In her first six months as dean at the University of San Francisco School of Law, Johanna Kalb heard a consistent message from alumni across sectors: law students entering the profession today will step into a career that looks meaningfully different from the one they left. Kalb responded by backing faculty members who were already experimenting with AI, integrating it into the legal writing program, and giving students a formal role in shaping the school's AI policy.
Start with faculty already in motion
Kalb identified professors Nicole Phillips and Megan Hutchinson, who had been conducting their own experiments and building tools in their classrooms. Rather than convening a task force, she gave them resources and institutional backing. This allowed the school to embed shared AI learning outcomes across its legal research, writing, and analysis program in the second semester of the 2024-'25 academic year.
The legal writing program was a deliberate starting point because it had existing momentum and a structure where faculty had autonomy while supporting each other.
Expand through voluntary workshops
Over the summer of 2025, Phillips and Hutchinson ran optional hands-on workshops for the broader faculty. "Faculty learn from other faculty," Kalb said. "They don't want a vendor to come in and sell them. They're not interested in having somebody from central administration try to tell them how they can teach better. But listening to a colleague who really understands the work that they do is very helpful."
Some faculty began integrating AI learning outcomes into their elective courses, creating a visible proof of concept before any requirements were introduced. Kalb also expanded AI learning outcomes into two required courses on evidence and professional responsibility. The professional responsibility inclusion was straightforward given the ethical dimensions of AI use in legal practice.
Let students shape the policy
When USF rolled out access to the AI platform Claude, student feedback raised questions about AI's social, environmental, and democratic impacts - a reflection of the school's Jesuit and social justice identity. Kalb chose to involve students directly. She convened a 15-person student advisory group that conducted interviews and surveyed one-third of the student body. The group drafted AI principles that were later adopted by the faculty.
The process uncovered a shared concern: both faculty and students worried that AI would erode critical thinking rather than develop it. "We now have a shared sense of where the community is and what our concerns are," Kalb said. "That allows us to speak in a common language as we talk about why and how we're doing this."
Commit to learning alongside students
Kalb advises faculty to integrate AI tools into their own lives, experimenting where stakes are low to notice their evolution. "It's hard to regulate and teach these tools in the abstract," she said. Some students arrive at law school with more familiarity with AI tools than their professors, which she sees as an opportunity to shift the classroom dynamic toward co-creation.
This perspective can turn the stress of keeping up into collaboration, she added.
Why this matters for educators
Kalb's approach offers a model for building change agility in any educational institution: build on existing faculty experiments, make participation voluntary before mandating, and treat students as partners in policy design. The result is a shared language around AI that addresses real concerns rather than imposing top-down directives.
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