As AI dismantles the entry-level work that has historically been used to train junior lawyers, law schools need to urgently redesign curricula, build AI-assisted teaching tools, and develop practice-ready graduates
Key highlights:
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Curriculum redesign must start now — One law school’s approach illustrates the necessity of mapping the entire curriculum to identify which skills to preserve, evolve, or build from scratch.
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Training faculty in AI use is critical — Faculty AI training should be a multi-layered approach including hands-on training with specialized legal AI tools, guidance on redesigning curricula, and more.
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AI simulations may be the key — Law school leaders need to act now by experimenting with small pilot projects and building simulation-based learning tools to replace the developmental depth that once came naturally in the first years of practice.
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The debate about AI consuming most of the work that teaches essential lawyering skills to junior attorneys is forcing a reckoning with the long-held assumption that law schools were never designed to produce practice-ready lawyers and that it was always the profession’s job.
Indeed, AI is forcing that uncomfortable truth into the open faster than anyone anticipated because essential lawyering work — the document review, contract markup, research memo creation — dictated how a junior lawyer learned to spot the issue buried on page 47, to sense when a clause was off, and to develop the instinct that no classroom can fully replicate. Now, as more law firms deploy AI to handle precisely those entry-level tasks, the organic training moments that used to define the first two to three years of legal practice are evaporating.
Nick James, Executive Dean, Faculty of Law at Bond University, and Co-Chair of the Council of Australian Law Deans, says he sees where this is leading. The ultimate results will be firms hiring fewer junior lawyers today because AI has taken over that entry-level work, James explains, adding that means there will simply be no pipeline of mid-level, experienced lawyers to draw from in three to five years. Indeed, this is a slow-moving crisis, already in motion, and yet to fully arrive.
This crisis lands at the center of what the AI and Future of Legal Practice (AIFLP) initiative exists to address because at the core of this crisis is what does being job-ready really means when the job itself is being redefined. Answering this question requires law schools, law firms, licensing bodies, and technologists to do something they have historically struggled to do — that is to think and act collaboratively.
Rethinking the curriculum before AI does it for you
Carmen Perez-Llorca leads IE Law School’s AI initiative and is steering the school’s efforts to embed AI across the curriculum. To do so effectively, her approach requires going back to a broader set of foundational questions in legal education such as: For what is legal education meant to prepare students? How do students learn to develop legal judgment? What makes legal advice genuinely valuable? And what skills are essential to deliver that value in an AI-enabled profession?
“Layering AI tools on top of an unchanged curriculum serves no one,” Perez-Llorca explains, adding that without answers to the fundamental questions, “you are just adding technology to a structure that was never designed to handle it.”
Check out how one law school professor is building AI simulation tools
IE law school is currently mapping its entire curriculum to determine which skills need to be preserved, which need to evolve, and which need to be built from scratch, while also using the AI-boosted curriculum to train faculty. Perez-Llorca describes the school’s faculty AI training as a multi-layered approach encompassing university-wide LLM training, substantive AI law curriculum review, hands-on training with specialized legal AI tools, guidance on redesigning curricula, and assessments to reflect students’ growing AI proficiency. Before students can be taught with AI, professors need to understand the tools themselves and how to use them in teaching, in simulation, and in assessment, she adds.
An AI tutor that meets students where they are
Bond University’s James says he has spent the last several months building an AI tutor designed to walk students through course material the way a patient, attentive instructor would. His vision for the AI teaching assistant supports the professor meeting students where they are. “It [the AI tutor] introduces the week’s topic, outlines learning outcomes, guides students through the readings, checks comprehension with short quizzes, and then adapts in real time based on how the student responds,” James explains, adding that the AI tutor will pull any student who is struggling deeper into the material until the learning outcome is achieved. “The conversation never stops until the learning does.”
However, James is careful to draw a clear distinction about what the tutor replaces and what it does not, stressing that AI is a substitute for the lecture recording, the static reading list, or the passive video watched at midnight before an exam — but it chiefly exists to support the law professor. This approach frees up class time, turning it from content delivery to more meaningful the time between the human instructor and students, he adds.
Act by design or default
The approaches by both Perez-Llorca and James point to a way to address the question of disappearing tasks that teach essential lawyering skills as well as shift the center of gravity in legal education toward ways to foster developmental skills and legal judgment. Indeed, inertia is not a strategy, and law school deans and associate deans can be at the forefront of this fight by taking decisive action, including:
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- Experiment freely — Investigate with AI on your own by starting small with a pilot project.
- Strategically assign where AI goes — Decide where AI belongs in the curriculum, such as in courses focused on legal research and drafting as they become commoditized by AI. Also, determine in which instances AI does not belong, such as counseling clients through ambiguity, navigating ethical complexity, and advocating persuasively. Make sure these all remain led by human lawyers.
- Focus on skills — Map your law school’s curriculum by identifying which skills need to be preserved, which skills need to evolve, and which need to be built from scratch.
- Build AI-assisted teaching tools — Make experiential and simulation-based learning central to the curriculum.
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“The choice is between dealing with this crisis by design or by default,” James says, noting that the pipeline problem he described is already in motion while the practitioners, educators, technologists, and licensing bodies that need to solve this together are not yet consistently in the same room.
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