AI policy template for European organisations
A practical, free AI policy template aligned with GDPR and the EU AI Act. Written for executives, DPOs and security officers who want to deploy AI responsibly without getting lost in legal jargon.
Below you'll find the full outline with ten standard sections, an implementation plan, and a download button to save it as PDF.
Why every organisation needs an AI policy
AI is no longer a future concept — employees use it daily. Without a policy you face three risks: data leaks via public tools, non-compliance with GDPR or the EU AI Act, and loss of grip on decisions made by models. A good AI policy isn't bureaucracy — it's a precondition for responsible acceleration.
Assign accountability. An AI policy makes explicit who is responsible for deploying, assessing and monitoring AI systems. Without that ownership, risks tend to get lost between IT, HR and the board.
GDPR and EU AI Act compliance. Both frameworks expect organisations to demonstrate measures around data processing, transparency and risk classification. A documented policy is your key evidence during audits and with regulators.
Clear guardrails for employees. Many employees already use public AI tools, often without the organisation knowing what data leaves. An AI policy prevents shadow AI by clarifying what is and isn't allowed.
Customer and partner trust. Clients increasingly ask for an AI policy before sharing data. A professional policy accelerates commercial and public procurement.
The 10 sections of a solid AI policy
Below are the sections every professional AI policy should include. Adopt them in this order and complete them with the specific roles, vendors and processes of your organisation.
1. Purpose and scope. Describe which entities, processes and AI system types the policy covers — including generative AI, predictive models and automated decision-making.
2. Definitions. Fix key terms (AI system, high-risk, personal data, automated decision) so everyone speaks the same language and the policy is auditable.
3. Roles and responsibilities. Appoint an AI owner or steering committee, define the DPO's role, and name who may approve new AI use cases.
4. Risk classification (EU AI Act). Distinguish prohibited use cases, high-risk systems, limited risk and minimal risk. Attach required safeguards and the decision process to each category.
5. Data and privacy (GDPR). Record which data categories may be processed, on what legal basis, how long they are kept, and which processors are allowed — with explicit attention to on-premise hosting.
6. Security and access. Describe authentication, authorisation, logging, encryption in transit and at rest, and how models and prompts are protected against unintended leakage.
7. Transparency and explainability. Set when users and data subjects are informed that AI is used, and the minimum explainability required for decisions that affect them.
8. Human oversight. Define for which decisions a human is the final decision-maker, and how human review is concretely organised.
9. Monitoring and evaluation. Set how often models are evaluated for bias, drift and performance, and how incidents are reported and followed up.
10. Training and awareness. Require that employees working with AI are demonstrably trained — an explicit obligation under the EU AI Act from February 2025 onwards.
Read more on the legal context at Private LLM, GDPR and the EU AI Act.
Implement the policy in five steps
A policy is only valuable when it works. Follow these five steps to turn the template into a living document within your organisation.
Step 1 — Take inventory. Map which AI applications are already in use, including public tools. Without that view, any policy is theory.
Step 2 — Tailor the template. Complete the sections with your own roles, vendors and processes. Delete what doesn't apply and add sector-specific requirements.
Step 3 — Have it reviewed. Ask your DPO, security officer and legal counsel to review the policy. In larger organisations, involve the works council too.
Step 4 — Adopt and communicate. Have the policy adopted by leadership and make sure all employees know it — a policy on the shelf doesn't work.
Step 5 — Maintain. Plan at least an annual review, and sooner in case of major technological or regulatory changes.
An AI policy is stronger with the right technical base. A secure private LLM with on-premise hosting makes compliance significantly easier than public AI tools.
