Honing legal judgment: The AI era requires changes to how lawyers are trained during and after law school

2026-04-02 · Source: Thomson Reuters Institute · Field: Legal & Regulatory — Legal Technology (LegalTech), Regulatory Affairs & Government Relations, Legal Education & Training · Depth: Intermediate, medium

Summary

The legal profession must fundamentally alter how lawyers are trained, both during and after law school, to prevent AI from eroding critical legal judgment skills, according to a Thomson Reuters Institute white paper and analysis by Jordan Furlong. AI's automation of entry-level tasks like research and writing, traditionally crucial for developing judgment, necessitates a new approach. The article proposes a three-pillar system: integrating work experience into legal education, decomposing legal judgment into teachable micro-skills (e.g., pattern recognition, ethical judgment), and incorporating AI as a thinking partner with clear standards and verification protocols. A significant challenge is funding this overhaul, with a proposed "legal education fund" supported by a small percentage of legal services revenue to subsidize residencies and curriculum development, requiring unprecedented coordination across law schools, employers, and state regulators.

Key takeaway

For legal educators and regulators designing future curricula, you must coordinate across institutions to integrate work-based learning and define legal judgment as teachable micro-skills. Proactively establish clear AI usage standards and secure dedicated funding, such as a legal education fund, to avoid a "lost generation" of lawyers lacking essential judgment in an AI-driven legal landscape.

Key insights

AI's impact on legal training necessitates a coordinated, profession-wide overhaul to preserve and develop legal judgment.

Principles

• Work-based learning enhances practical judgment.
• Decomposing complex skills enables effective teaching.
• AI integration requires clear standards and verification.

Method

A proposed system integrates work experience (like medical residencies), breaks legal judgment into micro-skills (e.g., pattern recognition, ethical judgment), and phases AI use with verification protocols.

In practice

• Implement mandatory supervised postgraduate practice.
• Define legal judgment via micro-skills for targeted teaching.
• Introduce AI gradually, with verification logs and "attack-the-draft" drills.

Topics

• AI in Legal Education
• Legal Judgment Development
• Lawyer Training Reform
• Work-Integrated Learning
• Legal Education Funding

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Editorial summary, takeaway, and curation by AIssential. Original article published by Thomson Reuters Institute.