Regulating AI in Legal Practice: Challenges and Opportunities
DOI:
https://doi.org/10.70356/josapen.v3i1.47Keywords:
Artificial Intelligence (AI) in legal practice, Ethical and regulatory challenges, Algorithmic bias and transparency, AI governance and fairnessAbstract
The integration of Artificial Intelligence (AI) in legal practice is transforming the legal profession by enhancing efficiency and accessibility while presenting significant ethical and regulatory challenges. AI applications such as predictive analytics, automated document drafting, and AI-driven legal research hold immense potential to reduce administrative burdens, streamline case management, and improve access to justice. However, issues such as algorithmic bias, lack of transparency, and data privacy concerns raise critical questions about fairness and accountability in AI-driven decision-making. This study aims to analyze the dual landscape of challenges and opportunities associated with AI adoption in legal practice, emphasizing the need for balanced regulatory frameworks. A systematic review of existing literature was conducted to identify the obstacles and benefits of AI integration. Key challenges include algorithmic biases, inadequate legal frameworks, and the digital divide among legal professionals, while opportunities range from cost reduction to improved dispute resolution processes. The findings contribute to ongoing discussions on AI governance by proposing actionable strategies such as fairness audits, explainable AI practices, and targeted training programs for legal professionals.
Downloads
References
C. Patsakis, C. Patsakis, F. Casino, F. Casino, and N. Lykousas, “Assessing LLMs in malicious code deobfuscation of real-world malware campaigns,” Expert Syst. Appl., vol. 256, no. July, p. 124912, 2024, doi: 10.1016/j.eswa.2024.124912.
M. Balas, D. T. Wong, and S. A. Arshinoff, “Artificial intelligence, adversarial attacks, and ocular warfare,” AJO Int., vol. 1, no. 3, p. 100062, 2024, doi: 10.1016/j.ajoint.2024.100062.
M. Text, M. Sarvazyan, and A. Mikael, “TextMachina : Seamless Seamless Generation Generation of e e e,” 2024, doi: 10.1016/j.procs.2024.09.462.
N. T. Dinh and V. T. Hoang, “Recent advances of Captcha security analysis: A short literature review,” Procedia Comput. Sci., vol. 218, pp. 2550–2562, 2022, doi: 10.1016/j.procs.2023.01.229.
A. Meroño-peñuela, E. Simperl, A. Kurteva, and I. Reklos, “Jou pro of,” Web Semant. Sci. Serv. Agents World Wide Web, p. 100847, 2024, doi: 10.1016/j.websem.2024.100847.
A. Pesqueira, A. de Bem Machado, S. Bolog, M. J. Sousa, and R. Pereira, “Exploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticals,” Comput. Ind. Eng., vol. 198, no. September, 2024, doi: 10.1016/j.cie.2024.110655.
C. Cancela-Outeda, “The EU’s AI act: A framework for collaborative governance,” Internet of Things (Netherlands), vol. 27, no. July, p. 101291, 2024, doi: 10.1016/j.iot.2024.101291.
B. Attard-Frost, A. Brandusescu, and K. Lyons, “The governance of artificial intelligence in Canada: Findings and opportunities from a review of 84 AI governance initiatives,” Gov. Inf. Q., vol. 41, no. 2, p. 101929, 2024, doi: 10.1016/j.giq.2024.101929.
M. Mohsin, N. Shah, N. Shaikh, A. Thabet, and S. Belkhair, “International Journal of Medical Informatics Towards secure and trusted AI in healthcare : A systematic review of emerging innovations and ethical challenges,” Int. J. Med. Inform., vol. 195, no. December 2024, p. 105780, 2025, doi: 10.1016/j.ijmedinf.2024.105780.
D. B. Olawade, O. Z. Wada, A. C. David-Olawade, O. Fapohunda, A. O. Ige, and J. Ling, “Artificial intelligence potential for net zero sustainability: Current evidence and prospects,” Next Sustain., vol. 4, no. February, p. 100041, 2024, doi: 10.1016/j.nxsust.2024.100041.
I. Domor, Y. Sun, and E. Ileberi, “Machine Learning with Applications Artificial intelligence and sustainable development in Africa : A comprehensive review,” Mach. Learn. with Appl., vol. 18, no. July, p. 100591, 2024, doi: 10.1016/j.mlwa.2024.100591.
L. Carrasquilla-Díaz, A. De Luque-Pisciotti, and E. Lagos-González, “AI Adoption in Colombian Legal Practice: Challenges and Opportunities.,” Procedia Comput. Sci., vol. 241, pp. 508–513, 2024, doi: 10.1016/j.procs.2024.08.072.
C. Rigotti and E. Fosch-villaronga, “Computer Law & Security Review : The International Journal of Technology Law and Practice Fairness , AI & recruitment,” Comput. Law Secur. Rev. Int. J. Technol. Law Pract., vol. 53, no. April, p. 105966, 2024, doi: 10.1016/j.clsr.2024.106053.
S. Kempeneer, A. Pirannejad, and J. Wolswinkel, “Open government data from a legal perspective: An AI-driven systematic literature review,” Gov. Inf. Q., vol. 40, no. 3, p. 101823, 2023, doi: 10.1016/j.giq.2023.101823.
M. Marelli, “The law and practice of international organizations’ interactions with personal data protection domestic regulation: At the crossroads between the international and domestic legal orders,” Comput. Law Secur. Rev., vol. 50, p. 105849, 2023, doi: 10.1016/j.clsr.2023.105849.
A. Mantelero, “The Fundamental Rights Impact Assessment (FRIA) in the AI Act: Roots, legal obligations and key elements for a model template,” Comput. Law Secur. Rev., vol. 54, no. June, p. 106020, 2024, doi: 10.1016/j.clsr.2024.106020.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Yatama Zahra
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
