AI in Defense Litigation: Strategic Opportunities and Critical Safeguards

Artificial intelligence (AI) is already altering the daily realities of legal practice. In 2024, 31% of attorneys reported personal use of generative AI compared to 21% of law firms. Some firms have carefully incorporated AI into their research process, while others are hesitant.   

The early verdict is that AI can be helpful when used strictly as a tool. Ultimately, a licensed (human) attorney must review all materials created by AI, especially those related to the law. 

AI Legal Risks to Avoid 

Mistakes in legal filings existed long before AI, so the problem itself isn’t new. However, AI usage creates new potential risks for attorneys and law firms. In 2025, the state court of appeals sanctioned a Utah attorney due to false case citations generated by ChatGPT. The filing included references to a nonexistent case, Royer v. Nelson, along with other unrelated citations.  Opposing counsel flagged the errors, noting the material was unverifiable in any legal database. 

A federal judge is considering sanctions and potential fines against another firm after attorneys filed two briefs with five false case citations generated by ChatGPT. A partner admitted to using the tool without verification, and the firm apologized. This is a clear example of how AI offers significant risks in litigation if not managed correctly. 

Current State of AI Adoption in Defense Firms 

AI is beginning to reshape litigation, but its role in defense practice remains unsettled. Some organizations are experimenting aggressively while others avoid it entirely, reflecting uncertainty about its value and risks.  

The question is not whether firms should use AI, but how. Attorneys must evaluate which applications improve case preparation without undermining credibility in court. When treated as a regulated tool, not a substitute for legal judgment, AI can provide a strategic edge while preserving authority with judges and juries. 

The Non-Negotiable Boundary of Client Confidentiality 

Client confidentiality is the most critical consideration in AI utilization. Open systems that transmit sensitive case information outside a firm’s firewall are unacceptable. This standard should guide adoption across the board.  

Firms exploring AI should confirm whether the platform processes and stores data internally or externally, whether outputs are logged, and whether confidential materials are exposed to third-party access or fed into a Large Language Model (LLM) for AI training purposes. Client welfare and data integrity must be guaranteed; no efficiency gain is worth the risk.  

Productive and Practical Applications of Legal Artificial Intelligence 

AI is being applied in defense litigation well beyond legal research. And its applications are no longer speculative. They are already in use, primarily by larger firms with the resources to test and monitor such systems. The opportunity for defense counsel is not in replacing traditional preparation but in enhancing it. AI can review documentation more efficiently, spot specific issues quickly, help with strategy, and streamline trial readiness. 

Deposition Analysis 

For example, in deposition analysis, AI can be trained on years of company representative testimony. Reviewing large volumes of transcripts and video highlights inconsistencies, contradictions, and nonverbal cues that might otherwise be missed. This shifts deposition prep from an exhausting manual process to a faster, more accurate review, freeing up defense teams to focus on strategy. 

Implications of AI for Cross-Examination 

As AI becomes embedded in business processes – from medical imaging to transportation tracking – defense witnesses increasingly face lines of questioning in cross-examination where AI could have been used. 

Defense counsel must anticipate this line of attack and prepare witnesses accordingly. Mock deposition questions about AI, explanations for when it was or wasn’t applied, and strategies to counter claims of negligence tied to its absence should all be built into preparation. Failing to address it leaves witnesses vulnerable to surprise challenges. 

Expert Witness Strategy 

AI can also be helpful with expert witness strategies; it can gather and examine previous deposition and trial transcripts of a frequently hired expert witness to identify inconsistencies or weak points that could otherwise be overlooked. Through this application, AI provides defense attorneys with a cross-examination plan customized to the expert’s past testimony. It can also speed up the case-building process by sorting through data at scale and directing attorneys toward areas that require a more thorough human review. 

Accuracy and Risk Management 

Opportunities don’t come without risk. AI tools, particularly those not tethered to trusted legal databases, can produce fabricated cases called “hallucinations” or misinterpret records. Attorneys who place blind trust in these outputs risk everything from courtroom embarrassment to potential sanctions. 

Mitigate AI Usage Risk Through Processes 

Risk management requires a multifaceted and structured approach. No AI output should reach a pleading, motion, or courtroom presentation without being thoroughly checked by a licensed attorney. Firms can establish internal protocols for AI use and define when it is acceptable, who oversees its outputs, and what verification steps are mandatory. Such protocols help lower the risk of errors, and avoiding unnecessary risks outweighs the benefits of speed. 

Accuracy and Credibility 

Losing credibility as an attorney or firm is not worth speed. The cost, quality, and time triangle provides a good perspective on this. This model suggests that in any project, you can only optimize two factors at the expense of the third. For example, to deliver high quality quickly increases costs, and reducing costs may require sacrificing speed or quality.  

This system applies directly to law. Using AI in defense litigation to speed up and keep costs lower by not investing in human checks of the material will inevitably lead to a loss of quality. Defense attorneys cannot afford to lose credibility by presenting or utilizing unvetted AI work. Strategic use means leveraging the tool, not outsourcing judgment to it. 

Strategic Use, Human Oversight 

The future of AI in defense litigation will be defined less by technology itself and more by how defense counsel controls it. Firms that treat AI as an unmonitored shortcut may face sanctions, credibility loss, fines, and malpractice exposure.  

Firms that treat it as a strategic asset that can accelerate data review utilize it to gain efficiency without sacrificing reliability or quality. The key is human oversight. Though AI can read a thousand transcripts in a couple of minutes, it is not reliable without human intervention and oversight. Defense firms may protect their clients and maintain competitiveness by integrating AI into current professional standards rather than replacing them. 

Improve Litigation Management with Courtroom Sciences 

Undoubtedly, AI applications in defense litigation are here to stay. They are already influencing research and case preparation. However, the adoption curve will not be determined by technology alone. It will depend on how defense attorneys manage confidentiality and enforce accuracy safeguards. Defense firms that engage thoughtfully and with strict human oversight will be better positioned to avoid risks.  

Courtroom Sciences helps attorneys efficiently navigate litigation by providing psychological expertise, science-backed data, and expert support for all phases of litigation. Learn how CSI’s litigation consulting experts can improve outcomes for your next case.  

Speak with one of our experts to get started. 

By Courtroom Sciences, based on insights from The Litigation Psychology Podcast, Episode #177 – Artificial Intelligence (AI) in Litigation