Enterprise AI Strategy: Page

Why multimodal AI is reshaping enterprise intelligence

Multimodal AI can transform industries by combining text, images, video and audio to solve complex problems single-modality systems often can't address.

By Stephen Catanzano • March 4, 2026

How GenAI deployments are redefining everyday work routines

GenAI deployments are making dramatic strides in boosting employee productivity, strategic analysis, software development cycles and customer service -- but not without risks.

By Stephen Bigelow • March 3, 2026

How CIOs should architect trust in AI -- not just govern it

When designing trustworthy enterprise AI applications, platform architecture, not policy alone, is the best way to minimize long-term risk and ensure compliance and sustainability.

By Varun Raj • Feb. 27, 2026

Is your business ready for an agentic AI team?

The race is on to implement agentic AI teams. But can your business successfully deploy and manage them before taking this next step in enterprise automation?

By Mary Pratt • Feb. 27, 2026

What Nvidia’s $78B quarter tells you about enterprise AI

Nvidia's latest earnings reveal more than impressive revenue figures. They highlight the accelerating adoption of enterprise AI and the growing pressure on infrastructure capacity.

By Mike Leone • Feb. 26, 2026

From security to trust: How AI is transforming the CISO’s job

Modern security officers must manage AI risks, safeguard enterprise data and ensure AI systems operate securely, expanding their role beyond traditional cybersecurity.

By Kinza Yasar • Feb. 26, 2026

Is Citrini Research’s dark AI future a given?

Agentic AI might look good now, but it could have negative repercussions on the economy. So says a controversial thought experiment from Citrini Research.

By Jennifer English • Feb. 26, 2026

How businesses can close the AI engineering gap

Amid growing concerns that AI is replacing jobs in several sectors, demand for AI engineers is surging as businesses employ several methods to overcome a severe skills shortage.

By Sean Kerner • Feb. 25, 2026

How agentic AI is changing work, strategy and competitiveness

AI agents are transforming work, business strategy and global competitiveness by enabling autonomous workflows, innovation and value creation in enterprises.

By Kishan Kumar • Feb. 25, 2026

Battle of the bots: Best GenAI chatbots for business

Businesses are deploying multiple GenAI tools to support productivity. Success requires choosing the right tools for the right use case and keeping a close eye on the outcomes.

By Bridget Botelho • Feb. 25, 2026

Reproducibility: Is your AI project doomed?

AI governance focuses on mitigating risks from generative AI's unpredictability. Key strategies include reproducibility, explainability and comprehensive controls.

By Guy Pearce • Feb. 24, 2026

7 practical tips for agentic AI cost optimization

Building an agentic AI cost-management framework requires unique considerations and details. These tips can help businesses get started.

By Kashyap Kompella • Feb. 24, 2026

The AI bias playbook: Mitigation strategies for CIOs

From prioritizing data management to having a governance-first mindset, the C-suite can use the AI bias mitigation strategies in this playbook to limit AI bias risk.

By Olivia Wisbey • Feb. 23, 2026

The ethics that make human-AI agent collaboration work

Skepticism and distrust are common with new technology. Executives must develop a culture of trust with AI to ensure effective human-AI agent collaboration.

By Zac Amos • Feb. 23, 2026

The role of AI and humanics in training healthcare professionals

The integration of AI and humanics in education is shaping the future of healthcare, with an emphasis on empathy, innovation and whole-person care.

By Michael Avaltroni • Feb. 20, 2026

Optimize AI models to generate more bang for your buck

AI models must be fully optimized to align with business goals, provide valuable insights and produce positive ROI. Check out these proven, common sense model optimization methods.

By Chris Tozzi • Feb. 18, 2026

Best practices for building scalable AI infrastructure

Scalability is vital for AI platforms. These 10 best practices can help businesses build scalable infrastructure that supports AI workloads and adapts to fluctuating demands.

By Stephen Bigelow • Feb. 13, 2026

AI deployments gone wrong: The fallout and lessons learned

AI's deployment landscape is littered with good intentions, crushed projects and unintended consequences due to misaligned business goals, mistrust in AI and weak management.

By Kathleen Richards • Feb. 12, 2026

How business leaders can prepare for quantum-AI integration

AI completely changed the way we work, and quantum computing has the potential to upend our work completely. How can these technologies integrate to achieve further innovation?

By Kerry Doyle • Feb. 12, 2026

How to navigate data sovereignty for AI compliance

As AI systems consume data for training and decision-making, businesses must navigate complex regulations, geopolitical boundaries and vendor risks.

By Donald Farmer • Feb. 9, 2026

How watermarking AI content benefits businesses

AI watermarking is being used to identify deepfakes, enhance transparency and build trust in AI-generated content, but reliability issues and false positives present challenges.

By Sean Kerner • Feb. 6, 2026

5 skills needed to become a prompt engineer

With the rise of generative AI, prompt engineering has emerged as a new profession. Desired skills include refining prompts, analyzing AI output and ensuring alignment with business goals.

By Stephen Bigelow • Feb. 6, 2026

Top AI KPIs that business leaders need to know

AI-specific KPIs can indicate model performance, customer satisfaction and overall business value. Explore these 25 AI KPIs to elevate the management of any AI initiative.

By Stephen Bigelow • Feb. 4, 2026

The operational reality of enterprise AI

AI models are now commodities. It's enterprise challenges like security, scalability and integration are the real barriers to successful deployment.

By Mike Leone • Feb. 2, 2026

What to know about synthetic data as a business advantage

Synthetic data mimics real data without sensitive information. It offers cost-effective options and competitive advantages for AI training, software testing and data monetization.

By Stephen Bigelow • Jan. 31, 2026