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AI Governance Framework

Building an AI Governance Framework

An AI governance framework is the set of policies, processes, and roles that ensure your team uses AI responsibly and stays compliant. Here's how to build one that's lightweight enough for a small team to actually use.

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Frequently Asked Questions

What's included in an AI governance framework?
At minimum: an acceptable use policy, a list of approved tools, a process for approving new tools, a data classification guide (what can go into which tools), and an incident reporting path. Larger teams add a risk register and regular audits.
Do small teams really need a formal governance framework?
Yes — but 'formal' doesn't mean 'bureaucratic'. A one-page policy, a shared spreadsheet of approved tools, and a named point of contact is a governance framework. The goal is consistency, not paperwork.
Who should own AI governance in a small team?
In most small teams, the founder, CTO, or ops lead owns it. The key is having one named person, not a committee. Assign it explicitly — ungoverned AI tools are how most small teams end up with data incidents.
How does AI governance relate to GDPR or the EU AI Act?
Both regulations require you to have governance processes in place — documented policies, records of AI systems in use, and evidence of human oversight. A well-structured governance framework is your compliance evidence.