Training Lawyers for the Generative AI Era
Conference highlights rarely occur at 9:00 a.m. on a rainy final day. Yet Training Lawyers for the AI Era: Building Learning Programs That Stick, moderated by Daniel Himmel of Legora, delivered exactly that at LegalWeek 2026.
Panelists Ian Nelson of Hotshot, Sarah Eagen and Victoria Albrecht of Cleary Gottlieb, and Corey Barnes of Crowell & Moring offered several practical takeaways:
1. Make training practical
Skip feature walkthroughs - they do not change behavior. Effective programs build a mindset for understanding how AI models work.
The strongest approaches focus on real workflows based on roles. Hotshot and Cleary emphasized training grounded in realistic scenarios—from M&A and litigation to even non-legal use cases like planning a dinner party, which lower barriers to entry while reinforcing core skills.
In practice, the most effective learning often occurs when tools are piloted on live matters. While this requires upfront operational investment—particularly around security, confidentiality, and system integration—it also allows lawyers to ask critical questions: Does it save time? Maintain quality? Fit existing workflows?
2. Adaptability defies assumptions
One somewhat counterintuitive panel observation: Senior lawyers are often more open to change.
Having navigated multiple waves of technological transformation—from fax to email to networked computing—they bring context and perspective.
Junior lawyers can exhibit greater caution. Even when personally familiar with generative AI, concerns about professional risk and evaluation can temper experimentation.
3. AI is reshaping training itself
AI is not only the subject of training, but also a tool for improving training programs themselves. Training teams are using AI to analyze performance data, assess learner progress, personalize learning, and accelerate content creation—making training more targeted and scalable.
4. The future is collaborative innovation
At Cleary, multidisciplinary teams of legal professionals, knowledge engineers, and data scientists are building solutions together, driven by a shared curiosity-driven, experimental mindset.
A notable shift: attorneys are increasingly prototyping ideas themselves—“vibe coding”—and partnering with engineers to refine them. This significantly shortens the path from concept to validation.
That said, experimentation does not replace technical expertise. Rapid prototyping can accelerate ideation, but scaling solutions efficiently still requires experienced developers.
The broader implication is clear: The era of an applications team building a finished product and handing it off to lawyers is fading. Collaborative development is the future.
5. Adoption is social
Peer example is the strongest lever. When partners and practicing lawyers demonstrate how they use GenAI tools in their own client work, new use cases spread quickly and organically.
Incentives matter too. If adoption is a priority, law firms and departments will need to encourage—and reward—attorneys for investing the time to up-skill.
Bottom line: Training alone isn’t enough. Real progress comes from aligning practical learning, culture, and collaboration..
👉 Curious: what approaches have worked in your organization when training professionals to adopt AI tools?
Further Reading on Training Design
