How to Check an AI Summary Against Its Source

AI

The summary reads well and fits on one page. Then someone notices a conditional delivery date has become a commitment. The wording improved while the meaning changed.

Two people reviewing printed documents at a table beside a phone and folder.

Photo by Olena Kholina on Unsplash.

Check an AI summary by comparing its claims, omissions and qualifications with the source. Readability is one criterion. Faithfulness to the information the reader needs deserves a separate check.

Define the purpose

A summary for deciding whether to accept a proposal needs different content from a quick reading aid. Write down the decision and the facts that must survive compression.

For an illustrative supplier proposal, those include deliverables, exclusions, dependencies, prices and dates. Identify what could change the reader's decision rather than treating every detail equally.

Check claims and coverage

Review in two directions:

  • From summary to source: where is each material claim supported?

  • From source to summary: which important points are missing?

  • Conditions: have proposed, subject to and optional been preserved?

  • Attribution: has a suggestion become an agreed decision?

  • Values: do numbers and dates retain their context?

  • Uncertainty: are unresolved questions visible?

Record error types rather than one general score. Unsupported additions and omitted exclusions need different corrections. Decide which errors stop the summary being used.

Include difficult sources

Try material with a changed decision, unresolved issue or similar dates. Success on clean, linear documents does not demonstrate the behaviour needed for complicated work.

If the source is unclear, the summary should identify that ambiguity. Do not force a definite answer because the template includes a field for it.

Keep reviewers near the evidence

Provide the source alongside the output and request relevant passage references where the tool supports them. Verify references rather than treating their presence as proof.

Use corrected examples to improve instructions, then check other cases to see whether the correction generalises. Keep acceptance criteria stable while comparing versions. Otherwise a new scoring rule can look like an improvement in output.

Finally, check whether the shorter result helps the intended reader make the decision without reopening every paragraph unnecessarily.

Related guidance: guide to mapping the work before changing it.

Hili Consulting can help design a summary-review checklist around the decisions your team actually needs to make.

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