Evolution of Artificial Intelligence within LegalTech-A Literature Review

DOI: https://doi.org/10.25147/ijcsr.v10i0.826

Abstract

Purpose – This research aims to provide an overview of the current state of research regarding the possible future use of AI in the legal domain and its impact.

Method – This research follows the guidelines proposed by Kitchenham and Charters (2007) for a systematic literature review.

Results – This study presents the current state of research on the use of artificial intelligence in LegalTech. This research shows that AI applications in the legal domain have existed for many years, but interest has grown sharply since around 2016. Across the literature, AI is used in a wide range of legal areas, and most papers focus on a single domain. A significant amount of research examines the justice systems. This study reveals that two major AI technologies are dominating the legal domain, namely, machine learning and natural language processing.

Conclusion – This review examines 91 studies and provides an overview of how AI is currently used in the legal domain.  Most studies focus on a single application domain. The reported benefits of using AI include improved efficiency and accuracy, reduced costs, and the ability to process large datasets without fatigue or human bias. However, the review also identifies major challenges such as liability, privacy risks, system complexity, and high implementation costs.

Recommendations – AI can be used to enhance the legal process and activities, but cannot yet replace human expertise.

Research Implications – Results show that current research highly focuses on specific legal domains, for example, lawyers, law firms, and judicial decision-making. Future studies can be open to other areas like legal education and public sector legal services.

Practical Implications – The findings demonstrate that legal practitioners and law firms can benefit by adopting AI to enhance efficiency, accuracy, and decision-making.

Author Biographies

Maarten S Looijenga, ir., University of Twente, The Netherlands

ir.drs. Maarten Sjoerd Looijenga is a Master's graduate in Business Information Technology from the University of Twente. His research focuses on natural language processing, machine learning, and transformer-based language models for the legal domain. His master's thesis explored the application of transformer models to Dutch legal texts. He also supports the implementation of AI solutions in professional practice to improve efficiency. Additionally, he is a qualified teacher with a strong interest in computer science and AI education.

Faiza Allah Bukhsh, Dr., University of Twente, The Netherlands

Dr. Faiza Allah Bukhsh is an Associate Professor in the Data Management and Biometrics group at the University of Twente. Her research focuses on machine learning, process mining, event-driven intelligence, and data privacy. She has collaborated with healthcare providers and industry partners, including KPN, Vodafone, Philips, and ING. She also leads initiatives supporting women in computing and has contributed extensively to research in privacy and data-driven technologies. Dr. Bukhsh earned her PhD from Tilburg University and completed postdoctoral research in cybersecurity at the University of Twente.

Jeewanie Jayasinghe Arachchige, Dr., Vrije University, The Netherlands

Dr. Jeewanie Jayasinghe Arachchige earned her PhD in Information Systems and Management from Tilburg University in 2013 and holds a Master's degree in Information Technology from Keele University. Her research focuses on conceptual modelling, ontologies, service-oriented design, and process mining. She is currently a lecturer in the Department of Computer Science at Vrije Universiteit Amsterdam and previously worked at the University of Twente. She has also served on program committees for several international conferences.

Frances Borkent, University of Twente, The Netherlands

Frances Borkent holds an LL.M. in Law and Technology from Utrecht University and currently works as a legal advisor specializing in privacy and data management. Her professional and academic interests lie at the intersection of law and technology, with a particular focus on data protection, encryption, and the legal governance of emerging technologies.

Maya Daneva, Dr., University of Twente, The Netherlands

Dr. Maya Daneva is an Associate Professor in the Services and Cybersecurity group at the University of Twente. She leads industry–university research collaborations and teaches in the Computer Science and Business & IT programs. Her expertise includes Requirements Engineering, Software Engineering, and Empirical Methods. Her current research focuses on digital transformation, crowdsourced software engineering, and large-scale Agile and DevOps practices, with an emphasis on security, accessibility, and resilience.

Published
2026-07-16
How to Cite
LOOIJENGA, Maarten S et al. Evolution of Artificial Intelligence within LegalTech-A Literature Review. International Journal of Computing Sciences Research, [S.l.], v. 10, p. 4292-4330, july 2026. ISSN 2546-115X. Available at: <//stepacademic.net/ijcsr/article/view/826>. Date accessed: 29 july 2026. doi: https://doi.org/10.25147/ijcsr.v10i0.826.
Citation Formats
Issue
Vol 10 (2026): Volume 10
Section
Articles
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