Extract from Justin Smith’s article, “Am Law 200 Firm Sets a New Standard for AI Performance in High-Stakes Insurance Litigation.”
Key Takeaways
Using generative AI to review nearly 600,000 documents in an insurance matter, this Am Law 200 law firm reported impacts including:
- Precision: 93% precision rate in the validated responsive sample.
- Recall: 93% recall rate for the Responsive No category and 60% recall rate for the Responsive Soft No category.
- Time Savings: The review timeline went from six weeks to less than two weeks.
In the modern legal landscape, the most formidable opponent often isn’t the opposing counsel—it’s the sheer amount of the data itself. As discovery evolves from a manageable stream into a digital deluge, the traditional linear review models that once served as the industry standard are being pushed to their breaking point.
For today’s litigation teams, the ability to harness generative AI to navigate this sea of information with precision hasn’t just become an advantage, but the new benchmark for excellence.
When faced with a case involving a complex insurance coverage dispute, an Am Law 200 firm saw an opportunity to save their client both time and money by leveraging generative AI, and primarily Everlaw’s Coding Suggestions tool, in the document review process.
