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Run the free AI compliance checkup to get a practical readiness score, likely risk bucket, missing controls and next actions.
Why AI compliance matters for startups
Start with a lightweight AI compliance baseline that investors, customers and partners can understand. The practical starting point is to list AI systems, identify who is affected, document data use, and decide which workflows need formal review before launch or scaling.
Common AI use cases to inventory
- prototype AI features
- internal productivity tools
- customer-facing chatbot or agent
- AI-generated marketing or support content
- automated document processing
- outsourced or API-based model use
Higher-risk signals to watch
- no one owns AI compliance or vendor review
- sensitive customer data enters AI tools
- the product is sold to EU customers or regulated sectors
- the startup claims high accuracy but lacks testing evidence
These signals do not automatically decide the legal classification. They tell the team when to escalate, gather evidence and use a formal risk assessment.
Controls to put in place this month
- Create a one-page AI inventory and owner map.
- Adopt an employee AI acceptable-use policy.
- Review vendors before customer data is used.
- Document intended use, limitations and human review.
- Set a monthly AI governance review calendar.
Suggested review path
For this industry, start with the use-case checker, then use the risk matrix to prioritise systems, and finally document the controls in your AI inventory.
Worked example: investor due diligence
A startup using AI in its product may be asked for evidence before enterprise customers, investors or partners sign. A lightweight governance pack can reduce friction without building a large compliance department.
Evidence to keep
- One-page AI inventory and owner list.
- Approved tools and restricted-data policy.
- Vendor/model documentation for core AI dependencies.
- Risk decisions, open issues and next-review dates.
30-day improvement plan
- Create a minimum viable AI policy for the team.
- Record all AI features, vendors and internal workflows.
- Flag any HR, credit, health, safety or child-facing use cases.
- Prepare a simple customer/investor AI governance summary.
FAQ
Is AI in startups always high-risk?
No. Risk depends on the specific use case, affected people, data, role and deployment context.
What should I document first?
Start with an AI inventory entry, owner, intended use, data categories, affected users, vendor/model documentation and review date.
Can this replace legal advice?
No. It is a practical readiness guide, not legal advice.
Sources and review method
This page is written as general business guidance, not legal advice. It is maintained from official AI Act materials, European Commission / AI Office updates, the NIST AI Risk Management Framework and practical AI governance controls.