Reimagining Legal Education for the Future of Law

Across the two days, the conference brought together different perspectives on the challenges legal education is currently facing and what it may need to become. In doing so, it sharpened a number of connected questions about what should be preserved in legal education, what may need to be rethought, and, in light of developments such as AI, what kinds of lawyers law schools are trying to form.

‘Whose Freedom? Law, Power, and Social Justice’ ¹

Although I had half expected the conference to move straight into AI and its impact on legal education, Kirsty Brimelow KC opened it from a very different perspective. Her keynote focused on public protest and with that she focused the discussion on a more foundational legal question: Why does the right to public protest matter, and what does it reveal about the law today? It was an important reminder that legal education is not only about training students to operate within legal systems, but also about helping them understand the public, political, and democratic significance of law. Public protest is one of the clearest examples of law in action. It reveals how legal rights are shaped, contested, limited, and defended in public life. Engaging with such questions requires students not only to know the law, but also to think critically about how law functions in society, whose interests it protects, and how legal principles are interpreted in practice. In that sense, starting with public protest grounded the conference in a simple but necessary insight: legal education is always about more than doctrine alone.

AI as a central theme of the conference

Although the conference opened from a different angle, it did not take long for AI to emerge as one of its central themes. What stood out, however, was that the discussion was not reduced to whether students should or should not use AI, or more specifically GenAI. That quickly proved too narrow a frame. Across keynotes, parallel sessions and panels, AI ‘prompted’ a much wider conversation about best practices, the limits of automation, the kinds of judgement and reasoning that remain distinctly human, and the question of what legal education should continue to cultivate in students. 

In his keynote², Sir Geoffrey Charles Vos, Master of the Rolls, framed the issue in unmistakable terms: “Law teachers will be at the sharp end of the transition from where we are now to where we will need to be”³. He positioned legal education within a broader transformation of the justice system and the legal profession, making clear that this is not a marginal or temporary development, but a structural shift. His message was both reassuring and demanding. On the one hand he rejected the idea that lawyers will become obsolete, stating that “Lawyers will be needed as much, if not more, in the machine age”⁴. While on the other hand, Sir Geoffrey made clear that this does not mean lawyers will remain relevant in the same way as before. Their role, skills and added value will have to change. In a world in which clients increasingly arrive with machine-generated answers, lawyers will be valued less for simply possessing knowledge and more for being able to interpret, verify, explain and justify outcomes. That has direct implications for legal education. The task is not to abandon legal reasoning, but to make its underlying structure more explicit. As Sir Geoffrey put it: “We need a complete rethink of how we prepare our young lawyers for practice in the machine age”⁵. That concern – rethinking legal education in the ‘machine age’ – resurfaced in different forms throughout the conference. 

MILE’s Nicole Kornet approached the conference theme from a more ‘helicopter view’ and used Biesta’s three domains – qualification, socialisation, subjectification – to explain what AI reveals about legal education. Through these domains, she showed that AI does more than disrupt teaching methods or assessment practices. It exposes what law schools prioritise, what they leave implicit, and where tensions arise between training students in legal knowledge and skills, inducting them into the legal profession, and enabling them to develop independent judgement. Her contribution framed AI less as a standalone technological issue and more as a diagnostic lens for examining the actual and/or underlying purpose(s) of legal education. 

Several other speakers addressed broadly similar questions, though from different angles. Ksenia Lavrenteva focused on the limits of AI by asking what AI cannot know, thereby foregrounding the importance of context, interpretation and human judgement. Sarah Zaghloul moved beyond prompt engineering and towards the question of what law students should actually learn about AI, especially if they are to remain critical readers and accountable legal thinkers. In her account, the real issue is not whether students can obtain usable output from AI, but whether they can critically assess that output, identify what is missing, recognise what assumptions are embedded in it, and remain accountable for the reasoning they present as their own. Amy Man brought the debate into the domain of integrity, implementation and student experience, showing that AI raises not only questions of misuse, but also questions of independent authorship, fairness and pedagogical design. The Partner Panel with panelists Felix Steffek, Andy Unger and Adam Nicholls on ‘Cultivating the Next Generation Lawyer: Merging Legal Judgement, Strategic Thinking, and AI Fluency in Legal Education’, added a professional perspective. Their discussion underlined that legal education must respond not only to new technologies, but also to a changing legal services market and shifting expectations of legal expertise. Future lawyers will not simply be rewarded for knowing more. They will be valued for their ability to assess reliability, exercise judgement, translate complexity, and provide strategic and normative guidance in situations where machine output alone is insufficient.

The keynote from Kirsten Maslen offered a clear framework for bringing many of these observations and concerns into sharper focus. Rather than discussing AI use in abstract terms, She highlighted a number of intellectual moves that legal education now needs to make more explicit: question formulation, source judgement, verification, comparison and critique, judgement and proportionality, and authorship and accountability. None of these are new. They have long been part of legal thinking and practice. What has changed is that, in an AI-rich environment, legal education can no longer assume that such capacities will automatically become visible in students’ work. Maslen’s keynote underlined a broader point that resonated throughout the conference: the core of legal education is not disappearing, but it does need to be articulated, taught and assessed more deliberately.

The conference suggested a number of important takeaways for thinking about AI in legal education. First, the conversation on integrity needs to move away from panicking about plagiarism and more towards pedagogy. The challenge is not simply how to detect misuse after the fact, but how to design legal education in ways that cultivate independent reasoning, critical source use, and ownership of work from the outset. Secondly, the conference made clear that AI cannot be approached in all-or-nothing terms. Not every use is equally defensible, useful, or educationally meaningful. Much depends on context: how demanding verification is, how serious the consequences of error are, and what kind of judgement the task requires. Where output can be checked relatively easily and the stakes are low, AI may add genuine educational or professional value. But where verification is demanding and the consequences of error are more serious, claims of efficiency become much less persuasive. In those contexts, AI can produce only the appearance of competence, while masking weak judgement or insufficient scrutiny. 

This points to a broader conclusion: the real issue is not whether AI should be embraced or rejected, but how legal education can engage with AI without losing sight of judgement, responsibility, and the conditions for meaningful learning.

Reimagining Legal Education beyond Technology

Although AI was one of the conference’s central themes, it was not the only lens through which legal education was being reconsidered. The panel session by Foluke Adebisi, Jade Kouletakis and Renginee G. Pillay shifted attention from technology to the deeper structures that shape legal education itself. Their contributions highlighted that reimagining legal education is not only about updating methods or responding to new tools. It also requires attention to what is taught, whose voices are centred, and which histories, perspectives, and epistemologies continue to shape legal knowledge and the curriculum of law schools. In that sense, legal education is not neutral, and curriculum design is closely connected to questions of power, exclusion, and inherited legal and institutional traditions. 

Kouletakis linked ‘decolonisation’ with AI in a very practical, but theoretically grounded way⁶. Drawing on Freire, Fricker and Quijano, she explored how AI might be used as a teaching tool to help identify bias, omissions, and gaps in representation within legal materials and the curriculum. According to Kouletakis, AI can potentially be used as a tool for making patterns of exclusion and inherited assumptions more visible. Together with Adebisi’s focus on race, empire, and knowledge production, this added a broader dimension to the conference discussion. Rather than presenting decolonisation as a finished goal, the panel invited reflection on what legal educators can do in practice: teaching more deliberately, exposing students to different perspectives, and encouraging them to think critically about whose knowledge counts and why.

Where does that leave us?

As a whole, the conference showed that legal education must respond to more than technological disruption. It must also respond to a changing profession, changing expectations of students, renewed scrutiny around integrity and authorship, and long-standing questions about canon, race, power, and colonial inheritance. That is why the theme of reimagining legal education was so fitting. The conference did not suggest that legal education needs to abandon its intellectual foundations. Quite the opposite. It showed that those foundations remain essential, but they must now be taught, assessed, and discussed more explicitly. Legal education needs to be clearer about what counts as legal judgement, where the line lies between using a tool and outsourcing reasoning, and how students come to know, justify, and defend the choices they make. It must do so in a world in which law is shaped not only by internal legal reasoning, but also by wider societal, technological, institutional, and global developments. 

If there was one overarching takeaway from ALT 2026, it was this: reimagining legal education is not only about adapting to the future of law, but also about making explicit what legal education should perhaps always have made visible. Many of the questions raised throughout the conference also connect closely to questions that are central to my own research on the impact of AI of legal education. It was precisely this breadth of perspectives and depth of discussion that left us inspired, with a head full of new ideas and much to continue thinking about.

1. Title of the Keynote Speech by Kirsty Brimelow KC
2.  Sir Geoffrey Charles Vos, Master of the Rolls, Lawyers and Legal Education in the Machine Age [Keynote Speech], ALT Conference 2026, Exeter, UK (accessed online: https://www.judiciary.uk/wp-content/uploads/2026/04/Exeter.Law-Teachers.nf3_.pdf) 
3. Ibid., p. 10, no. 41
4. Ibid., p. 1, no. 3
5. Ibid., p. 9, no. 37
6. I deliberately used brackets around the word decolonisation here, because – as I learned – this term needs to be used with care, and can be misleading if it suggests that law schools can somehow fully decolonise themselves while remaining embedded in sectors and institutional structures fundamentally resistant to such change.