Akpareva, Wendy ORCID: https://orcid.org/0009-0003-2737-9153, Dimmock, John, Hargreaves, Robert
ORCID: https://orcid.org/0009-0006-8778-7417, Paskell, Tayla-Jade and Cheung, Timothy
(2026)
A critical review of AI in higher education: comparative insights from the legal sector.
The Law Teacher.
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Abstract
Artificial intelligence (AI) is rapidly reshaping higher education through tools such as automated assessment, predictive analytics, intelligent tutoring systems and learning analytics. This paper reviews UK and international literature to examine both the opportunities and risks created by AI’s integration into universities. Evidence suggests that AI can reduce academic workload, personalise learning and enhance inclusivity by tailoring support for diverse learners. It may also strengthen workforce preparation, particularly as governments (including the UK) invest in AI skills development and employers increasingly expect graduates to be AI-literate. However, these benefits are counterbalanced by concerns around consent, surveillance, privacy, accountability and academic integrity risks. A further barrier is uneven competence among students and staff, which can lead to unethical use, misinterpretation of outputs and inconsistent adoption across institutions, potentially widening existing inequalities. Analysis of AI adoption in the legal industry illustrates parallel dynamics: it suggests AI will augment rather than replace professional expertise, reinforcing the need for higher education to embed AI literacy, critical evaluation skills and ethical training across curricula. The paper concludes that universities should pursue balanced AI integration leveraging innovation while strengthening governance and standards and calls for future research into transparent institutional frameworks and cross sector ethical guidelines for responsible adoption.
| Item Type: | Article |
|---|---|
| Status: | Published |
| DOI: | 10.1080/03069400.2026.2661474 |
| School/Department: | London Campus |
| URI: | https://ray.yorksj.ac.uk/id/eprint/14679 |
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