Generative artificial intelligence (“AI”) is reshaping litigation. For insurers and legal operations professionals, the immediate concern is not simply that AI can help lawyers work faster; it is that AI can also help self-represented - pro se - litigants generate pleadings, filings, legal arguments, and more legal paper for defense counsel to answer.
New Jersey’s courts have already acknowledged AI’s significance. The New Jersey Supreme Court issued preliminary guidance on lawyers’ use of AI in January 2024 through its Committee on Artificial Intelligence and the Courts, and the New Jersey Judiciary later announced a technology-related Continuing Legal Education requirement for attorneys that began in 2025. Together, those developments reflect a broader recognition that AI competence now affects legal practice, court administration, and litigation risk.
Most commentary has focused on lawyers’ use of AI. For insurers, however, the more disruptive development may be AI-enabled pro se litigation.
Publicly available AI tools can draft complaints, motions, discovery requests, and briefs in seconds. That lowers the practical barrier to filing suit and allows self-represented litigants to submit documents that look sophisticated even when the legal analysis is weak, inaccurate, or entirely fabricated. Unlike attorneys, pro se litigants generally do not receive formal training on AI risks, verification standards, or professional duty of candor, thereby increasing the likelihood that courts and opposing parties will encounter polished but unreliable filings. The New Jersey Supreme Court’s guidance expressly warns lawyers to verify AI output, and the same concern applies with even greater force when no lawyer is involved.
For people who cannot afford counsel, AI may seem like a low-cost substitute for legal representation. That accessibility has real upside, but it also creates a new cost center for insurers: filings that may appear credible on their face yet still require careful review, response, and court appearances.
That is the insurance problem in practical terms. AI can increase the volume and complexity of pro se filings without improving their legal merit. The concern is not whether an AI-generated filing will ultimately fail, but how much defense work is required to test, narrow, or defeat it.
A Growing Pattern of AI-Generated Errors in Court Filings
Recent decisions in New Jersey and elsewhere show a familiar pattern: AI-generated filings can contain invented authorities, misstated holdings, and unsupported arguments. One example is Mata v. Avianca, Inc., 678 F. Supp. 3d 443 (S.D.N.Y. 2023), where attorneys were sanctioned for submitting fictitious cases generated by ChatGPT. Other examples, many of which involve pro se litigants, include:
- Baker v. Rastelli Foods LLC, No. 24-cv-08882-ESK-AMD, 2026 U.S. Dist. LEXIS 64242, at *13 n.5 (D.N.J. Mar. 26, 2026) – Addressed a pro se litigant’s AI filing in a footnote, requiring the pro se litigant who had failed to heed warnings about improper AI filings to “provide PDF copies of each case cited both in the new or amended pleading and the original complaint filed.”
- McCarthy, P.A. v. United States DEA, 171 F.4th 245, 255 (3d Cir. 2026) – Majority and Concurring Opinions differing in opinion on the sanctions appropriate for an attorney filing papers with improper AI citations;
- Shaporov v. Levine, No. 22cv1150 (EP) (LDW), 2025 U.S. Dist. LEXIS 189369, at *37 (D.N.J. Sep. 25, 2025) – Noting generative AI without proper verification in violation of Federal Rule of Civil Procedure 11.
- Minchin v. Ascend Wellness Holdings, Inc., No. 25cv17576 (EP) (SDA), 2026 U.S. Dist. LEXIS 120794, at *18 n.12 (D.N.J. June 1, 2026) - While discussing pro se litigant’s prolix complaint, recognizing pro se litigant’s possible use of generative AI and requiring mandatory certification that the AI work product was diligently reviewed by a human being in accordance with the judge’s preferences.
- K.W. v. Ringwood Bd. of Educ., Civil Action No. 24-8293 (MAH), 2026 U.S. Dist. LEXIS 107809, at *7 (D.N.J. May 15, 2026) - In noting more than ten major deficiencies in case citations in pro se litigant’s briefs, Court ordered that “Plaintiff's counsel shall disclose in a letter to the Court whether he used generative artificial intelligence in drafting his filings, and if so, to what extent.”
- Powell v. Borough of Bergenfield, No. 23-cv-21399 (EP) (JRA), 2026 U.S. Dist. LEXIS 105024, at *11 (D.N.J. May 12, 2026) – In noting that plaintiff’s filing contains improperly cited case law and may have used generative AI, the Court reiterated, “Pro selitigants are not shielded from the sanctions offered by Rule 11” and ordered the plaintiff to: “file a letter on the docket within 21 days of this Order, indicating: (1) whether she used generative artificial intelligence (“GAI”) while drafting her Opposition; (2) if so, why she has not violated Federal Rule of Civil Procedure 11(b) and why sanctions should not issue.”
These decisions illustrate the operational risk: AI-assisted filings can trigger court scrutiny, verification disputes, and additional procedural steps, even before the merits are reached.
Longer Pleadings and Increased Defense Costs
The billing impact appears most clearly at the front end of a matter. Defense counsel must parse lengthy allegations, test whether cited cases are real and on point, identify procedural defects, and determine the most efficient response. Hearings may expand when the court must address citation problems, disclosure issues, or motions prompted by AI-generated overreach.
Early empirical work suggests this is more than anecdotal. Indeed, among roughly 2.8 million federal filings, the federal civil pro se plaintiff rate rose from 11.33% before widespread access to generative AI to 16.94% afterward. (See The New Pro Se: Generative AI and the Surge in Federal Civil Self-Representation, Or Cohen-Sasson, Miami Law & AI Lab, University of Miami School of Law, May 28, 2026). Additionally, AI-consistent complaints were more citation-dense and more likely to be dismissed earlier in the case. Id. These more formal-looking filings can still produce more defense costs for insurers, despite a lack of merit.
Strategic Challenges for Insurers
A case with limited exposure may still be expensive to unwind if it generates repeated motion practice, defective discovery requests, or multiple amended filings. In some matters, nuisance-value resolution may appear cheaper than litigating to dismissal; in others, a disciplined early motion strategy may be the better long-term control measure. Either way, insurers need clear visibility into why time is being spent and which actions are most likely to reduce total claim cost.
Courts may need to adapt procedural mechanisms historically reserved for exceptional circumstances to address this situation. Motions to dismiss, motions for a more definite statement, sanctions motions, and procedures addressing frivolous litigation may become increasingly important tools for managing AI-generated filings. Rule-based mechanisms designed to deter baseless litigation may need to be used more frequently as courts seek to balance access to justice with the efficient administration of civil litigation.
From an oversight perspective, the key is to align those tools with early case assessment, budget discipline, and reporting practices that explain not only what was done but also why it was cost-effective.
Conclusion
Generative AI expands access to legal information, but it also changes the economics of defending litigation. For insurers, the takeaway is straightforward: AI-assisted pro se litigation calls for updated oversight practices, early identification of AI-driven filings, disciplined budgeting, sharper reporting on cost drivers, and defense strategies designed to control costs while preserving strong outcomes.
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