AI Governance Audit — Process

From conversation
to structured decision-making.

A five-step engagement designed to move organizations from fragmented AI usage to a clear, accountable operational view.

Each step builds on the previous one — no generic checklists, no abstract maturity scoring.

Discovery — Establish context.

01
Map current AI usage across teams and tools.
02
Clarify organizational context, roles and operating model.
03
Surface objectives and expectations for governance visibility.

Assessment — Read the operational reality.

01
Governance review — current frame, policies, ownership.
02
Risk review — exposure surfaces and informal mitigations.
03
Process review — how AI enters daily workflows.
04
Documentation review — what exists, what is missing.

Analysis — Transform observations into structured findings.

01
Findings across usage, responsibility and risk dimensions.
02
Maturity observations grounded in operational evidence.
03
Governance gaps prioritized by operational impact.

Deliverables — Produce the audit artifacts.

01
Executive summary written for leadership review.
02
Findings report with structured observations.
03
Recommendations prioritized by operational relevance.
04
Implementation roadmap covering the next operational quarter.

Strategic Review — Convert clarity into decisions.

01
Structured discussion of findings with leadership.
02
Priority alignment across operational and governance teams.
03
Definition of immediate next actions and ownership.

Book an Audit Discussion.

Begin with the AI Governance Intake. It is the structured way to qualify scope and prepare a meaningful first conversation.

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