AI Is Revolutionizing Legal Research and Discovery

August 8, 2024

Strategies for Effective Compliance Risk Assessments

Artificial intelligence is being hyped within the legal industry as a transformative tool that is revolutionizing legal research and discovery, according to a U.S. Legal Support article. Demonstrating explosive growth over the past few years, AI is now being incorporated into eDiscovery by legal teams, corporations, and government agencies.

AI can significantly enhance the discovery process by:

  • Automating data collection, processing, and review
  • Crafting summaries of legal documents
  • Reviewing electronically stored information

AI’s ability to respond to human inquiries, refine search patterns, and conceptually cluster relevant data improves the efficiency and effectiveness of legal work.

Investing in AI technology promises long-term benefits. According to Deloitte, review time can be reduced by up to 40% by applying machine learning algorithms. AI tools can process data faster and more accurately than humans, eliminating errors from fatigue or bias. Predictive analytics can identify compliance issues, legal risks, and potential conflicts, predict case outcomes, and provide legal insights. However, the most important aspect of using AI in legal discovery is human oversight. Review processes should be in place to ensure that any AI output is reviewed for accuracy. 

Adopting AI comes with challenges, such as the need for training and overcoming user resistance. The future of AI and its use in legal discovery requires enhancing skill sets, as legal professionals will need to learn about creating generative AI prompts, identifying biases, and evaluating relevance. New methods will be needed for training as the manual discovery work that was part of the training will need to be replaced. 

As AI is revolutionizing legal research and discovery, expect changes in skill sets and more regulations. Legal professionals will need to adapt to these advancements, ensuring they can effectively guide and evaluate AI output. 

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