The rapid growth of financial technology (FinTech) in emerging economies presents an opportunity to address long-standing financial inclusion gaps. Yet, adoption depends critically on cognitive trust—users’ rational confidence in a platform’s reliability, competence, and security. This study investigates how cognitive trust in AI-powered FinTech services influences adoption intentions and subsequent financial inclusion outcomes among urban millennials in India and Southeast Asia. Drawing on the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and trust theory, we develop and empirically test a structural equation model using survey data from 520 fintech users. The model integrates perceived usefulness, ease of use, and perceived security as antecedents of trust, with adoption intention as a mediator leading to actual usage and inclusion outcomes. Partial Least Squares Structural Equation Modeling (PLS-SEM) results reveal that cognitive trust is a significant driver of adoption, mediating the effects of ease of use and security on intention. Furthermore, adoption intention strongly predicts actual usage, which in turn enhances financial inclusion by enabling access to credit, savings, and digital payments. The findings highlight that while functionality and convenience matter, building trust through transparency, security assurances, and responsible AI deployment is essential for sustainable fintech growth. The study contributes to theory by extending TAM with trust-centric and inclusion outcomes, and offers practical insights for fintech firms and regulators to design trust-based strategies that foster financial empowerment in emerging economies.