Control design

Traceability Is the Difference Between AI Assistance and AI Risk

Published July 21, 20263 min read

AI can produce a plausible answer quickly. Professional work also requires the ability to explain where the answer came from, what changed, what remains uncertain, and who accepted responsibility for the result.

Preserve the source

A controlled workflow identifies the files, records, messages, or data used for each material step. When a source changes, the team should be able to identify downstream work that may need review.

Record material transformations

Capture enough evidence to show what the system was asked to do and which material parts it produced or changed. The goal is reconstructability, not surveillance of every keystroke.

Surface exceptions

A polished draft can hide missing inputs and contradictory facts. Unresolved items should be visible, assigned to an owner, and governed by a rule for when work may proceed.

Separate assistance from approval

Reviewers should know what was automated and what requires judgment. Final approval should remain attributable to a responsible person.

Run the traceability test

Which sources were used?
What did the system change or generate?
Which exceptions were raised?
Who reviewed the material result?
What evidence shows final approval?

Private pilot

Review one high-rework workflow.

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