Perspectives on AI strategy, governance, and the leadership decisions that will define the next decade of enterprise transformation.
Most enterprises are focused on the wrong thing — evaluating AI tools while underinvesting in the infrastructure that determines whether those tools will ever work at scale. The result is AI that impresses in demos and disappoints in production.
Read the full articleAI is the railroad of the 21st century. The track we lay now determines where it leads. Why governance standards must keep pace with agentic systems — before crisis forces the conversation.
Read moreBefore you can lead an AI strategy, you need to understand what AI can and cannot do. The gap between perception and reality is where most organizations get stuck.
Read moreGenAI is not magic. It is a set of powerful capabilities that, when matched to the right problems, can transform how organizations operate.
Read moreMost organizations are running AI experiments. Very few have connected them to strategy. That gap is where value is created — or lost.
Read moreThe shift from AI as a tool to AI as an actor is the most consequential technology transition since the internet. Most organizations are not ready.
Read moreThe best GenAI use cases are not invented in boardrooms. They are discovered in the workflows where time, cost, and risk are concentrated.
Read moreThe most sophisticated AI models in the world will fail if fed poor data. Data quality is not a technical problem to delegate — it is a strategic capability.
Read moreThe organizations that govern AI well do not move slower. They move faster — because clear guardrails create confidence to scale.
Read moreGenAI adoption is not primarily a technology challenge. It is a work, skills, and trust transformation. The organizations that understand this will win.
Read moreSix weeks teaching AI in Financial Services at Columbia Business School surfaced a clear truth: models are powerful, but the expert who wields them is the real differentiator.
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