Why AI governance won't fix decision governance
Model policies and AI-use guidelines protect against misuse. They do not preserve reasoning.
15 Apr 2026 · 9 min read
Most enterprises now have an AI usage policy. Few have a decision governance policy. The two are often confused, and they should not be.
What AI governance handles
AI governance covers model selection, data handling, allowed use cases, prompt logging, output review, and vendor risk. It is the discipline of preventing harm from the tools.
What it does not handle
AI governance does not preserve why a decision was made. It does not capture dissent. It does not track conditions. It does not maintain a permanent ID for a strategic commitment.
A perfectly governed copilot can produce a perfectly ungoverned decision.
Why this matters in practice
The output of any AI session — a draft memo, a summarised analysis, a structured recommendation — is an input to a decision, not the decision itself. If the only artefact that survives is the chat thread, the organisation has substituted one kind of fragmentation (folders, decks, emails) for another (threads, sessions, prompts).
Decision governance is the layer above. It owns the verdict, the rationale, the dissent, the conditions, and the review.