AI Governance

Give AI decisions an accountable owner.

Design policies, decision rights and oversight routines that fit the way AI is used.

Decision rights: Design policies, decision rights and oversight routines that fit the way AI is used.
Policy controls: Define the evidence, interfaces and accountable owners for this part of the work.
Human oversight: Review findings against agreed decision criteria and record unresolved limitations.

Proposed engagement framework; scope and evidence requirements are agreed for the workflow.

Explore the engagement scope

Design policies, decision rights and oversight routines that fit the way AI is used. Begin with an agreed workflow, accountable owner and representative evidence. The engagement defines its coverage, dependencies and decision criteria before work starts.

AI Governance Operating System

Make AI oversight part of daily operations. Connect inventories, accountable owners, change decisions and evidence into a workable governance process.

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Supporting capabilities

AI governance and regulatory readiness

Connect inventory, accountability, oversight and evidence to AI operating decisions.

A little more clarity

Questions worth asking.

Start with the questions that shape a better decision.

What does AI Governance cover?

Design policies, decision rights and oversight routines that fit the way AI is used. Indicative focus areas include decision rights, policy controls, human oversight.

What is needed to scope AI Governance?

What decision does AI Governance support?

Give AI decisions an accountable owner. Findings and indicative outputs apply to the agreed scope. Your accountable owner retains deployment, investment and risk decisions.

Who owns the decision and its oversight?

Bring the workflow, the constraints and the evidence you already have.

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