Here is the fastest way to lose a board on AI governance: walk in with a slide deck about maturity models, framework layers, and compliance mapping. Here is the fastest way to win them: walk in with a capital investment proposal. Your board already knows how to evaluate capital investments. They’ve been doing it for…
The organizations that deploy AI fastest share one counterintuitive trait: they spend time before they build anything understanding exactly where they are. Not where they want to be. Not where the frameworks say they should be. Where they actually are — with their actual data, their actual decision-making culture, and their actual governance capability. That…
The governance team looked great on paper. A representative from IT. One from Legal. One from Finance. Data Science. Operations. HR. A six-person cross-functional team chartered to oversee AI governance. After three months, the CEO asked for a progress update. The team had met eight times. They’d produced a stakeholder map, a responsibility matrix, and…
A $400M logistics company asked me to review their AI governance. They had a 47-page governance policy. Board-approved AI principles. A risk classification matrix. Ethics guidelines. Compliance mapping. Beautiful documents. Sitting in SharePoint. Untouched since approval. When I asked how an AI initiative actually moves from pilot to production, the answer was: “It depends on…
Before you build AI governance, you need to know where you’re starting from. An AI governance maturity assessment reveals exactly that. Most organizations skip this step. They jump straight to implementing frameworks, writing policies, or hiring consultants—without understanding their current state. It’s like starting a road trip without knowing your current location. The result? You…
