ARTIFICIAL INTELLIGENCE:
Do I Need to Disclose My Client’s Use?
BY CHARLES MILLS, ESQ.
GENERATIVE AI (GENAI) is rapidly entering litigation, raising new discovery concerns. Artificial Intelligence’s (AI) contact with evidence can affect privilege, authenticity, and confidentiality. Maryland courts have not yet issued AI-specific discovery guidance, so the need to proactively understand how GenAI might impact litigation necessitates proactive measures.
GenAI and Its Artifacts: What Lawyers Should Know GenAI refers to AI systems that can create new content (text, images, audio, etc.) by learning patterns from existing data. There are three “AI artifacts” that become part of a client’s electronically stored information (ESI):
A prompt – the user’s input or query (e.g., “Summarize this deposition transcript in 200 words”).
An output – the AI’s generated response (e.g., a written summary of the transcript).
Prompt metadata/logs – behind the scenes, the system may record data about the interaction: the prompt text, the time, the user account, and even system parameters used. These logs can be akin to an AI “audit trail.”
These records can often include data that clients want to preserve, just like any other business records, as they provide deeper insight into an organization’s thought process and decision-making than similar ESI. Lawyers need to be familiar with the discoverability of such records so they can guide clients on updating internal retention policies to reflect these advancements.
Discovery Implications of Generative AI Usage
A client’s use of GenAI in the ordinary course of business can become a part of discovery in litigation. Maryland litigators should be prepared to handle several issues unique to AI-generated ESI: what is discoverable, how to preserve it, and how to address relevance and privilege concerns.
Types of AI-generated material that may be discoverable:
GenAI outputs are generally discoverable within ordinary discovery constraints. For example, if a marketing team used an AI tool to draft product descriptions, those outputs are like any other corporate documents.
More novel are the prompts. Suppose an employee asked a GenAI tool to analyze a dataset and received an output that influenced a business decision now in dispute. Now, counsel requests the prompt. But not every AI prompt is relevant; many will be unrelated to the litigation. Lawyers will need to negotiate the scope so that fishing expeditions into a company’s AI use are avoided unless clearly tied to the case. One recent federal case highlights the care needed here. In Tremblay v. OpenAI, the defendant sought broad discovery of the plaintiffs’ ChatGPT prompts and account data from
their pre-suit testing of the AI. The court ultimately denied most of the requests to compel, noting counsel’s queries to test an AI were work product. The plaintiffs only had to produce the specific prompts and settings actually used and quoted in their complaint.
Preservation challenges:
Since GenAI artifacts may not be stored unless a user saves them, and some enterprise AI tools may not retain logs indefinitely, counsel must address preservation issues early. In practice, this means working closely with information technology (IT) to understand the applications your client is using and the saving mechanics of each. Failing to preserve an AI output that played a role in key decisions could risk spoliation.
data, and usage logs).” Establishing these terms ensures everyone is on the same page about the subject matter.
Confidentiality concerns:
Normally, a receiving party agrees not to disclose confidential materials to anyone beyond the litigation team. But if a lawyer uploads the other side’s confidential documents into a public AI service to summarize or analyze them, that could effectively disclose them to the AI provider, undermining the order. To prevent this, a protective order can state: “No party or counsel may input, upload, or expose another party’s Confidential or Attorneys’ Eyes Only information to any generative AI tool or service unless (a) the tool is an internal or securely hosted platform that does not disclose or use
Maryland courts have not yet issued AI-specific discovery guidance, so the need to proactively understand how GenAI might impact litigation necessitates proactive measures.
Relevance, proportionality, and scope:
Opposing counsel might overreach with discovery requests, such as “Produce all documents and communications involving Artificial Intelligence related to the case.” Such a request is likely overbroad on its face; not every use of GenAI will be relevant. For example, the fact that an employee used an AI writing assistant to polish grammar in an unrelated report should not open the door to examining every AI interaction that employee ever had. If a motion to compel arises over AI data, arguments can be made that the request is not proportional, given potentially massive volumes of irrelevant AI use. Proactive agreements in the ESI protocol can help here, too.
Protective Order and ESI Protocol Recommendations for AI
Lawyers can negotiate protective orders and ESI protocols before artifacts lead to disputes. Here are key clauses and considerations Maryland practitioners should consider adding:
Explicit definition of AI-related data can help clarify what constitutes “AI-Generated ESI” or “AI artifacts” in the agreement. For example, a definition might state: “‘AI-Generated Content’ means text, images, or other material created by a generative artificial intelligence tool, and ‘AI Metadata’ means information describing the use of such a tool (e.g., prompts, input data, output
inputs for any purpose outside this litigation, or (b) the producing party provides written consent.” Alternatively, a protective order can state that the receiving party will not utilize AI or machine learning tools on the producing party’s data without permission.
Conclusion
The rapid development of GenAI means attorneys must do what they can to keep up and be prepared for its introduction into their everyday practice. Building AI considerations into discovery practice is now part of competent representation. By understanding GenAI’s mechanics and outputs, counsel can better advise clients on preserving and producing this new form of ESI. As businesses continue to integrate generative AI and courts grapple with its fallout, proactive attorneys who are wellinformed about AI will be ready to ensure discovery remains fair, efficient, and protective of all parties’ rights in the age of AI.
Charles Mills is a federal judicial law clerk in the U.S. District Court for the Northern District of West Virginia (Martinsburg). He is admitted to Texas and has applied for admission to Maryland. He writes in his personal capacity; no pending matters are discussed.