Britixo · Practical product and service guidance
AI Audit Trails and Evidence
Connect AI system changes, review decisions and operating evidence so that authorised reviewers can understand what happened and why.
01
Record the decision as well as the event
A timestamp shows when an action occurred; it does not explain why the action was approved. Connect relevant events to the use case, deployment version, responsible person and supporting assessment. Distinguish automated system activity from a human decision and make the source of each record clear.
02
Protect the evidence without over-collecting
Define access, retention and export requirements around the information actually needed for review. Logs may contain confidential inputs or outputs, so minimise or redact content where appropriate. Test whether exported evidence preserves its identifiers and context. A file labelled audit does not automatically establish completeness, integrity or legal admissibility.
03
Make review repeatable
Agree the question a reviewer should be able to answer, then trace a sample from a system change to its approval, evaluation and operating result. Record gaps and unresolved findings with an owner. The software should support your evidence process; assurance depends on the process, controls and records in the specific deployment.