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Core AI skills

How to summarise long documents with AI without losing what matters

By TechlyUpUpdated 2 min readProfessionals who read a lot

Quick answer

Tell the AI who the summary is for and what decisions it supports, ask for a structured output (key points, numbers, risks, open questions), and require a quoted source line for each point. For very long documents, summarise section by section, then combine. Check numbers and any statement you will act on against the original.

Define the purpose first

A summary for a manager deciding whether to renew a contract needs different content from a summary for a colleague preparing a presentation. State the reader and the decision in your prompt.

Ask for structure and traceability

A structured, quoted summary is easier to check than a paragraph.

Reader: finance head deciding on renewal.
Summarise the contract below under: obligations, costs and payment terms, renewal and termination, risks, open questions.
For each bullet, quote the clause number it comes from. If a heading has nothing in the document, write “not found”.

Handle long documents in parts

Split long documents into sections, summarise each with the same structure, then ask for a combined summary from the section summaries. This reduces the chance that details from the middle are dropped.

Check before you share

Recompute any totals, open every quoted clause, and read the “not found” items yourself — absence in a summary isn't proof of absence in the document.

Common summarisation mistakes

These lead to summaries that look complete but aren't.

  1. Asking for “a summary” without saying who it's for, so the AI chooses what matters.
  2. Trusting summaries of scanned or badly formatted PDFs where text extraction failed silently.
  3. Losing numbers: summaries often round, merge, or drop figures that were important.
  4. Sharing the summary instead of the document when decisions depend on exact wording.

Worked example: a board pack summary

A manager has a 60-page board pack and 20 minutes. They split it into its five sections and run the structured prompt on each, asking for decisions required, key figures with page references, risks, and questions to raise.

They then combine the five section summaries into a one-page brief and spot-check every figure against the referenced page. Two figures turn out to be from the prior year's comparison column — a common extraction error. The final brief is accurate, traceable, and ready for the meeting, and the manager knows which pages to read in full.

Try it yourself

Summarise a public report you know using the structured prompt. Check five bullets against the source and note any that were wrong or missing context.

Frequently asked questions

Can AI summarise PDFs accurately?

Often, when the text is extractable and you ask for traceable points. Scanned images, tables, and complex layouts can cause errors.

Is it safe to upload contracts to AI tools?

Only if the tool is approved for that data under your organisation's policy. Remove or mask sensitive details otherwise.

How long can a document be?

It depends on the tool's limits. For very long documents, the section-by-section method is more reliable anyway.

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Sources and further reading

Examples are authored practice material, not measured learner outcomes. Tool behavior can change. Found an error? Contact TechlyUp with the page URL and correction.

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