A company needs to extract the main points from lengthy policy documents to help employees find information faster. Which generative AI strategy should they use?

Summarization is the correct strategy because it directly addresses the need to condense lengthy text into shorter, coherent versions while retaining the main points. This is precisely what's required to help employees quickly grasp essential information from policy documents. Regression is used for predicting continuous numerical values, which is irrelevant to extracting main points from text. Clustering groups similar data points together, but doesn't extract meaning or condense text. Classification categorizes data into predefined classes, like sentiment analysis or spam detection, not for extracting main points from a document.