New & Notable
Get Started
To justify physical AI costs, choose high-value use cases
Physical AI is starting to drive business value in industries like manufacturing and healthcare. But the ROI calculus is subtle and calls for a wide-angle view of metrics.
Manage
AI cloud migration: Key steps to success
Migrating AI to the cloud demands strategic planning, system assessments, component modernization, data pipeline optimization and phased deployment. Find out what you need to know.
Get Started
Planning AI infrastructure upgrades: Four steps for success
AI infrastructure upgrades require proactive planning. Steps include setting business goals, assessing existing infrastructure, and optimizing hardware, security and governance.
Manage
What businesses really need from an AI off switch
Turning off an AI feature doesn't necessarily stop AI processing. Businesses need meaningful controls over AI features, data access, third parties and software updates.
Trending Topics
-
Quantum Computing News
What Claude Mythos revealed about post-quantum security
Quantum computing will break standard security codes and change how we protect data and prepare for the future. Claude Mythos proved we're still not ready for the quantum era.
-
Enterprise AI Strategy Manage
Key enterprise strategies for AI agent observability
Monitoring AI agents encompasses three pillars: agent intent, method and outcome. Explore all three, along with best practices for AI agent observability.
-
Emerging Tech Get Started
Making space for spatial computing
Construct spatial computing programs through evidence, not hype. Use this roadmap to ensure that workflow selection is the starting point, not device selection.
-
AI Technologies & Platforms Evaluate
Ethical AI surveillance balances oversight and transparency
AI-powered employee surveillance gives employers new visibility into workers while raising concerns about privacy, bias and trust. Learn how enterprises can deploy it responsibly.
-
AI Infrastructure Manage
AI cloud migration: Key steps to success
Migrating AI to the cloud demands strategic planning, system assessments, component modernization, data pipeline optimization and phased deployment. Find out what you need to know.
-
AI Ethics & Governance Manage
What businesses really need from an AI off switch
Turning off an AI feature doesn't necessarily stop AI processing. Businesses need meaningful controls over AI features, data access, third parties and software updates.
Sponsored Sites
-
Artificial Intelligence
Intel & Red Hat: Leading the way in Enterprise AI
Combining Intel’s silicon experience with Red Hat’s software innovation to enable AI-driven hybrid multi-cloud solutions.
-
Information Management
Information Reimagined
Looking to drive innovation, enhance security, and streamline operations? Information management solutions based on AI, cloud, and security help you get there.
-
Articlficial Intelligence
AI-Powered Devices: The Fourth Wave of Enterprise Computing
Enterprise computing enters its fourth wave as client devices transform from passive endpoints to intelligent AI systems. Modern laptops, desktops, and mobile devices now feature built-in NPUs and AI accelerators that bring artificial intelligence directly to where work happens. This shift creates distributed intelligence networks where every device anticipates user needs, optimizes workflows, and collaborates autonomously. Organizations gain enterprise AI at scale, transforming employees into human AI agents with unprecedented access to contextual, personalized computing experiences. The future of work is here—powered by intelligent devices that don't just access AI, but embody it.
Find Solutions For Your Project
-
Evaluate
Making space for spatial computing
Construct spatial computing programs through evidence, not hype. Use this roadmap to ensure that workflow selection is the starting point, not device selection.
-
A guide to AI chip architectures
-
Ethical AI surveillance balances oversight and transparency
-
AI agent security: How reliable is enterprise AI testing?
-
-
Problem Solve
Beyond discovery: The real shadow AI challenge
IT teams can now identify shadow AI tools, but remediation doesn't scale. Managing hundreds of niche AI tools requires faster approvals and distributed governance.
-
Power-hungry AI data centers weigh viable energy sources
-
AI isn't breaking higher education – it's exposing the cracks
-
HAL 9000 was right: AI guardrails matter more than perfect models
-
-
Manage
AI cloud migration: Key steps to success
Migrating AI to the cloud demands strategic planning, system assessments, component modernization, data pipeline optimization and phased deployment. Find out what you need to know.
-
Planning AI infrastructure upgrades: Four steps for success
-
What businesses really need from an AI off switch
-
AI cybersecurity vs. AI cyberattacks: Who's winning?
-
AI & Emerging Tech Basics
-
Get Started
Planning AI infrastructure upgrades: Four steps for success
AI infrastructure upgrades require proactive planning. Steps include setting business goals, assessing existing infrastructure, and optimizing hardware, security and governance.
-
Get Started
Making space for spatial computing
Construct spatial computing programs through evidence, not hype. Use this roadmap to ensure that workflow selection is the starting point, not device selection.
-
Get Started
A guide to AI chip architectures
The diversity of today's AI processors can make their purpose, benefits and limitations confusing. This roundup can help businesses match their AI tasks to the right chip.
Multimedia
Vendor Resources
- The DevOps Roadmap for Security –eBook
- From Code to Production –Analyst Report
- Enterprise Networking Sees Age of SASE and Network as a Service –Research Content
-
News
View All -
AI Infrastructure
AI agent security: How reliable is enterprise AI testing?
Experts outline comprehensive testing practices before and after deployment of AI agents to prevent them from acting on their own beyond prescribed instructions.
-
AI Ethics & Governance
When AI agents go rogue: What enterprise leaders need to know
A recent wave of AI agents breaching test sandboxes and outside company systems is raising new governance and security questions for enterprise IT leaders deploying autonomous AI.
-
AI Technologies & Platforms
Zuckerberg's manifesto: Do Meta's promises and actions align?
Mark Zuckerberg's manifesto on the future of AI sounds promising, with democratized AI and superintelligent personal agents for everyone. But is this vision too good to be true?
AI & Emerging Tech Definitions
- What is automated machine learning (AutoML)?
- What is a data scientist? What do they do?
- What are AI agents? Types and examples
- What is an intelligent agent? Definition, use cases and benefits
- What is natural language processing (NLP)?
- Agentic AI explained: Key concepts and enterprise use cases
- What is a neural network?
- What is a robot? Definition, purpose, uses