AI needs a reviewer
A useful procurement AI discussion starts with accountability for the output.
Know the consequence of error
Summarising a public document and recommending a supplier decision have different risk profiles. Before discussing speed, identify what a wrong output could change. The review process should fit that consequence, with a named owner for the final judgement.
Inspect the source material
Incomplete documents and inconsistent records do not become dependable merely because a model can read them. Ask which sources the output uses, how recent they are and how conflicting information is handled. Make it possible for a reviewer to follow the result back to evidence.
Measure the whole workflow
Time saved in generation may be spent again in verification and correction. Compare the complete task, including review, rather than only the moment the tool produces an answer. A bounded trial reveals whether the workflow is genuinely useful.