Diffuse AI // May 12, 2026
The Structural Barriers to AI Lawyers
Published in Diffuse AI, this piece examines why legal AI adoption still runs into structural limits inside real practice despite the profession looking tailor-made for automation.
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.
Live publication
The full essay is now live at Diffuse AI. Open the original publication for the complete piece.