Most AI policies are theater — long enough to look serious, vague enough to mean nothing. A useful policy is short, specific, and enforceable. Here's the template.
An AI policy that nobody reads or enforces is worse than no policy — it creates the appearance of governance without the substance. The template below is the minimum a startup needs to actually govern its AI use.
The Conduct Rule: Specific and Enforceable
A policy is a law of conduct — and a law that can't be enforced isn't a law. The policy has to name what's allowed, what's not, who's responsible, and what happens when it's violated. Vague principles don't govern; specific rules do.
- What's allowed, in plain language.
- What's not allowed, with reasons.
- Who owns the policy and the violations.
- What happens when the policy is violated.
The Template, Section by Section
- **Scope.** Which AI tools and uses the policy covers.
- **Allowed uses.** The cases that don't need review.
- **Restricted uses.** The cases that need review, and by whom.
- **Prohibited uses.** The cases that are never allowed.
- **Data handling.** What may and may not go into AI tools.
- **Ownership.** Who owns the policy, the review process, and the violations.
- **Review cadence.** When the policy is revisited.
Process: Keep It Short
A one-page policy that's read and enforced beats a twenty-page policy that isn't. The process discipline is to keep the policy short enough that every new hire reads it on day one — and specific enough that a violation is unambiguous.
What to Refuse
- A policy longer than a page that nobody reads.
- Principles without rules ("we use AI responsibly" is not a policy).
- A policy with no owner.
- A policy that's never reviewed.
Conclusion
A useful AI policy is short, specific, and enforceable — scope, allowed, restricted, prohibited, data handling, ownership, cadence. The policy that's read and enforced governs; the policy that isn't is theater.
About FACTA
FACTA helps startups and growth-stage teams turn AI into production systems that keep running — not demos that impress once.
We design the architecture around the parts that actually break under real usage: tooling you own, credentials you control, failover, cost controls, observability. The boring infrastructure that keeps a system alive after launch.
Led by Matías Baglieri and Carolina Fogliato, we focus on one thing:
AI leadership that builds. Not just advises.
Ask us for the one-page template.
We'll help you fill it in for your startup. See AI governance for startups for the frame around it.
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