1. Define the task and its owner
Choose one process with a known starting point and a result that can be checked. Identify who owns the process and who will review the pilot. A knowledge assistant that finds approved guidance is easier to evaluate than a broad request to automate an entire department. Record a baseline for time, quality, or review effort.
2. Decide which information the system may use
List approved data sources and determine whether users have different access rights. Retrieval must respect those boundaries. Review provider terms, data retention, training settings, and the treatment of personal information. Using an internal document does not automatically make every part of it appropriate for every employee.
3. Separate answers from actions
Drafting a response and sending it are different capabilities. Define which tools the agent can use, the limits on each action, and which steps require human approval. A document or webpage the agent reads should be treated as information, not authority to change its instructions.
4. Test realistic failures
Evaluate incorrect answers, missing sources, conflicting records, and attempts to manipulate the assistant. Include Greek and English examples if both are used at work. Test permission boundaries as well as answer quality, and measure how much review the result still needs.
5. Plan operation and review
Assign responsibility for monitoring, access changes, model updates, and incident handling. Agree on a rollback or manual fallback. Expand the pilot only when its quality, cost, and control measures have been evaluated. AI governance and security assessment can support this process; legal obligations depend on the application and the organisation’s role.
Further reading
Put the guidance to work
Assess prompt injection, data exposure, agent permissions, model behaviour, and the governance of AI adoption.
AI security & governance