Leveraging AI-Evidence in Money Laundering Cases in Mexico: its Rules of Evidence (according to SCJN’s resolutions) - Sanchez Reyes, Patricia Margarita (Law, State and Telecommunications Review, 2025)
[Purpose] To analyze the admissibility of AI-generated evidence in money laundering cases in Mexico, with an emphasis on how this type of evidence might be evaluated under existing SCJN resolutions. [Methodology/approach/design] This research uses a qualitative methodology, utilizing a comprehensive literature review of the SCJN’s judicial resolutions regarding evidence in money laundering cases. While no cases involving AI-generated evidence were found, the research examines current legal principles to anticipate how such evidence might be evaluated under the Mexican legal system. [Findings] The research shows that, although the SCJN has not yet addressed cases involving AI-generated evidence, existing legal guidelines provide a foundation for determining its admissibility. These findings provide a structured approach for the potential future evaluation of AI evidence in Mexican courts. [Practical implications] The findings of this research can help legal professionals, including judges and lawyers, understand how AI-generated evidence can be evaluated under the current legal framework. These findings will help shape future legal practices regarding the use of AI in the collection of evidence in money laundering cases. [Originality/value] This paper is among the first to explore the admissibility of AI-generated evidence within the Mexican legal system, providing valuable insights for legal professionals and policymakers on how AI technology aligns with legal evidentiary standards in money laundering cases.