AI Implementation

There is a question I hear from executives more than almost any other when the conversation turns to AI governance: Are we compliant? It is a reasonable question. It is also, increasingly, the wrong one. Compliance is necessary. No serious leader dismisses regulatory requirements or the legal frameworks that govern AI deployment. But compliance has become a ceiling when it needs to be a floor. Organizations that treat regulatory adherence as the destination for AI governance

When an AI system denies your loan, flags you as a flight risk, or filters your résumé before a human ever sees it, the instinct is to ask: Who is responsible for this? The honest answer is everyone — and therefore no one. That is not a scandal. It is a structure. And until we understand the structure, we will keep responding to AI failures the wrong way. The Question That Never Gets Answered On January 15, 2021, the entire Dutch cabinet resigned after an investigation reveal

Most executive conversations about AI risk start in the wrong place. They start with the model — its accuracy, its bias scores, its regulatory compliance status, its vendor validation documentation. They start with the technical question: Is the system performing within acceptable parameters? That question matters. But it is not the question that should be keeping executives up at night when it come to AI. The systems that have produced the most significant organizational and