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.
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.