📖 Case Summary: Grymes Dev. Co. v Fodera

Courts are no longer treating AI-generated research errors as harmless mistakes. In this Richmond County Supreme Court decision, the court sanctioned counsel for relying on a fabricated case and invented quotation, conduct the court deemed a waste of judicial and party resources with real consequences for motion practice.

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⚡️ What Happened:

• The third-party plaintiffs’ attorney moved for summary judgment in a title-insurance dispute concerning undisclosed encroachments on a residential property.
• The attorney cited a case that did not exist in the memorandum of law. He also quoted language from the non-existent case, which was produced by an artificial intelligence (AI) too.
• Opposing counsel identified the false citation, prompting the third-party plaintiffs’ attorney to apologize and attempt to withdraw the motion “without prejudice.”
• Opposing counsel objected, arguing that they had expended significant resources to oppose the motion and that successive summary judgment motions are disfavored.

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📝 Court’s Ruling:

• The court agreed with the opposing counsel and concluded that the filing was frivolous under 22 NYCRR 130-1.1.
• The court also concluded that the memorandum of law was filed without reasonable inquiry and was wasteful of judicial and party resources.
• The court stated that the misuse of AI could not be excused as a mistake. It emphasized the growing issue of AI hallucinations in the law and reiterated that technology cannot replace an attorney’s independent professional judgment.
• The court sanctioned the third-party plaintiff’s attorney and awarded the opposing parties attorney’s fees. It also denied the summary judgment with prejudice.

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🧭 Why This Case Matters for Claims Handling:

• Sanctions = Direct Defense Cost Exposure: Courts are shifting attorney’s fees where AI misuse wastes judical and party resources, a risk that can materially affect reserves.
• Loss of Dispositive Motion Leverage: Denial of summary judgment with prejudice elimnates a key pressure point in settlement negotiations.
• Distorted Coverage and Exposure Assessments: AI-driven research errors can undermine early liability analysis and mislead carriers evaluating risk transfer or settlement authority.
• No “Good Faith” Safe Harbor for AI Errors: Courts are making clear that AI misuse is not excusable negligence; it is sanctionable conduct.

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✅ Key Legal Takeaways:

• Frivolous Conduct: New York courts are treating fabricated citations as frivolous conduct, requiring reimbursement of fees and imposing sanctions.

• Denial of a Dispositive Motion: Based on the research error, the court disallowed withdrawal of the motion and denied it. The court’s holding eliminated a major procedural tool for the third-party plaintiff, impacting litigation exposure, settlement posture, and coverage evaluations.

• Increased Policing of AI Hallucinations by the Courts: This case is one of multiple recent decisions that shows an increasing judicial intervention into improper AI-generated work.. See Augustin v Formula 3 Brooklyn Inc. and Mata v Avianca, Inc.

• Attorneys Must Be Diligent of Legal Research Results Generated by Artificial Intelligence (AI): Attorneys should verify all AI output with reliable legal research databases or the official reports. When legal filings are the product of more than one attorney, do not assume that the other attorneys have verified the cited cases and quotes.

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▌ Practice Takeaway: Courts are now sanctioning attorneys for AI-generated hallucinated citations, with real consequences for motion practice and litigation exposure.

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👉 Explore more New York decisions affecting claims handling, motion practice, and litigation strategy at New York Civil Law — Case Summaries & Legal Updates. Clearly Explained

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