Garbage In, Garbage Out: Legal AI’s Big Data Problem (and how to fix it)

About the Webinar

Your company prides itself on innovation. The AI revolution is here, and you’re ready to seize the moment. You spend the money and time implementing a state-of-the-art AI tool for your legal. The only problem? It doesn’t work.  

Though AI holds enormous promise for in-house legal teams looking to increase efficiency, reduce cost, and drive better decision-making, most legal departments jump ahead to AI implementation without ensuring their data is structured and reliable. The result is sunk cost with low adoption and even lower ROI. Because without a solid foundation, even the best technology will fail to deliver.  

This webinar explores why data quality is the most important (and often overlooked) step in implementing legal AI tools. We’ll take a ground-up approach to help in-house counsel understand what “good data” actually means, and what they need to do before deploying AI for contract review, analysis, and other functions. We also discuss how alternative legal service providers (ALSPs) like Axiom can help teams pilot AI tools or get their data house in order with scalable support and tailored subject-matter expertise. 

Agenda items include:

• Why poor data leads to poor AI
• How to assess your team’s data maturity
• Strategies to structure data
• Prominent legal AI use cases