Technical Feasibility Of Artificial Intelligence-Based Technology For Implementing International Agreements

ISBN

978-607-8964-36-9

Fecha de publicación

13-02-2026

Licencia

D. R. © copyright 2026. Laura Fabiola Machuca Martinez y Julio Ale-jandro Santillan Becerra

Todos los contenidos de esta obra se comparten bajo la licencia Creative Commons Atri-bución/Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0). Esto implica que no está autorizado el uso comercial de la obra original ni de las eventuales obras derivadas, las cuales deberán distribuirse bajo la misma licencia que rige la obra original. No obstante, se permite a terceros compartir el contenido siempre y cuando se reconozca debidamente la autoría y la publicación original en esta editorial.

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Juan Vasquez
INTERNATIONAL INSTITUTE FOR INTELLIGENT TECHNOLOGY ADOPTION IN THE LAW
Enrique Sanchez Jr.
INTERNATIONAL INSTITUTE FOR INTELLIGENT TECHNOLOGY ADOPTION IN THE LAW
Daniel Kovach
KOVACH TECHNOLOGIES

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This article assesses the feasibility of deploying artificial intelligence (AI) to enhance treaty compliance within the complex U.S.–Mexico bilateral relationship.  Faced with escalating administrative burdens, AI offers the potential to process vast data, detect anomalies, and optimize compliance mechanisms.  However, significant obstacles exist, including the divergence between U.S. common law and Mexican civil law traditions, conflicting data protection regimes, and ethical challenges such as algorithmic bias.  This paper proposes a technically feasible, multilayered reference architecture for a binational AI system designed to mitigate these risks through robust governance and human oversight.  It concludes that successful implementation depends not only on technology but on a pragmatic, incremental roadmap, starting with joint regulatory sandboxes, to build institutional trust and ensure that AI-driven compliance remains accountable, transparent, and aligned with the legal values of both nations.

Referencias

APEC Economic Committee (2021). FinTech Regulatory Sandboxes Capacity Building Summary Report. Asia-Pacific Economic Cooperation. https://www.apec.org/docs/default-source/publications/2021/3/FinTech-regulatory-sandboxes-capacity-building-summary-report/221_ec_FinTech-regulatory-sandboxes-capacity-building-summary-report.pdf?sfvrsn=387b04bc_1
Breña, C. M. (2025, August 6). Customs, the new battlefield of the U.S.-Mexico trade war. EL PAÍS English. https://english.elpais.com/economy-and-business/2025-08-06/customs-the-new-battlefield-of-the-us-mexico-trade-war.html
Dulka, A. (2023). The Use of Artificial Intelligence in International Human Rights Law. Stanford Technology Law Review, 26(2), 316-366. https://law.stanford.edu/wp-content/uploads/2023/08/Publish_26-STLR-316-2023_The-Use-of-Artificial-Intelligence-in-International-Human-Rights-Law8655.pdf
Eben, O., Loveth, R. G., & Bright, A. (2025). Ethical Considerations in Global AI Regulations: A Cross-Border Approach. https://www.researchgate.net/publication/392595695_Ethical_Considerations_in_Global_AI_Regulations_A_Cross-Border_Approach
European Crypto Initiative (n.d.). Differences Between a Regulatory Sandbox and Safe Harbor. https://eu.ci/differences-between-regulatory-sandbox-and-safe-harbor/
Ghoshal, R. (2025). Cross-border AI governance for legal tech: Standardizing ethical and legal norms in access to justice. International Journal of Law, Justice, and Jurisprudence, 5(1), 186-194. https://www.lawjournal.info/article/177/5-1-34-764.pdf
González-Hermoso, J., & Morales-Burnett, J. (2021). Lessons from Mexico on how the federal government can help build local infrastructure and urban planning capacity. Urban Institute. https://www.urban.org/urban-wire/lessons-mexico-how-federal-government-can-help-build-local-infrastructure-and-urban-planning-capacity

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