Executive Briefing · Boards

Board Guide to Enterprise AI

Enterprise AI should be governed as a portfolio of business capabilities and risks, not as a race to deploy the newest model.

Questions leaders should ask

  1. 1.Which business outcomes justify each material AI use case?
  2. 2.What data, systems and decisions can the AI access or influence?
  3. 3.Where is human review mandatory and who remains accountable?
  4. 4.How are quality, security, privacy, resilience and cost evaluated before and after deployment?
  5. 5.Can we change provider or disable the capability without breaking the business process?
  6. 6.Which AI uses would we be uncomfortable explaining to a customer, regulator or employee?

Practical next actions

  • • Create an inventory of material AI use cases and accountable owners.
  • • Classify use cases by consequence, autonomy and data sensitivity.
  • • Require evidence-based evaluation and approval before high-impact deployment.
  • • Track model/provider changes and define incident/stop procedures.
  • • Review portfolio value periodically and retire experiments that do not justify their cost or risk.

This briefing is general decision-support material, not legal, regulatory, financial or investment advice. Apply sector-specific obligations and evidence before acting.

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