In the rush to integrate Artificial Intelligence (AI) into legal education, an inconvenient truth has remained largely unspoken: the AI revolution is being shaped by infrastructures, ideologies, and institutions far removed from the realities of most classrooms in the Global South. While much has been written about cheating and academic integrity in the age of ChatGPT, there has been far less scrutiny of the colonial logic embedded in the very tools that legal educators are being urged to adopt. The result is not merely a digital divide, but a growing epistemic rupture.
At first glance, the adoption of generative AI in legal education appears to promise democratisation. AI tools can summarise cases, generate citations, draft essays, and even simulate client interviews. But a sobering asymmetry lies under this surface. Most of these tools are developed and trained within an environment that has digital literacy, reliable internet access, and sustained investment in legal technology. These datasets are Anglocentric and are built upon the legal corpora that highlight epistemologies and procedural priorities of Euro-American legal cultures.
For law students and educators in Pakistan, Bangladesh, or Kenya, the matter goes beyond mere ease of use; it touches on intellectual autonomy. If an AI model developed using the jurisprudence of the United States or Britain begins shaping a law student’s analysis, which legal system is truly being learned, and whose authority is quietly being endorsed?
The interaction of the Global South with AI is influenced not only by economic limitations but also by systemic exclusion from conceptual developments. Legal education in these regions faces significant challenges, including outdated syllabi, insufficient teaching resources, and restricted access to legal databases and academic journals. The introduction of AI technologies, rather than bridging gaps, risks widening existing inequalities. Institutions lacking reliable infrastructure or the means to procure proprietary AI platforms are left at a disadvantage, thereby creating a divided legal pedagogy between those with advanced access and those without.
As the western‑built AI platforms become routine, they usher in a form of data colonialism. Local statutes seldom appear in their databases and, when included, are often marginalised. As a result, the advice these systems issue tends to treat Global South jurisdictions as peripheral rather than authoritative sources. This is not merely a matter of representation but one of interpretive authority. Law students trained on such systems risk internalising a worldview in which their own legal systems appear underdeveloped, incoherent, or in need of ‘improvement’ through foreign models.
The problem is compounded by the lack of regulatory scrutiny or critical pedagogy in how these tools are deployed. In many law schools across the Global South, generative AI is introduced informally, often through student peer networks or administrative adoption of detection software. Rarely are students offered a critical lens to examine the assumptions underlying AI outputs or the biases encoded into the algorithms. There is no requirement to disclose the datasets on which these models were trained, nor is there any discussion about whether students are being asked to consent to their data being collected, stored, or processed by third parties.
Ethics, if addressed at all, is framed within narrow bounds: plagiarism detection, exam conduct, and academic integrity. What is omitted is a broader conversation about digital ethics in postcolonial contexts. There is little attention to the asymmetry of power that allows a handful of corporations and elite institutions to define the contours of legal intelligence. Nor is there adequate discussion on how to develop local AI tools that reflect the linguistic, doctrinal, and procedural specificities of Global South jurisdictions.
What would a decolonial AI pedagogy look like in legal education? First, it would involve resisting the passive importation of Euro-American platforms and advocating for open-source alternatives co-designed with local experts. Second, it would centre digital literacy not just as a technical skill, but as a critical practice: training students to ask who built a tool, whose interests it serves, and what epistemologies it reinforces. Third, it would treat law schools as sites of ethical resistance, capable of modelling alternative relationships to technology grounded in transparency, inclusivity, and local relevance.
UNESCO’s call for an ‘Ethics by Design’ approach to AI in education is an important starting point, but it must be adapted to the realities of postcolonial legal systems. Simply translating global frameworks into national policies will not suffice. What is needed is a pedagogy that emerges from the margins, not one that trickles down from the centre.
AI in legal education should not be an instrument of epistemic submission. Nor should it become another chapter in the long history of pedagogical dependency. The classroom must be reclaimed as a site where students can critically engage with AI, not merely consume it. Until legal education in the Global South reclaims its agency in this transformation, the promise of AI will remain hollow, its benefits accruing elsewhere, its risks disproportionately borne by those least equipped to navigate them.
The future of legal education cannot be built on borrowed code. It must be written, quite literally, in languages, contexts, and values that belong to those it seeks to serve.
