Your clients are already using AI to fact-check you, test defenses, and workshop their next move and they’re doing it on their phones with a timestamp. That means generative AI chat history is no longer a novelty in e-discovery. It’s ESI that can show intent, knowledge, and credibility, and a judge may end up reading it line by line.
We break down Conlin Tire Company v Gonzalez, a non-solicitation dispute where the entire case turns on whether an agreement was signed and returned by email. During a forensic examination, the defendant’s ChatGPT prompts about deleted Yahoo emails become a key piece of circumstantial evidence. The court ties those prompts to the timeline, shifting explanations, and access delays, ultimately finding intent to deprive under Rule 37(e) and moving toward an adverse inference instruction.
From there, we follow the arc: targeted replacement discovery, fights over what can be restored or replaced, and how incomplete compliance can make missing evidence truly irreplaceable. Then we connect the sanctions record to real-world litigation outcomes, including how the adverse inference supports a preliminary injunction. Along the way, we translate the decision into practical steps for preservation letters, forensic collection protocols, and client intake scripts so you’re ready for AI evidence in employment, trade secret, and contract cases.
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Thank you for tuning in to Meet and Confer with Kelly Twigger. If you found today’s discussion helpful, don’t forget to subscribe, rate, and leave a review wherever you get your podcasts. For more insights and resources on creating cost-effective discovery strategies leveraging ESI, visit Minerva26 and explore our practical tools, case law library, and on-demand education from the Academy.
