As generative and agentic AI tools move from experimentation into real litigation workflows, legal teams are rethinking how evidence is captured, analyzed, and used to prepare for disputes. This session examines how AI-driven transcription, evidentiary consistency analysis, and agent-based workflows are reshaping litigation preparation—from identifying inconsistencies across the record to supporting deposition strategy through simulations and automated preparation tasks. Panelists will focus on practical, defensible use cases drawn from real-world litigation environments, exploring where these technologies add measurable value, how teams validate outputs, and what guardrails are necessary to preserve accuracy, security, and attorney judgment as AI becomes embedded in litigation strategy.

Discussion topics include:

• Using AI to surface inconsistencies, gaps, and context across the evidentiary record
• Agentic AI applications for deposition preparation, simulations, and litigation readiness
• Establishing guardrails for accuracy, security, and defensibility in AI-enabled litigation workflows