Diffuse AI // Forthcoming
The Structural Barriers to AI Lawyers
Forthcoming in Diffuse AI, led by Daniel Bashir of OpenAI and The Gradient Podcast, Clara Collier of Asterisk, and Charles Yang of the Center for Industrial Strategy, this piece examines why legal AI adoption still runs into structural limits inside real practice.
Summary
The essay starts with a puzzle: law looks tailor-made for AI, yet most firms have only experimented at the margins. From there, it outlines the structural reasons diffusion has been slower than the headlines suggest.
It then traces four pressure points: the legal-data moat around research tools, the messy operational reality inside firms, the tension between AI efficiency and billable-hour economics, and the widening supervision gap as systems move from assistant to primary work producer.
The piece closes by asking what these barriers mean for access to justice. If legal AI cannot move from demos to reliable adoption, the people most likely to be left waiting are the millions who already cannot afford meaningful legal help.
Original publication
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