The rapid proliferation of FinTech innovations has reshaped payment behaviour across urban India, with the Unified Payments Interface (UPI) emerging as a dominant retail rails. This empirical study investigates whether and how AI-enhanced features embedded in UPI platforms influence adoption and measurable business outcomes among Micro, Small, and Medium Enterprises (MSMEs) in urban Mumbai, with a focus on establishments in Andheri West. Using a structured survey of 150 MSME owners/managers, the research operationalises determinants such as perceived ease of use, transaction security, AI-driven analytics (fraud alerts, cash-flow forecasting, automated reconciliation), cost efficiency, and trust in digital infrastructure. Statistical analysis uses exploratory factor analysis, reliability testing, and structural equation modelling (PLS-SEM), supplemented by multiple regression, to estimate the direct and mediating effects of AI capabilities on business outcomes (revenue growth, cash-flow stability, and customer retention). Results indicate that AI-enabled security and analytics features significantly increase UPI adoption intent and are positively associated with short-term operational efficiency and improved financial transparency. The study concludes with policy and managerial recommendations: targeted digital literacy programs for MSMEs, collaborative AI-infrastructure development between payments networks and private partners, and tailored incentives to accelerate secure AI integration in merchant payment flows. Findings contribute original, place-based evidence to the literature on FinTech adoption and MSME development in emerging urban ecosystems.