UK-rural-and-urban-areas">rural mobile not-spots</a>.</p> <p>Under the scheme, the four operators committed to improving 4G coverage and levelling up connectivity across the UK, which has seen them invest in a shared network of new and existing phone masts, overseen by jointly owned company&nbsp;<a href="https://dmsluk.com/">Digital Mobile Spectrum Limited</a>. The operators’ £532m investment has been complemented by more than £501m in government funding.</p> <p>The SRN is also seeing UK government investment of £184m to upgrade extended area service (EAS) masts – originally built to support the&nbsp;<a href="https://www.computerweekly.com/news/366585817/CGI-selected-to-streamline-UK-ESN-programme">Emergency Services Network</a> – to provide coverage from all four mobile operators.</p> <p>Mobile operators have invested more than £500m to target “partial not-spots” across the UK, where customers can only access 4G if they are signed up with a mobile network operator that is active in the area.</p> <p>The government-funded 4G mast upgrades are delivered through existing infrastructure, and bring 4G coverage from EE, Virgin Media O2, and Vodafone and Three UK to bolster connectivity in rural areas.</p> <p>The roll-out is intended to support accessing online public services, working more flexibly from home, running payments and bookings for local firms, and for holidaymakers accessing location data or calling for emergency assistance.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about the SRN</h3> <ul class="default-list"> <li><a href="https://www.computerweekly.com/news/366640234/Shared-Rural-Network-expansion-removes-Islay-not-spots">Shared Rural Network expansion removes Islay not-spots</a>: Latest development in £1.3bn mobile expansion scheme sees mobile not-spots reduced on Scottish island as 4G site goes live, providing coverage from all mobile operators for the first time.</li> <li><a href="https://www.computerweekly.com/news/366639807/Shared-Rural-Network-scheme-hits-mast-upgrade-milestone-in-Wales">Shared Rural Network scheme hits mast upgrade milestone in Wales</a>: Latest expansion of government’s £1.3bn mobile coverage scheme sees significant expansion of mast construction in rural parts of Wales from all four UK operators.</li> <li><a href="https://www.computerweekly.com/news/366636722/UK-government-further-expands-rural-4G-coverage-through-SRN">UK government further expands rural 4G coverage through SRN</a>: Over 100 mobile masts have been upgraded across rural Wales, Scotland and England, delivering 4G coverage from all mobile network operators for the first time as part of an ongoing development scheme.</li> <li><a href="https://www.computerweekly.com/news/366628346/North-Yorkshire-sees-4G-coverage-boost-through-SRN">North Yorkshire sees 4G coverage boost through SRN</a>: Expansion of £5bn UK mobile coverage scheme takes place in North Yorkshire to offer improved connectivity in and around market towns.</li> </ul> </div> </div> <p>Some 42 Shared Rural Network sites are now active across the UK’s national parks, including 25 sites in England covering areas such as the Lake District and Yorkshire Dales, 16 sites in Wales including Eryri, and one site in Scotland in Loch Lomond and the Trossachs. With this latest roll-out across the UK’s national parks, the Shared Rural Network programme has now hit its objective of extending 4G coverage to 95% of the UK landmass a year ahead of schedule.</p> <p>“Strengthening connectivity in rural areas is a key aspect of the UK's growth ambition, providing greater access to digital services, AI tools and streaming in hard-to-reach locations like the Yorkshire Dales and Eryri,” said Mike Hellers, product development manager at interconnection and colocation services firm <a title="https://url.us.m.mimecastprotect.com/s/tutLCOYEZruwynOZ2SvhB2hGpe08?domain=urldefense.com" href="https://url.us.m.mimecastprotect.com/s/tutLCOYEZruwynOZ2SvhB2hGpe08?domain=urldefense.com">London Internet Exchange</a>.</p> <p>“As more communities gain access to reliable 4G coverage through the Shared Rural Network, efficient traffic exchange and keeping data as local as possible will become increasingly important in delivering the low-latency, resilient services people expect. Continued investment across the wider internet ecosystem will be essential to support growing demand and maximise the benefits of expanded mobile connectivity.”</p> <p>Elizabeth Anderson, CEO of the <a title="https://url.us.m.mimecastprotect.com/s/bLnPCPNMYvtZkW6N5C1ilXhxYt9O?domain=urldefense.com" href="https://url.us.m.mimecastprotect.com/s/bLnPCPNMYvtZkW6N5C1ilXhxYt9O?domain=urldefense.com">Digital Poverty Alliance</a>, added: “Connectivity continues to get taken for granted across the UK despite being something we all rely on so heavily. Rural communities, in particular, have long faced challenges as essential digital services such as healthcare, banking and education shift online, also having a knock-on impact on wider employment and access opportunities.</p> <p>“The government’s latest expansion of the Shared Rural Network roll-out is an important step in recognising the importance of reliable mobile and internet access to keep people connected in remote areas. Connectivity is a key component of digital inclusion, and the next step is ensuring people in Yorkshire have affordable and suitable devices for work and school, alongside the digital skills to use them effectively. These government initiatives set the tone for inclusivity in the UK’s regions.”</p> Over 150 4G mast upgrades are now live across the UK’s national parks as part of the Shared Rural Network, as target of having 4G coverage across 95% of the UK has been achieved a year ahead of schedule https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/EE-SRN-4G-mast-hero.jpg https://www.computerweekly.com/news/366648774/UK-Shared-Rural-Network-roll-out-passes-key-target Mon, 17 Aug 2026 06:30:00 GMT <p><span style="font-weight: 400">Open source is (of course) the foundation for much of the Internet and the methods underpinning fundamental cybersecurity practices today.</span></p> <p><span style="font-weight: 400">Its inherent transparency lets “defenders” verify instead of having to rely on trust – and its openness has also cemented a discipline that the whole industry now depends on, such as signed artefacts and dependency inventories.</span></p> <p><span style="font-weight: 400"><strong>NOTE:</strong> Signed artefacts (artifacts, if you’re across the pond) are digital items or physical objects cryptographically or visibly marked to verify their creator, preserve integrity, and ensure authenticity.</span></p> <p><span style="font-weight: 400">AI is arriving at the same kind of fork in the road that open source has experienced.</span></p> <section class="section main-article-chapter" data-menu-title="Data, inference &amp; audit trails"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">Data, inference &amp; audit trails</span></h2> <p><span style="font-weight: 400">Open models can now extend an advantage to defenders, primarily because software engineers can run them on their own infrastructure, so they let organisations keep sensitive data, inference, and audit trails inside their own boundary.</span></p> <p><a href="https://www.linkedin.com/in/christalevi/?skipRedirect=true"><span style="font-weight: 400">Chris Talevi</span></a><span style="font-weight: 400">, chief information security officer (CISO) at</span><a href="https://www.computerweekly.com/blog/CW-Developer-Network/Domino-Data-Lab-Agentic-AI-is-scaling-faster-than-governance-the-split-explained"> <span style="font-weight: 400">Domino Data Lab</span></a><span style="font-weight: 400">, says that enterprises scaling their AI adoption need to consider new risk factors that AI introduces.</span></p> <blockquote> <p><span style="font-weight: 400">“The defining difference between AI (and many other monumental changes like it) is its pace,” said Talevi. “As such, velocity is the critical component that enterprises cannot ignore. Teams will move rapidly towards the best combination of intelligence &amp; cost. Enterprises must be ready for that pivot, and momentum is just beginning to build up.”</span></p> </blockquote> <p><span style="font-weight: 400">Talevi references</span><a href="https://www.microsoft.com/en-us/corporate-responsibility/topics/open-weight/"> <span style="font-weight: 400">July’s open letter</span></a><span style="font-weight: 400">, signed by 30+ companies to the White House, and says that this might be the first meaningful crack in the dam as more and more enterprises move away from and/or supplement their reliance on frontier model providers as their primary, or only, source of AI.</span></p> </section> <section class="section main-article-chapter" data-menu-title="Zero risk is not the goal"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">Zero risk is not the goal</span></h2> <p><span style="font-weight: 400">“To scale AI effectively and safely, enterprises also urgently need an internal governance structure and body capable of adapting to a rapidly changing risk profile,” said Talevi. “This governance body needs to balance speed and enablement with risk management. The goal has never been zero risk, but to achieve bounded or acceptable levels of risk in balance (and at times tension) with business priorities.”</span></p> <p><span style="font-weight: 400">The Domino security man thinks that, when weighing up what’s happening here, whether an enterprise is using frontier models, open source ones, or hosting their own models, its governance focus should be on a few key tenets:</span><span style="font-weight: 400"><br> </span></p> <ul class="default-list"> <li style="font-weight: 400"><span style="font-weight: 400">First, enterprises must understand what their AI implementation or agents can do &amp; on whose behalf, as this is the foundation of identity and access management. </span> <span style="font-weight: 400"><br> </span></li> <li style="font-weight: 400"><span style="font-weight: 400">Second, they must understand the blast radius, including preparing for potential incidents. </span> <span style="font-weight: 400"><br> </span></li> <li style="font-weight: 400"><span style="font-weight: 400">Third, </span> <span style="font-weight: 400">they must maximise observability with tools such as audit logs.</span></li> </ul> <p><span style="font-weight: 400">He reinforces his point and says that it’s also crucial that “AI leadership understand the asymmetric nature of the frontier models and cybersecurity” today, because many enterprises rely on models with substantial guardrails in place to prevent cyber misuse. Those same guardrails can slow down defenders.</span></p> </section> <section class="section main-article-chapter" data-menu-title="Don’t foreclose on the open option"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">Don’t foreclose on the open option</span></h2> <p><span style="font-weight: 400">Meanwhile, attackers are leveraging models without those same limitations… and, also m</span><span style="font-weight: 400">eanwhile, regulators also play a role in ensuring AI security.</span></p> <blockquote> <p><span style="font-weight: 400">“While much of their guidance is still taking shape, it’s important for regulators not to foreclose on the open option before we have the actual evidence for or against it,” said Talevi. “Restrictions should follow risk analysis, and at this point, it feels more like a presumption that closed systems are safer by default.”</span></p> </blockquote> <p><span style="font-weight: 400">It feels like the most useful thing policymakers could support is shared evaluation benchmarking, and a clearing house with red-team capacity that lets anyone determine what is true.</span></p> </section> <section class="section main-article-chapter" data-menu-title="CISO deep dive"> <h2 class="section-title"><i class="icon" data-icon="1"></i><span style="font-weight: 400">CISO deep dive</span></h2> <div id="attachment_5051" style="width: 288px" class="wp-caption alignright"> <img loading="lazy" decoding="async" aria-describedby="caption-attachment-5051" class="wp-align wp-image-5051 " src="https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/Domino-300x289.jpg" alt="" width="278" height="268" srcset="https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/Domino-300x289.jpg 300w, https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/Domino-768x741.jpg 768w, https://itknowledgeexchange.techtarget.com/open-source-insider/files/2026/08/Domino.jpg 868w" sizes="(max-width: 278px) 100vw, 278px"> <p id="caption-attachment-5051" class="wp-caption-text">Talevi: Ephemeral agents that exist for seconds may break the delegation model entirely but still must be accounted for in the audit log source of truth.</p> </div> <p><span style="font-weight: 400">The Computer Weekly Developer Network sat down with Talevi for an extra helping of his insight and analysis on this matter.</span></p> <p><b>CWDN: </b><span style="font-weight: 400">You’ve engineered governance guidance around identity, blast radius and observability – practically, what does an audit log need to capture for an AI agent that it wouldn’t already capture for a human user?</span></p> <p><b>Talevi: </b><span style="font-weight: 400">I would first start with observability regarding the question “on whose behalf?” The delegation chain from human to agent to sub-agent is the thing human audit logs haven’t had to record. Then we must capture the remaining core factors: model and version, the context and retrieval it was given, what it attempted, what was blocked, and what it ultimately did to which resource. Lastly, I’d add one caveat: ephemeral agents that exist for seconds may break the delegation model entirely but still must be accounted for in the audit log source of truth.</span></p> <p><b>CWDN:</b><span style="font-weight: 400"> Give us stats – what proportion of enterprises today can actually trace an AI-driven action back through a full audit trail, from inference to outcome to identity?</span></p> <p><b>Talevi: </b><span style="font-weight: 400">Honestly, a very small percentage, particularly when considering the full chain from identity to inference to outcome.</span></p> <blockquote> <p><span style="font-weight: 400"> Broadly, we know from Domino’s </span><span style="font-weight: 400">Enterprise AI Report</span><span style="font-weight: 400"> that 600+ surveyed companies are evenly split between those with governed agents and those with ungoverned agents, at roughly 40% each. I’d be skeptical of anyone who offers granular traceability stats with high confidence, but a 2026 survey of 235 CISOs and CIOs found 92% lack full visibility into their AI agent identities, and 95% doubt they could detect or contain a compromised agent (</span><a href="https://saviynt.com/ciso-ai-risk-report-2026"><span style="font-weight: 400">Source</span></a><span style="font-weight: 400">). Single digits feels right to me based on discussions with peers across industry.</span></p> </blockquote> <p><b>CWDN:</b><span style="font-weight: 400"> Looking at July’s open letter, what changes practically for a developer choosing between open and closed models this year?</span></p> <p><b>Talevi: </b><span style="font-weight: 400">The signatories include direct competitors at nearly every layer of the stack: the chip designers, the hyperscalers, the frontier labs, the security vendors many of us buy from, the tooling that sits underneath all of it, and the operators who run on top of it. It’s the broader supply chain, and it is incredibly telling to see a rare level of agreement across that di</span><span style="font-weight: 400">verse group.</span><span style="font-weight: 400"> ‘</span></p> <blockquote> <p><span style="font-weight: 400">Why now’ is a convergence: model quality closed the gap, token economics started to bite, sentiment shifted, and open weights got entangled with the broader question of who will win the race for global AI supremacy. </span></p> </blockquote> <p><span style="font-weight: 400">The cost/benefit ratio is changing for developers: open-weight models are now good enough that self-hosting is a defensible engineering decision.</span></p> <p>&nbsp;</p> <p>&nbsp;</p> </section> Open source is (of course) the foundation for much of the Internet and the methods underpinning fundamental cybersecurity practices today. Its inherent transparency lets “defenders” verify instead ... https://www.computerweekly.com/blog/Open-Source-Insider/Dominos-Talevi-Open-source-AI-is-cybersecuritys-next-big-fork Mon, 17 Aug 2026 06:10:08 GMT 60 webmaster@techtarget.com