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.
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?
- GDPR requires records of processing activities (Article 30), and the EU AI Act requires risk management, documentation and human oversight for high-risk systems. A well-structured governance framework gives you that evidence in one place.