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Buyer template · Research verification checklist · Updated 2026-08-15

AI Research Source Verification Checklist

A copyable checklist for deciding whether AI-assisted research has enough traceable, independently checked evidence to support an important decision.

When to use it: Use this before an AI-assisted research summary becomes evidence for a product, vendor, strategy, or other consequential business decision.

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Define the decision and evidence bar

  • State the decision the research is meant to support and what would materially change that decision.
  • Separate facts, inferences, and recommendations so a confident summary does not hide where judgment begins.
  • Name the reviewer or decision owner who is accountable for checking the evidence before the conclusion is used.

Trace the material claims

  • Attach a source to every claim that could change the decision; do not accept an AI-generated citation list without opening the underlying sources.
  • Prefer primary sources for current product, policy, pricing, legal, scientific, or company claims when primary evidence is available.
  • Record the source date or version when freshness matters, and flag claims that rely only on secondary summaries or inaccessible material.

Cross-check decisive evidence

  • Open the underlying source and confirm it actually supports the claim being made, including important scope, caveats, and exceptions.
  • For the most consequential claims, look for an independent source, counterexample, or contradictory evidence instead of only collecting confirming material.
  • Record unresolved conflicts and missing evidence explicitly; do not collapse disagreement into one synthetic certainty score.

Hand off a reviewable decision packet

  • Summarize the conclusion, the strongest supporting evidence, the important unknowns, and what new evidence would reverse or materially weaken the conclusion.
  • Keep a source list or evidence table with enough context that another reviewer can reproduce the decisive checks without rerunning the AI workflow.
  • For high-stakes decisions, require the appropriate human, domain, legal, security, or compliance review before acting on the research.
  • Set a recheck date when the conclusion depends on fast-changing products, policies, prices, or other time-sensitive facts.

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