Whenever a policy or procedure is revised, finding every change across two long PDFs can take time. ChatGPT can help organize a comparison, but the team still needs to check what was read and whether important findings match the source documents.
This comic follows a team comparing fictional training-registration rules. They ask ChatGPT to group items as unchanged, added, removed, or changed, then verify important passages in the original PDFs and record the filename, viewer page, and section. When an appendix reveals a changed deadline, the team also keeps an unresolved effective-date question visible instead of guessing. Follow along to see how a quick comparison can become a useful, evidence-backed report.
The team finds an important change in the appendix: the fictional registration deadline moves from three business days to five business days before training. Another detail—the date an effective-date note refers to—remains unclear, so the team leaves it as a question for the policy owner before publishing a staff notice.
A useful workflow is to define the task, identify the old and new versions, compare the documents, verify high-impact changes in the source, and separate confirmed findings, proposed actions, and open questions. The same approach can help with contracts, policies, and manuals. Try it with documents you are permitted to use, and record the evidence alongside each change. For personal or confidential information, follow your organization’s approved AI tools and data rules.
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