AI governance

Control AI initiatives without shadow IT or unnecessary bureaucracy

AI governance defines roles, decision rights, risk routing, and gates so strong initiatives move faster and weak or risky ones stop before large spend.

What AI governance should include

Good AI governance does not route every initiative through one heavy committee. It routes initiatives by value, risk, and readiness.

Decision rights

Who can register an initiative, approve assessment, start delivery, accept risk, and close impact.

Stage gates

Clear checks before resource spend: data, security, process owner, product route, impact metric.

Risk routing

Different routes for self-service, pilots, strategic initiatives, sensitive data, and prohibited use cases.

Decision trail

Every continuation, return, stop, or exception is recorded so the portfolio does not become a black box.

Typical gates

Registration

There is a problem, initiator, short description, expected impact type, and business context.

Admission to assessment

No obvious duplicate, owner exists, base fields are complete, and the next analysis step is clear.

Admission to delivery

Product route is selected, similar initiatives checked, risks are not blocking, and priority is clear.

Impact validation

Actual metrics, data source, and decision on scaling, support, revision, or closure are available.

When governance is urgent

Risk

AI moves into shadow IT

Teams launch tools and agents without shared architecture, data rules, or access controls.

Money

Budgets grow faster than impact

Platforms, licenses, and pilots are purchased without a clear mechanism for selection and stopping.

Speed

Everything gets stuck in approvals

Criteria are not known in advance, so every initiative becomes a manual debate between functions.

Impact

Result is unclear

Initiatives reach demos but lack process owners, adoption metrics, and dates for impact validation.

Governance works best inside the AI operating model.It should be connected to the initiative portfolio and validated through the AI adoption diagnostic.

Need to set up AI governance?

Start with an audit of portfolio and gates: risks, decision rights, blockers, and first management rules.