Examining the Role of Basic Formal Education Quality and HDI in India

Abstract

This research looks into how Artificial Intelligence, or AI, might really change things for financial inclusion in rural India. You know, it checks out the upsides and the big roadblocks in using AI there. Basically, the goal is to figure out if AI tools can make financial services easier to get for folks in underserved rural spots, while also spotting the main limits in how these systems are being rolled out right now. The study uses a mixed-methods setup. It pulls in secondary data from real-world sources, a careful review of existing literature, and some qualitative looks at how rural financial outfits in India are actually adopting AI. Findings point to some quick progress. AI-powered financial products have helped close access gaps for rural users and boosted efficiency in operations. Still, challenges stick around pretty stubbornly. Things like a strong bias toward urban areas show up a lot. There's not enough deep dive into skills needed, no solid causal models to explain causes and effects, and state-level data that's spotty in quality. Oh and, the big gap here is the lack of solid, India-focused empirical stuff, plus detailed breakdowns on how skills affect performance. That kind of shortfall makes it hard to come up with full-on policy advice. Some suggestions for the future are building standardized datasets, better casual modelling setups and including variables on skills and demographics. What makes this study stand out is the way it stacks up against global research. It emphasizes on India’s combination of rural differences and infrastructure problems which require AI that is modified to meet these needs.