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The set of policies, processes, roles, and controls an organization puts in place to ensure its AI systems are used responsibly, legally, and in line with its values. AI governance covers the full lifecycle: how AI tools are evaluated and approved, how data is handled, how outputs are reviewed, how incidents are tracked, and how the program is updated over time. For small teams, AI governance is not a compliance checkbox — it is operational infrastructure that reduces risk, builds trust with customers, and prepares the organization for regulation that is coming whether or not it has arrived yet.
Why this matters for your team
AI governance is infrastructure, not bureaucracy. Organizations that build governance habits now — a tool inventory, an approval process, an incident log — will adapt to regulation far faster than those scrambling to comply after the fact.
A 20-person company implements AI governance by: maintaining an AI tool inventory, requiring approval for new tools, running quarterly vendor reviews, and keeping an incident log — all without a dedicated compliance team.