Concept
An operating discipline of continuous human ownership of AI systems across their lifecycle, with named owners, decision rights and escalation authority to pause or retire AI behavior. Described in the episode as the complement that turns AI governance principles into enforceable decisions.
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2026-01-08 · Video on YouTube
AI governance doesn’t fail because of missing policies — it fails because no one owns the moment when things go wrong. In this M365.FM episode, the conversation reframes AI governance as AI stewardship, arguing that documents and dashboards alone don’t stop…
AI stewardship reframes AI governance as clear human ownership of AI intent, behavior and outcomes across the lifecycle. It is a continuous loop of intake, deployment, monitoring, escalation and retirement with named owners at every step. · From the episode: AI Stewardship for Microsoft 365 Governance
The show notes name poor data quality, privacy concerns, cybersecurity attacks and legal issues from bias in AI systems. Clear guidelines and regular audits help maintain ethical standards and trust. · From the episode: AI Stewardship for Microsoft 365 Governance
Use high-quality, well-documented data, increase transparency, involve diverse teams to reduce bias, stay up to date on AI regulations and foster a culture of responsibility in AI use. · From the episode: AI Stewardship for Microsoft 365 Governance
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Maintained by Mirko Peters (Microsoft MVP) · Last updated:
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