AI Governance Control Checklist

Critically test the quality, consistency and readiness of AI Governance Control Checklist. The objective is to remove ambiguity around board/advisor rhythm, decision records and governance basics, give the founder a decision-ready output, and make it clear whether the venture should progress, repeat the task with stronger evidence, escalate to expert support, or move into a linked stage.

Bertie or a programme manager assigns AI Governance Control Checklist when the venture needs a decision-ready output for this group. Typical triggers include group-gate reviews, evidence gaps identified by the co-pilot or founder request.

company documents; data flows; contracts; security posture; finance or compliance records; existing artefact to review; specific context for board/advisor rhythm, decision records and governance basics.

1. 1Gather AI Governance Artefacts and Decision Recordsexpand_more

   Compile all existing documentation relating to AI model deployment, decision logs, oversight frameworks, board schedules, and advisor engagement terms. Collate current policy documents, data usage registers, and technical risk assessments into a centralised inventory.

   Objective

   Completing this action creates a comprehensive, auditable inventory of all existing AI governance materials and oversight mechanisms. It establishes the baseline evidence required to evaluate the venture's operational compliance and risk posture accurately.

   What's expected

   The founder must present a structured inventory containing current AI policies, board minutes documenting AI decisions, risk logs, and data processing agreements. Every document must be version-controlled, dated, and explicitly mapped to active AI models or operational workflows.

   Consultant stress-test · 5 questions

   1. 1.What specific AI decision logs or registry entries prove that board oversight of algorithmic deployment is operational rather than nominal?
   2. 2.How have you verified that your current data processing agreements explicitly cover third-party AI model training and data ingestion risks?
   3. 3.Which key AI governance policies are currently missing, outdated, or reliant on informal verbal agreements with advisors?
   4. 4.Where is the objective evidence that ethics and risk considerations are recorded prior to model deployment rather than retrospectively?
   5. 5.How does this collected inventory reflect actual developer practices and data flows across the current venture architecture?

   Open action arrow_forward
2. 2Audit Board Rhythm and Core Governance Basicsexpand_more
3. 3Benchmark Controls Against Regulatory Standards and DNAexpand_more
4. 4Expose Governance Contradictions and Material Risksexpand_more
5. 5Prioritise Remediation Actions and Governance Experimentsexpand_more
6. 6Record Governance Verdict and Next Progression Decisionexpand_more

• A data-room asset titled AI Governance Control Checklist
• A review note with a verdict, evidence gaps, risks, recommended corrections and a clear continue / repeat / escalate decision
• It should update the venture DNA with specific evidence or decisions about board/advisor rhythm, decision records and governance basics, create a visible milestone in the founder journey, and generate one or more recommended next tasks

A mentor or evaluator can review the output at the group gate. Programme managers can require an advisor checkpoint before Bertie moves the venture forward.

Draft your output and let Bertie review it