Exploring the determinants of AI driven FinTech adoption by Indian farmers for sustainable agrarian economic development

This paper explores the transformative potential of AI-enabled FinTech in agriculture, an area relatively understudied compared to other industries that have benefited from such innovations. The study investigates important factors such as Social Influence (SI), Performance Expectancy (PE), Convenience (C), and Price Value (PV) and their significant impact on farmers' intention to adopt FinTech solutions. Empirical evidence is provided through the application of Structural Equation Modelling (SEM) using PLS4 on survey data from 266 farmers. The findings indicate that SI, PE, C, and PV strongly influence farmers' technology adoption, emphasizing the need for social interaction and knowledge sharing, especially in semi-urban and rural communities where social media is less prevalent. The study recommends that FinTech companies should enhance their offerings through interactive features, training, and educational programs, particularly around social gatherings, while governments should promote FinTech adoption by providing support services like lower loan interest rates and comprehensive education initiatives. The research highlights psychological and experiential factors as more critical than physical dimensions, positioning agriculture as a competitive sector. It also addresses the need to study technology adoption across different demographics, underscoring the importance of localized, rather than universal, FinTech strategies. Overall, this research advances knowledge on AI-driven FinTech adoption in rural economies, providing a basis for interdisciplinary collaboration and future technological advancements in agriculture.