How to Get More Out of Your Depositions With AI

A deposition transcript is a data input. The quality of that data determines what AI can do with it downstream. This course walks litigators through a three-phase framework for integrating AI into the deposition process: before the deposition (witness research and question building), during the deposition (record hygiene practices that make transcripts AI-ready), and after the deposition (AI-assisted review, contradiction analysis, and trial prep).

Throughout, the course addresses the professional responsibility obligations that arise at each phase-including competence, confidentiality obligations when inputting case data into AI tools, supervision of staff AI use, and verification requirements for AI-assisted work product. Attorneys will leave with a practical, phase-by-phase action plan they can implement immediately.

Learning Objectives

• Understand how AI can be used at each phase of the deposition process to improve preparation, record quality, and post-deposition review

• Identify the professional responsibility obligations triggered by AI use in deposition practice, including competence, confidentiality, supervision, and candor

• Apply record hygiene practices during depositions that improve the accuracy and utility of AI analysis afterward

• Develop verification protocols for AI-assisted deposition prep and transcript review

• Implement supervision standards for staff and associate AI use on deposition-related tasks

• Evaluate AI tools for deposition use against confidentiality and security requirements 

This CLE is provided by Lawline. To earn your credit, click the Play button above.