Not the technology, but the accountability architecture, explainability requirements, data foundations, and human-oversight model that determine whether AI can be deployed responsibly, commercially, and at scale in regulated organisations.
Not a compliance exercise, a policy document, or a vendor assessment template. The organisational architecture that determines how AI-driven decisions are made, attributed, reviewed, and held accountable.
The academic AI governance debate — bias, fairness, societal impact — is largely inapplicable to the immediate, more consequential governance challenges facing regulated commercial organisations: who is accountable when an AI-driven recommendation is wrong, how a next-best-action decision is explained to a regulator, and what data foundation the model is legally and ethically permitted to use.