Leveraging AI-Evidence in Money Laundering Cases in Mexico: its Rules of Evidence (according to SCJN’s resolutions)

[Purpose] To analyzethe admissibility of AI-generated evidence in money laundering cases in Mexico, with an emphasis on how this type ofevidence might be evaluated underexisting SCJNresolutions.[Methodology/approach/design]Thisresearchusesa qualitativemethodology, utilizing a comprehensive literature review of the SCJN’s judicial resolutionsregarding evidence in money laundering cases. While nocases involving AI-generated evidence were found, the researchexaminescurrent legalprinciples to anticipatehow suchevidence might be evaluatedundertheMexicanlegal system.[Findings]Theresearch showsthat, althoughthe SCJN has not yet addressedcases involving AI-generated evidence, existing legal guidelines provide a foundationfor determining itsadmissibility. These findings provide a structured approach for the potential future evaluation of AI evidence in Mexican courts.[Practical implications]The findingsof this researchcan helplegal professionals, including judges and lawyers, understand how AI-generated evidence canbe evaluatedunderthe current legal framework. Thesefindings will help shapefuture legal practicesregardingthe use ofAI inthe collection ofevidence inmoney laundering cases.[Originality/value]This paper is amongthe firstto explorethe 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 launderingcases.