AI summarization: Definition and best practices
If you’re feeling overwhelmed by the volume of files you need to go over or rushing against the clock to complete a report, leveraging artificial intelligence (AI) to summarize documents and extract key insights will help you save time and untap the value of your unstructured data.
Let’s explore how to make the most of AI summarization tools to improve your productivity and decision-making.
What is an AI summarizer?
An AI summarizer is a type of technology that leverages large language models (LLMs) to analyze and condense text or information into a shorter, coherent summary.
AI document summarization often employs algorithms that prioritize important sentences, phrases, or concepts based on factors such as relevance and frequency within the text. The goal is to extract the most relevant information from a given document while preserving the key meaning and context. This way, you get a quick overview of the main points without the need to go through the entire text, streamlining information extraction and saving time.
There are two approaches to text summarization:
- Extractive summarization: Selects and compiles the most relevant sentences or phrases directly from the source material
- Abstractive summarization: Understands the content and paraphrases it in a more concise form
AI summary tools find applications in fields such as content curation, research assistance, data analysis, and more. Here are a few use cases.
| Type of document | Use of AI summary tools |
| Business plans | Provide a quick overview of the strategy and goals, highlighting processes and requirements |
| Market research studies | Condense key market trends, opportunities, and competitive insights |
| Competitor analysis | Outline strengths, weaknesses, and strategic implications |
| Financial statements | Extract critical financial information for efficient financial analysis and forecasting |
| Legal contracts | Indicate the most important terms and obligations |
| Meeting minutes | Capture action items, decisions, and key discussions for easy reference |
| Email and memos | Go through lengthy email threads to bring out important information and action items |
| Policy documents | Sum up internal policies, compliance documents, and regulatory updates for a quick understanding |
| Project updates | Recap progress reports and milestones for efficient project management |
| Customer feedback | Compile feedback from surveys, reviews, and support interactions to identify trends and areas for improvement |
| Employee surveys | Identify key concerns, trends, and areas for organizational improvement |
Why you need AI summary generator tools
In a McKinsey study, 8% of respondents in marketing and sales said their organizations are using generative AI to summarize text documents. With this use case of AI technology, enterprises reduce manual work and save employee time. Consider the following benefits.
Increased efficiency and scalability
Unlike manual summarization, which is time-consuming and resource-intensive, AI algorithms analyze and summarize large datasets in a fraction of the time. No wonder 79% of IT leaders surveyed by Salesforce cite operational efficiency as a top benefit of generative AI.
With this increased efficiency also comes greater scalability. And as the amount of data grows, an AI summarizer is able to handle the increased workload without a proportional increase in time or resources.
Take the example of legal teams, which rely on summarizations to navigate extensive legal briefs, case documents, and contracts with efficiency. By accelerating legal research and case preparation, AI summarizations enable lawyers to dedicate more time to client-focused tasks.
Reduced information overload
Enterprises generate an often overwhelming volume of documents, reports, emails, and other content on a daily basis. In fact, in a Box-sponsored IDC report, 25% of respondents said that data volume is growing faster than their ability to use, process, and/or manage it.
AI summary generator tools help to reduce the burden of information overload by offering a more digestible and accessible representation of data without sacrificing critical content.
In life sciences, for example, scientists often encounter a wealth of scientific papers, research articles, and experimental reports. By using AI for summarizing information, researchers quickly sort through complex scientific literature in order to identify breakthroughs, novel methodologies, and key findings.
Enhanced decision-making
According to IDC, 90% of the data generated by organizations is unstructured, creating a missed opportunity to extract information of potential value. AI summarization helps extract knowledge and insights from vast repositories of unstructured text data, making it easier to leverage this knowledge for faster and more informed decision-making.
Let’s say you receive a high volume of customer reviews, emails, and inquiries. AI algorithms quickly analyze and summarize the sentiments and key themes expressed by customers. Instead of manually sifting through each piece of feedback, you go directly to key takeaways. With this automation, customer service teams gain a rapid overview of customer satisfaction, identify recurring issues, and prioritize areas for improvement.
How to use AI to summarize a document: 5 best practices
When summarizing documents with AI, follow these best practices to enhance the quality and relevance of the generated content:
- Understand the purpose: Clearly define what you want to accomplish — for example, quickly retrieving information or conveying key points to a broader audience
- Provide clear and precise instructions to the AI tool: Give detailed commands so the AI model understands the intent accurately, resulting in more relevant and accurate generated content — for example, indicate the desired word count for the summary
- Tailor the summary to the intended audience: Adjust the level of detail and technicality according to the target audience
- Use extractive and abstractive summarization techniques wisely: Combine extractive and abstractive AI summarization methods based on the specific requirements and nature of the content
- Review and refine the AI-generated summary: Correct any inaccuracies, awkward phrasing, or missing context
More than an AI document summarizer
Box AI helps you unlock the full potential of your enterprise content, whether it’s a sales presentation, budget spreadsheet, or lengthy PDF with product specs.
Our new suite of intelligent capabilities natively integrates advanced AI models into the Content Cloud. As a result, you summarize documents with AI in seconds. But there’s much more you can do.
With a simple command, create emails and reports from scratch or refine existing content. By asking questions about a specific document (or a few of them), you can quickly uncover critical information and get insights for making informed decisions.
Plus, enterprise-grade security is built into our DNA, so rest assured that your Box AI data is always protected. We follow strong AI principles to ensure your proprietary data stays safe.
Reach out to our team, and let’s discuss your AI summarization needs.
**While we maintain our steadfast commitment to offering products and services with best-in-class privacy, security, and compliance, the information provided in this blog post is not intended to constitute legal advice. We strongly encourage prospective and current customers to perform their own due diligence when assessing compliance with applicable laws.