Enterprise AI Strategy: Page

MIT study warns of major AI risk. Is governance keeping up?

AI experts warn of catastrophic AI risks, but governance lags, with security concerns driving policy while broader risks aren't being fully addressed.

By Kinza Yasar • June 16, 2026

Controlling AI sprawl: A practical guide for the C-suite

As AI tools proliferate across enterprise teams, leaders must ensure AI use isn't redundant or unsanctioned. Do you know all the AI tools your business uses?

By Zac Amos • June 4, 2026

Best practices for integrating third-party AI with local systems

Third-party AI components are increasingly common across industries and domains, but many businesses don't know how to effectively integrate them with their local systems.

By Stephen Bigelow • June 2, 2026

Is AI replacing jobs? How 17 job types feel the effects

AI has threatened various jobs since ChatGPT came out. New data shows where the threat is real and where it's imagined.

By Ben Lutkevich • June 1, 2026

How businesses can get ahead of potential AI deskilling

Will AI's efficiency gains of today come at the expense of workforce skill tomorrow? Hear one expert's thoughts on the impending AI deskilling epidemic and how to prevent it.

By Chris Tozzi • May 29, 2026

10 top AI knowledge management platforms for businesses

AI knowledge platforms use search and GenAI to surface and monetize enterprise information, but comparisons show wide variance in capabilities, integration, governance and scale.

By Kinza Yasar • May 29, 2026

How to apply FinOps to optimize agentic AI costs

FinOps gives businesses the operating model for visibility, accountability and value management. But traditional FinOps models will need to be reworked for agentic AI.

By Kashyap Kompella • May 29, 2026

AI FinOps requires a different approach than cloud

While AI's utility will continue to generate revenue for businesses, its cost grows with it. FinOps is a key strategy and governance tool that ensures AI delivers measurable ROI.

By Damon Garn • May 28, 2026

Agentic governance must go beyond traditional IT practice

Industry experts agree: Agentic AI requires new governance methods, not traditional IT playbooks. The current agentic governance gap threatens to derail enterprise AI adoption.

By Everett Bishop • May 27, 2026

How to choose the right IKMS in a fast-moving AI market

Poor platform selection is a leading cause of failed knowledge management system deployments. Product demos don't tell nearly enough. Five key factors can determine IKMS success.

By Kinza Yasar • May 27, 2026

8 AI costs leaders don’t always budget for but should

The hidden costs of enterprise AI often emerge after deployment, through stalled pilots, compliance burdens, workforce disruption, model upkeep and reputational risk.

By Kinza Yasar • May 21, 2026

Why AI pilots fail and how to move them into production

While AI pilots thrive in sandboxes, production demands clear ownership, robust data infrastructure, failure testing and runtime monitoring throughout the system's lifecycle.

By Donald Farmer • May 16, 2026

Educating the future AI-savvy human workforce

As the need for skilled AI workers approaches desperation levels for many businesses, unique and more personalized teaching methods are preparing tomorrow's AI workers.

By Liz Hughes • May 15, 2026

AI drones undertake high-risk jobs along the supply chain

From power line and bridge inspections to remote and heavy cargo deliveries, autonomous AI drones are becoming the supply chain's version of air traffic controllers.

By Chuck Martin • May 12, 2026

GenAI and synthetic data: What can go wrong in business?

GenAI's ability to improve everything it touches, including synthetic data, is undeniable, but when misused, simulated data can amplify bias, taint data and compromise security.

By Stephen Bigelow • May 7, 2026

Build and organize an effective machine learning team

Putting together an ML team requires a business understand why it needs one and the core roles involved in making all aspects of the machine learning process work.

By Cortnie Abercrombie, Stephen Bigelow • April 28, 2026

How to build AI skills across your workforce

AI skills are no longer an optional investment. Business leaders who know how to build AI skills throughout their organizations can unlock AI's full potential.

By Kashyap Kompella • April 27, 2026

How businesses use KPIs to measure AI’s performance

Business decision-makers under heavy pressure to justify the value of their AI projects look to key performance indicators for salvation. KPIs reveal AI's efficiency and ROI.

By John Burke , Jerald Murphy • April 24, 2026

How to start a career in AI: Advice from experts

AI careers don't follow one path. As AI becomes part of everyday work, more professionals are entering the field by building on what they already do and focusing on real results.

By Liz Hughes • April 20, 2026

Business vs. provider: AI software restrictions to know

How much control do businesses have over the use of AI platforms they buy? Vendor acceptable use contracts and policies can determine an AI deployment's success or failure.

By Stephen Bigelow • April 20, 2026

Citizen developers are redefining enterprise AI development

Generative AI is enabling nontechnical business users to build enterprise software, accelerating innovation while creating new risks around governance, security and control.

By Kinza Yasar • April 17, 2026

GenAI in accounting: Chat BDO’s ride from pilot to production

Accounting and advisory firm BDO built and deployed a proprietary AI platform so its tax and audit pros could automate routine tasks and significantly increase client-facing time.

By Kathleen Richards • April 16, 2026

4 strategic approaches to effective shadow AI governance

Shadow AI is a technological risk and a governance challenge. Organizations must combine structured frameworks, continuous visibility and education to control these risks.

By Nihad Hassan • April 15, 2026

GenAI data center infrastructure reshapes business processes

Building and retrofitting data centers to support GenAI is not a matter of IF but WHEN, so the game plan must include power needs, grid connectivity, model training and permitting.

By George Lawton • April 10, 2026

GenAI in product manufacturing cuts costs but adds risks

In product design and manufacturing, GenAI systems are consolidating supplier data, improving processes and cutting significant software costs -- yet they raise unique concerns.

By Patrick Thibodeau • April 7, 2026