Microsoft, Google, and ServiceNow all want you to believe agentic AI governance is a platform feature. It is not. It is a discipline that lives one layer above platform selection. The vendor selling you the agents cannot also be the neutral arbiter of how those agents behave, what they access, or whose data they touch. […]
Agentic AI Governance Cannot Be Solved by the Platform Selling You the Agents Read More »
I have been telling clients for two years that the gap between AI investment and AI deployment is the actual business problem. Last week, OpenAI bet four billion dollars on the same thesis. That is not a coincidence. That is the largest enterprise AI company in the world arriving at the same conclusion the AI
AI Readiness Assessment Gap: Why OpenAI Just Spent $4 Billion to Fix It Read More »
Most enterprises are still asking the wrong question. They sit down to debate build vs buy AI as if the answer determines their strategy. It does not. By the time the framework hits the whiteboard, the company has already collected six pilots, three vendor contracts, two off-the-shelf agents, and a custom-built copilot from the data
Build vs Buy vs Orchestrate: The New AI Decision Framework Read More »
A new report has the data community talking. The Fivetran 2026 Agentic AI Readiness Index says 60 percent of enterprises are investing millions in agentic AI, but only 15 percent have the data foundation to run it. That gap is real. But framing it as a data readiness problem misses the deeper issue. Agentic AI
Agentic AI Readiness Is Not Data Readiness: What the 2026 Fivetran Index Misses Read More »
Most enterprises do not have an AI model problem. They have an AI pilot to production problem. The demos work. The early metrics impress. The CFO signs off on a roll-out budget. Then nothing scales. Six months later, the pilot is still running in the same business unit, the same three power users are getting
AI Pilot to Production: The Missing Middle Layer Most Companies Skip Read More »
Most AI investments fail before the first model is deployed. Not because the technology does not work, but because the organization is not ready to put it to work. Before signing the next contract, run through this AI readiness checklist. Fifteen questions, organized around five readiness dimensions, designed to surface the gaps that matter before
AI Readiness Checklist: 15 Questions to Ask Before Your Next AI Investment Read More »
Most companies have an AI adoption problem they keep mistaking for an AI strategy problem. They add more tools. They launch more pilots. The dashboards multiply. The results do not. The gap between AI activity and AI impact keeps widening, and the cause is rarely the model, the data, or the budget. It is enterprise
The Enterprise AI Coordination Crisis and How to Fix It Read More »
Most enterprises have an AI agent pilot. Almost none have an AI implementation roadmap that survives contact with production. That is the 10 percent problem, and it is where the 2026 enterprise AI story is actually being told. Pilots are running everywhere. Scaling is not. Here is the stat that should stop your next leadership
The 10% Problem: What an AI Implementation Roadmap Actually Solves Read More »
Most CTOs I talk to cannot tell you how many AI tools their teams actually use. Not within an order of magnitude. That is the starting point, because AI tool sprawl is the quiet drag on enterprise productivity that nobody owns and nobody is measuring. The pattern repeats. A department head spins up a copilot
AI Tool Sprawl: When More Tools Make You Less Productive Read More »
Enterprise AI governance is broken in most mid-market companies. Not because they are ignoring it. Because they are treating it as a compliance checkbox instead of a strategic function. The result is predictable. Organizations buy AI tools faster than they can govern them. Teams deploy agents without guardrails. And when something goes wrong, the response
Enterprise AI Governance: What Mid-Market Leaders Need to Know Read More »