Text Summarizer: How AI Summarisation Works and When to Use It
Understand AI text summarisation — extractive vs abstractive methods, tools, and best practices.
What Is Text Summarisation?
Text summarisation automatically condenses long content into a shorter form while preserving key information. AI summarisation tools can reduce a 5,000-word article to a 200-word summary in seconds.
Two Types of Summarisation
Extractive summarisation: Selects the most important sentences from the original text and presents them as the summary. The exact original language is preserved — nothing is paraphrased. Simpler but may miss nuance and read choppily.
Abstractive summarisation: Understands the content and generates new sentences capturing the key ideas. Like how a human would summarise — the output may use different words than the original. More sophisticated, produces more readable summaries.
Modern AI tools (ChatGPT, Claude) use abstractive summarisation. They understand meaning, not just sentence frequency.
Use Cases for AI Summarisation
Research: Quickly assess whether a paper is worth reading in full by summarising the abstract and introduction.
News: Summarise long news articles to their key facts.
Email threads: Summarise long email chains to get the current status quickly.
Meeting notes: Paste raw meeting notes and get a structured action item summary.
Legal documents: Get the key points of contracts before detailed review (always follow up with full reading).
Limitations to Understand
AI summaries may miss crucial nuance or caveats present in the original. For important decisions (legal, medical, financial), read the full document — use summaries only for initial orientation.
AI summaries can introduce errors — the model may paraphrase incorrectly or omit critical exceptions. Verify key facts against the original.
Best Practices
Request specific output: "Summarise in 3 bullet points" produces a different result than "write a paragraph summary." Be explicit about format and length.
Provide context: "Summarise this contract focusing on payment terms and cancellation clauses" gives better results than a generic summarise request.
Frequently asked questions
Can AI summaries be trusted?
For initial orientation, yes. For important decisions, no — always read full legal, medical, and financial documents. AI summaries can miss nuance, introduce errors, or omit critical exceptions.
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