AI Glossary
Governance (AI)
The framework of policies, roles, and processes that control how AI is developed, deployed, and monitored in an organization. Good governance reduces risk and builds trust.
Understanding Governance (AI)
AI governance provides the guardrails that let businesses adopt AI confidently. It covers who can deploy AI, what data it can access, how decisions are monitored, and what happens when things go wrong.
A practical governance framework includes an AI use-case registry, data classification policies, model evaluation criteria, deployment checklists, monitoring dashboards, and incident response procedures.
Governance isn't bureaucracy — it's risk management. Organizations with clear AI governance adopt faster because teams have confidence in what's allowed, and leadership has visibility into how AI is being used across the organization.
Governance (AI) in Canada
The Treasury Board of Canada has published a Directive on Automated Decision-Making that requires federal agencies (and influences private sector best practices) to assess and document AI-driven decisions.
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Frequently Asked Questions
At minimum: an AI use-case registry, data handling policies, risk assessment criteria, human oversight requirements, monitoring procedures, and an incident response plan.
Typically a cross-functional team including IT/engineering, legal/compliance, and business leadership. Some organizations create a dedicated AI ethics or governance committee.
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