Enterprise AI Has A Readiness Problem, Not A Model Problem

InnovationEnterprise AI Has A Readiness Problem, Not A Model ProblemByShreyas Nair,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 27, 2026, 12:30pm EDTShreyas Nair is an AI venture founder and founder of Wordsworth AI. gettyI recently spoke with a friend at a large company who had just finished another AI pilot review. The pilot went well. The tool summarized documents, drafted follow-ups, extracted action items and made the old workflow seem painfully slow by comparison.However, the mood in the room shifted when the team spoke about a full-blown production rollout. Data was scattered across too many places; no one was sure which system was the real source of truth; legal wanted an approval step; IT wanted access controls; the business team wanted things to move faster; and the people who knew about the exceptions weren't even in the room.To me, this is the real story of enterprise AI right now.Headlines suggest that AI adoption is already a done deal. Accenture is rolling out Microsoft 365 Copilot to about 743,000 employees after a big internal pilot. General Mills has used AI to analyze thousands of daily shipments and reportedly saved over $20 million in transportation costs. Gartner, Inc. predicted that agentic AI would appear in one-third of enterprise software and services by 2028. On paper, AI is now mainstream in business.Inside companies, things are much messier. The demos work well and the pilots are real. Employees are actually using these tools, and that matters. However, just using AI isn't the same as real transformation. A company might have thousands of people summarizing meetings, drafting emails and writing code with AI but still have the same broken workflows underneath.This is where I think the conversation should go. Enterprises don't have a model problem anymore; they have a read...