3 questions that tell you whether you’re actually governing AI

Effective AI governance depends on answering three runtime questions: who is acting on data, what resources and actions they can access, and whether the organization can maintain control while agents operate. The framework distinguishes human users, agents borrowing human permissions, and service agents with independent identities, arguing that each requires deliberately scoped least-privilege access and clear attribution. It recommends defining granular policies centrally across environmental, platform, and application layers, then enforcing them consistently at runtime rather than rebuilding controls within each app. Control should rely on deterministic rules that models cannot override, comprehensive audit trails, potential guardian agents to detect policy violations, protections that keep sensitive data within organizational boundaries, and spending limits tied to use cases and outcomes. Citing a survey in which few technology leaders rated their governance or production visibility as strong, the piece urges organizations to begin with a high-value workflow, assess it against the three questions, and select platforms that provide unified governance across apps, automations, and agents.

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