The rapid uptake of AI in the financial industry has transformed how legal compliance, risk management, and decision-making are conducted. However, issues regarding the transparency, accountability, and legal compliance of emerging markets remain. This paper examines how data analytics mediates the relationship between the adoption of AI and legal compliance in the financial markets in Jordan. A quantitative research approach was employed, whereby data were gathered from financial institutions in Jordan and analyzed via SPSS and AMOS using Structural Equation Modelling (SEM). AI was found to have a significant and positive direct influence on legal compliance and a strong influence on data analytics capabilities. Additionally, data analytics was found to positively influence legal compliance and partially mediate the relationship between AI and legal compliance. This suggests that the outcomes of AI compliance are improved when additional analytics are employed that improve interpretability, transparency, and streamlining of the regulation. This study documents the empirical evidence from Jordan on the hitherto unexplored mediating role of data analytics in the AI-compliance literature. The findings have practical implications for financial institutions and regulators who wish to practice AI within the legal and regulatory constraints.