Artificial Intelligence (AI) has rapidly transformed financial technology (FinTech) ecosystems, particularly in emerging economies where digital financial inclusion is both an opportunity and a challenge. While algorithm-driven FinTech platforms promise efficiency, personalization, and scalability, their success fundamentally depends on consumer trust and sustained digital engagement. This study investigates how AI-enabled FinTech systems influence financial inclusion outcomes by shaping trust perceptions, usage behaviour, and engagement intensity among users in emerging markets. A mixed-method framework combining computational modelling, survey-based behavioural analysis, and platform-level engagement metrics is employed across selected urban and semi-urban regions. Machine learning models are used to analyse trust determinants, while statistical and clustering techniques identify engagement patterns across demographic segments. The findings reveal that transparency of algorithms, perceived data security, and explainability of AI decisions significantly influence consumer trust, which in turn mediates digital engagement and long-term adoption. Results further indicate that AI personalization enhances inclusion only when accompanied by ethical governance and user literacy. The study contributes a scalable analytical framework for policymakers, FinTech designers, and financial institutions aiming to balance algorithmic efficiency with inclusive and trustworthy digital finance ecosystems in emerging economies.