What should an AI-assisted workflow record?
A useful evidence record helps an authorised reviewer understand what happened in a particular workflow run. It should be designed around the task, the risks and the organisation’s retention rules. Recording everything by default can create privacy, security, storage and access problems; recording too little can make review difficult.
For each workflow, first identify the question a reviewer may need to answer. Was the correct input used? Which process version ran? What did the AI return? Was the result reviewed, corrected or rejected? Who approved the next step? Did an exception occur? The answers determine which events the system should record.
A proportionate record may include a workflow or case identifier, date and time, process version, source references, the AI task or prompt version, the output presented for review, validation results, reviewer actions, approval status, exception route and any subsequent correction. Whether to store raw inputs or outputs depends on purpose, privacy, security, contractual obligations, retention and technical design. Prefer a secure reference to an authorised source record where that is sufficient.
Define access and retention before launch. Decide who can view the record, who can change configuration, how long records are retained, how exports are produced and what happens when a customer or employee exercises a data right. Document any limitations, such as incomplete third-party telemetry or a model provider that does not expose a particular event.
Test that the record matches actual behaviour. Run normal cases, exceptions, retries, service failures and manual overrides. Confirm that the record lets a reviewer reconstruct the sequence that matters without implying that the AI output is correct. Reassess the evidence design after changes to the model, prompt, workflow, integration or retention requirement.
An evidence record supports review; it does not prove a system is compliant, accurate, tamper-proof or audit-proof. The organisation remains responsible for deciding what evidence is required and whether it is sufficient for its context.
KPOData’s platform describes an append-only history of field-level changes in production. The events, retention period, export options and coverage for AI requests and responses must still be confirmed for each deployment. If your team needs a record of AI-assisted work, start by defining the reviewer’s questions and the evidence needed to answer them.
