AI Governance

AI Governance Roles and Ownership

2 min read · AI Governance · 2026

AI Governance Roles and Ownership

AI governance is not a policy PDF in a drawer. It is clear ownership for how workflows change, what data they touch, and who answers when something goes wrong.

RACI (typical mid-size team)

Activity Executive sponsor Process owner IT Legal / compliance Ops lead
Approve new customer-facing workflow A R C C C
Maintain context / policy packs I C R A C
Integrations and secrets I C A/R C I
Eval set and release gate I A R C C
Incident review I C R A R

R = responsible, A = accountable, C = consulted, I = informed

Minimum viable governance

  1. One executive sponsor for AI operating priorities—not every tool decision.
  2. Process owner per workflow who can say no to scope creep.
  3. IT owns integrations, logging, and access; not business wording of prompts alone.
  4. Legal owns policy context and prohibited uses—not daily prompt tweaks.

Anti-patterns

  • “Everyone owns AI” → no one owns incidents.
  • IT writes all prompts without process owners → misaligned outcomes.
  • Legal only engaged after a breach → governance as cleanup.
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