There has been a lot of discussion about whether artificial intelligence (AI) will help or harm law students. The National Law Review’s article, The 2026 Top 50 Legal Innovators in Academia, provides a useful contribution to this discussion.
The article describes faculty and administrators at law schools across the country who are teaching students how to use AI thoughtfully and responsibly. Several schools now require AI instruction for all first-year students, including Case Western Reserve, Chicago, Mississippi Christian, UNLV, and Suffolk.
AI has enormous potential to help people create value, improve their work, and accomplish things they otherwise couldn’t. Realizing these benefits requires learning how to use AI effectively, exercising good judgment, and recognizing its risks and limitations.
The educators described below are helping students develop the skills to realize these benefits, undeterred by the stigma sometimes associated with using AI.
Examples of Teaching Students to Use AI Responsibly
Using AI to Develop Legal Skills
Kirsten Davis (Stetson) developed an AI-specific legal writing course and founded a national faculty learning group that now includes more than 550 members.
Alexandria Serra (USF) developed fifteen AI-powered tools for experiential learning, including simulated judicial questioning and witness preparation.
Carolyn Williams (North Dakota) developed approaches to assessment that emphasize students’ reading, reasoning, and professional judgment rather than relying exclusively on the final products they submit. She co-founded the Legal Writing and Generative AI Convo Group, a monthly forum that brings together hundreds of law faculty to share AI teaching practices.
Teaching Students to Question and Evaluate AI
Seth Chandler (Houston) developed an “augmented seminar” that lets students use AI to develop topics and test arguments while holding them fully responsible for sourcing, verifying, and defending every claim.
Gregory Duhl (Purdue Global) rebuilt his entire first-year Contracts course around AI, so students learn to supervise and critique AI rather than hide from it.
Nancy Rapoport (UNLV) co-created a course on the responsible use of AI in legal practice that emphasizes critically evaluating AI-generated content and keeping human judgment at the center of legal work.
Jennifer Wondracek (SMU) teaches students and practicing lawyers to develop practical AI workflows and recognize the tools’ weaknesses.
Developing Systematic Approaches
Naomi Goodno (Pepperdine) created a school-wide AI readiness initiative that connects practical AI skills with professional judgment, values, and responsibility to prepare students for effective lawyering.
Leah Chan Grinvald (UNLV) provided leadership as dean to establish required first-year instruction emphasizing professional judgment, human oversight, and decisions about when tasks should or should not be delegated to AI.
Dyane O’Leary (Suffolk) helped build an innovative program connecting legal writing, professional skills, legal technology, generative AI, ethics, and legal services.
The NLR article provides more information about these educators and many others.
Caitlin “Cat” Moon, founding co-director of Vanderbilt’s AI Law Lab and co-director of its Program on Law and Innovation, has started a Substack series examining the positions law firms are hiring for and what those decisions reveal about how AI is changing legal work. The series will explore emerging roles, changing responsibilities, and what law students may need to learn to prepare for these developments.
What Can We Learn from These Initiatives?
There are many ways to incorporate AI into legal education. Some programs teach students to evaluate AI-generated work. Others use AI for simulations, legal writing, research, or practical exercises. The educational value of particular uses depends on the learning objectives, the tasks involved, and how students are taught to use the technology.
Educators developing constructive uses of AI generally take its risks seriously. Their programs emphasize independent reasoning, verification, ethical obligations, and professional judgment.
In my recent post, Getting Beyond Simple Stories About AI, I suggested that we should pay particular attention to how faculty and students actually use AI rather than relying on generalizations about its effects.
The educators described in the NLR article are trying different approaches to a difficult educational challenge. Their experiences can help us understand what works, what doesn’t, and why.
For faculty who want to incorporate AI into their teaching, learning to use it effectively will be an ongoing process as the technology continues to evolve. Starting with small experiments now can help them build experience, refine their teaching methods, and discover new opportunities to help their students learn.