Evidence and accountability
What should a decision evidence pack contain?
A future reviewer should be able to understand what was requested, which information was considered, how AI contributed, what a person decided and what happened next.
Keep enough connected evidence to explain the decision without collecting everything indiscriminately. The record should be proportionate to the consequence of the work.
Begin with the original request
Retain the question, desired outcome, accountable owner, timing and material constraints. Without the original intent, a later reader cannot judge whether the output answered the right problem.
Where the request changes, preserve that change rather than overwriting the starting point. A revised brief can be as important as the final decision.
Identify sources and relevant context
Record the policies, documents, data, prior decisions and other approved sources used. Where practical, preserve a version or reference so the reader can distinguish the information available at the time from information added later.
This does not mean copying every connected system into the evidence pack. It means making the material basis of the decision identifiable and reviewable within the agreed information boundaries.
Show what automation and AI did
Separate deterministic actions from interpretive assistance. The record might show that a rule validated required fields, an agent compared a response with criteria, and a second step prepared a summary for review.
Keep prompts and technical traces when they are genuinely useful for assurance, but do not confuse a large volume of machine logs with an intelligible account. A reviewer needs to understand the role of the assistance, the context supplied and the output that influenced the next step.
Keep human review visible
Name the reviewer or accountable role, the options considered, the decision and the rationale appropriate to the situation. If the person adjusted or rejected an AI recommendation, retain that difference rather than silently replacing the earlier output.
This is particularly important when the workflow involves professional judgement or acceptance of risk. Human oversight should leave a meaningful decision record, not merely a tick box.
Capture exceptions and uncertainty
Evidence packs become most useful when the standard route breaks. Record missing information, conflicting sources, policy exceptions, permission problems, escalations and unresolved uncertainty.
An honest record may say that a conclusion was provisional or that a decision proceeded with a named limitation. Removing ambiguity from the record does not remove it from the decision.
Connect the outcome
A recommendation is not the end of the work. Where possible, connect the approved output, action taken, subsequent status and relevant feedback. This allows the organisation to ask whether the workflow produced a useful result, not simply whether it completed.
Outcome evidence also supports later improvement. Recurring exceptions or reversals may point to a weak source, an unclear rule or an AI task that needs to change.
Make the pack proportionate
A routine, reversible decision may need a compact record. A consequential or regulated decision may require stronger versioning, authority, retention and review controls. Those requirements should be agreed with the relevant technical, legal and operational owners.
The aim is neither surveillance nor paperwork for its own sake. It is continuity: another authorised person can understand what happened and decide what should happen next.
Design the evidence with the workflow
Decide what must remain connected before the first case reaches review.
Map a decision route