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Global Compliance · Expanded Global Compliance

AI Governance Assurance

Keep an inventory of the customer's AI systems and agents: model and provider dependencies, risk assessments, use cases, approvals, policy obligations, human oversight,…

Demonstration: Meridian Freight Group (fictional) · Freight and logistics. Fictional data and a scripted answer.

The situation

Organisation
Meridian Freight Group (fictional)
Who is asking
Head of AI governance
Industry
Freight and logistics
What happened
Teams have started using AI tools, and the governance committee wants to know which systems meet the company's own AI policy.

The question asked

Which AI systems in use fall short of our AI policy, and how many decisions do they influence?

What it reads, and who can see the result

  • AI system register registerSystems with owner, purpose and assessment status.
  • AI policy documentThe company's requirements.
Reads
The AI register entries and the policy.
Does not read
Model internals or the data processed.
Permission
The AI governance office's register access.
Who sees it
The head of AI governance and the AI committee.

Try it

Review each flagged record: confirm it or dismiss it. The totals and the answer below follow your decisions.

SystemUsed forOwnerDecisions a monthFindingDecision
Route optimiserPlanning delivery routesOperations18,000MatchedNone needed
CV screening assistantShortlisting applicantsNone recorded1,400No owner, and it influences hiring decisions without human review
Invoice readerExtracting invoice fieldsFinance9,200MatchedNone needed
Customer chat assistantAnswering customer questionsCustomer service22,000No impact assessment; the policy requires one for customer-facing use
Fraud scoring modelScoring payment riskFinance6,400Human review required by policy is not evidenced
Meeting summariserSummarising internal meetingsIT3,000MatchedNone needed
Flagged
3 of 6 · 29,800
Policy gap
0 · 0
Compliant
0 · 0
Undecided
3 · 29,800

The answer

Simulated answer. Written for this fictional case, not produced by a live model. Only the figures in it are computed, from what you decided above.

3 of 6 AI systems fall short of the policy, influencing 29,800 decisions a month.

Three gaps appear: a system with no owner that influences hiring, a customer-facing assistant with no impact assessment, and a scoring model whose human review cannot be evidenced [S1][S2]. The first is the most serious: a hiring decision with no owner and no review.

You have recorded 0 as policy gaps (0 decisions a month) and 0 as compliant (0); 3 are undecided.

Relies on: S1 · AI system registerS2 · AI policy v1

Review and approval

The head of AI governance decides. Approving sends remediation requests to the system owners for the gaps recorded. It does not switch any system off.

Not ready to approve. 3 flagged systems are still undecided. Confirm or dismiss each one first.

In the product this is a different person with the right permission. Here you play that role to see the rule.

What it produces

registerDraft, not approved

AI policy gap register

  • Gaps: 0 systems, 0 decisions a month.
  • Compliant: 0 systems.

Limits of this example

  • Checks the register against the policy; it does not test how a model behaves.
  • A system missing from the register is invisible to this review.
  • This is a scripted demonstration on fictional data. No model was called and no real organisation, person or result is shown.