As legal teams navigate the evolving landscape of e-discovery, a new challenge has emerged: managing the output and prompt logs from generative AI tools. According to Thomas Barce from FTI Technology, enterprises are actively forming committees, budgeting resources, and conducting pilots to implement these advanced AI applications. While there is significant pressure to quickly onboard and leverage these tools, legal teams face the delicate balance of embracing innovation while maintaining robust risk management practices.
The introduction of generative AI into enterprise environments has created a new dimension of information governance, necessitating control over “interactions” — logs of prompts used to query AI tools. New discovery rules and processes are required to handle these previously undiscoverable data categories, including interactions and machine-generated documents.
To prepare for potential e-discovery scenarios involving AI-generated data, companies must address several key areas:
- Establishing governance and compliance policies for AI interactions
- Determining storage and retention protocols for prompt logs
- Implementing monitoring systems to ensure compliance
Organizations should manage AI tools similarly to other communication methods like emails and chats. Legal teams can enhance oversight by conducting security and third-party risk audits, establishing protective contractual controls, and implementing abuse monitoring capabilities. It’s also crucial to review access controls to prevent unauthorized queries and ensure sensitive information is adequately protected.
As generative AI use cases expand, the data sets created by AI tools, including prompt logs and outputs, may fall within the scope of e-discovery. These artifacts could become pivotal in litigation or regulatory investigations, raising new challenges for preservation, collection, and analysis.
Modern communication tools like Slack, Zoom, and ephemeral messaging platforms quickly became rich sources of evidence. Likewise, as generative AI gains mainstream adoption, data from these systems is likely to be sought for fact-finding in discovery processes.
Currently, many organizations are still in the early stages of implementing generative AI, dealing with proof of concept and pilot phases. Given the rapidly evolving nature of AI technology, governance and e-discovery readiness programs must remain adaptable and subject to continual testing. Until more established controls are in place, companies must proactively manage AI-generated data to avoid potential liabilities.
The clock is ticking. With an expected 12- to 24-month lag between the adoption of new technology and its emergence in litigation, today’s AI outputs could become tomorrow’s legal battlegrounds.
For more detailed insights, visit Bloomberg Law.