Data
Provenance, quality, privacy, access and permitted use.
AI InventAI Readiness Diagnostic For Boards
Defensible AI oversight without becoming AI engineers.
Boards need clear visibility, decision rights and evidence that AI risk is understood, governed and tied to enterprise outcomes.
The blind spot
The risk is not only AI failure. It is invisible AI activity.
Shadow AI, fragmented pilots and unclear ownership can place material decisions outside established oversight.
02
Four domains every board should be able to question.
Model
Fitness, accuracy, bias, robustness and explainability.
Operational
Ownership, controls, monitoring, incidents and safe fallback.
Reputational
Impacts on customers, employees, rights and stakeholder trust.
03
Seven questions to bring oversight into the boardroom.
Where is AI used?
Maintain a current enterprise use-case inventory.
What can it decide?
Define autonomy and retained human authority.
Who is accountable?
Name owners, reviewers and escalation paths.
What evidence supports trust?
Demand evaluation, impact and control evidence.
How are incidents handled?
Set pause, appeal and recovery mechanisms.
How is value measured?
Connect use cases to approved outcomes.
What changes require review?
Reassess material changes in data, models and purpose.
Strategy · Governance · Delivery