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Glossary · Strategy

What is AI Governance?

Definition

AI governance is the set of policies, roles and processes an organization uses to decide how AI may be used, manage its risks and stay accountable for its outcomes. It typically covers approved tools, data handling rules, review of new use cases, human oversight, testing, vendor assessment, incident response and compliance. Frameworks such as the NIST AI Risk Management Framework provide structure.

Why it matters for your business

Employees are likely already using AI tools, with or without permission, so the real choice is between managed and unmanaged use. Governance does not need to be heavy for a small or mid-sized company: a short acceptable use policy, a list of approved tools, rules for client and personal data, a simple review for new use cases and a named owner go a long way. It matters more in regulated areas such as hiring, lending, insurance and healthcare, where rules like New York City's Local Law 144 already require bias audits for some automated hiring tools.

Example

A 120-person staffing firm adopts a two-page AI policy. It approves one enterprise AI assistant, bans candidate data in personal AI accounts, requires a manager's sign-off and a bias review before any AI tool scores candidates, and names the operations director as owner. New AI tools go through a short checklist covering data handling, vendor terms and who reviews outputs.

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Next steps

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