Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting

David Autor, Tanya Rodchenko, Josh Martin, Zanna Iscenko, Scott Strand, David Pearl and Melissa Ferere

No 35720, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: AI assistance in expertise-intensive work presents a tension between performance and learning: AI tools may raise the quality of the work a professional delivers while stunting the expertise they would otherwise develop in producing it. In a pre-registered three-month randomized controlled trial, we gave 133 practicing patent lawyers at eleven U.S. intellectual property law firms access to a custom AI patent drafting assistant and measured both their performance while using AI and their professional judgment afterward without it. All work was scored by blinded expert patent attorneys. AI access raised the quality of work delivered on benchmark patent drafting tasks at 10 days (0.34 SD, ? = 0.03) and 90 days (0.38 SD, ? = 0.01), with larger gains among junior lawyers. After three months, all subjects redlined an existing patent application without AI, a core task of patent practice that requires expert judgment. Treated lawyers outperformed controls by 0.32 SD (? = 0.04), but this advantage was concentrated entirely among senior lawyers (0.45 SD, ? = 0.02). Junior lawyers showed no average gain. Their scores instead bifurcated, with sharply fewer mediocre scores offset by more poor and more good ones, suggesting that AI assistance served as a springboard for some juniors and a cushion for others. Foundational expertise may be a prerequisite for extracting durable skill from AI-assisted practice.

JEL-codes: I24 I29 J0 (search for similar items in EconPapers)
Date: 2026-09
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