Summarisation is one of the clearest AI value-adds — processing a 100-page report in minutes rather than hours is a genuine time saving that changes what is feasible in a working day. Here is how to use AI summarisation effectively.
What AI Summarisation Does Well
AI is excellent at: extracting the key points from a long document, identifying the structure and main arguments, finding the sections most relevant to a specific question, and producing summaries at different levels of detail (executive summary, detailed outline, bullet-point action items). For legal contracts, academic papers, corporate reports, and technical documentation, AI summarisation reduces the time required to extract usable information by 60–80%.
Types of Summary Prompts
Different prompts produce very different outputs. “Summarise this document” produces a general summary. “What are the three most important conclusions?” produces specific takeaways. “What obligations does this contract place on us?” produces legal-analysis output. “What methodology did this paper use and what were its limitations?” produces academic critique. “List every date, deadline, and party mentioned in this document” produces structured extraction. Match the prompt type to your actual need.
Multi-Document Synthesis
With a 200K token context window (Claude’s limit), you can paste multiple documents and ask for synthesis across them. “Compare the approach taken in these three research papers and identify where they agree and disagree” is a task that previously required hours of reading and note-taking. The output is not a replacement for reading the papers yourself when depth matters, but it is an excellent first-pass orientation.
Limitations
AI summaries lose nuance and context that may matter for specific decisions. They can mischaracterise subtle arguments or technical distinctions. For documents where precision is legally or technically critical, verify the summary against the original before acting on it. AI is better at telling you what a document says than at judging whether what it says is correct.
