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Abstract

Four major generative AI engines—DeepSeek, Claude, ChatGPT, and Grok—are useful legal analysis tools for employment law practitioners. This Article presents the results of an experiment in which a transcript of a hypothetical client interview involving potential disability discrimination, retaliation, and wrongful termination claims was submitted to each AI system. The accompanying prompts requested identification and assessment of viable legal theories. The experiment demonstrates that contemporary generative AI performs sophisticated legal analysis comparable to experienced associates, correctly identifying major employment law claims including ADA violations, Title VII discrimination, OSHA retaliation, FMLA interference, and workers’ compensation retaliation. All four engines successfully spotted legal issues, assessed claim strengths and weaknesses, and suggested follow-up investigation—tasks that traditionally required eight to forty hours of junior attorney research time.

Significant limitations emerged, however, in case law citations, with most cited cases being non-existent or incorrectly referenced, though statutory and regulatory citations proved generally accurate and useful. The analysis reveals AI’s potential to transform law firm economics by dramatically reducing research time while maintaining analytical quality, though careful attorney oversight remains essential. The technology particularly benefits less experienced practitioners by providing comprehensive starting points for legal research, while experienced attorneys can use it for quality control and initial drafts. Generative AI serves as an effective “wingman” for employment lawyers, capable of replacing substantial junior associate work while requiring continued human expertise for client counseling, supervision, and final legal advice preparation.

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