This study explores how Artificial Intelligence (AI) can facilitate financial inclusion and enhance banking services to support rural entrepreneurship development in Odisha. Through focus group with 15 financial service providers (banks, fintechs, and NGOs) and 30 rural entrepreneurs across four socioeconomically diverse districts Sambalpur, Ganjam, Mayurbhanj, and Khurda. Thematic analysis revealed critical barriers like infrastructural deficits, low digital literacy, and poor trust in AI-mediated banking among entrepreneurs, alongside providers’ challenges in mitigating algorithmic bias and operational costs. Both groups recognised the potential of AI to enhance credit access, market insights, and business scalability. The findings also explored the necessity for multi-stakeholder collaboration to develop context-specific solutions, including vernacular AI interfaces, offline-capable tools, and SHG-driven digital literacy programmes. Policymakers are urged to prioritise rural internet service expansion, solar-powered kiosks, and gender-inclusive training programs to bridge adoption gaps. This research provides interesting insights into the dual role of AI as an enabler and disruptor in financial inclusion, proposing strategies to align technological innovation with socio-economic landscape rural Odisha.

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AI-Driven Financial Inclusion and Banking Services for Rural Entrepreneurship in Odisha

  • Niladri Bihari Das,
  • Suman Kalyan Chaudhury,
  • Sharada Prasad Sahoo,
  • Smruti Ranjan Das,
  • Narayana Maharana

摘要

This study explores how Artificial Intelligence (AI) can facilitate financial inclusion and enhance banking services to support rural entrepreneurship development in Odisha. Through focus group with 15 financial service providers (banks, fintechs, and NGOs) and 30 rural entrepreneurs across four socioeconomically diverse districts Sambalpur, Ganjam, Mayurbhanj, and Khurda. Thematic analysis revealed critical barriers like infrastructural deficits, low digital literacy, and poor trust in AI-mediated banking among entrepreneurs, alongside providers’ challenges in mitigating algorithmic bias and operational costs. Both groups recognised the potential of AI to enhance credit access, market insights, and business scalability. The findings also explored the necessity for multi-stakeholder collaboration to develop context-specific solutions, including vernacular AI interfaces, offline-capable tools, and SHG-driven digital literacy programmes. Policymakers are urged to prioritise rural internet service expansion, solar-powered kiosks, and gender-inclusive training programs to bridge adoption gaps. This research provides interesting insights into the dual role of AI as an enabler and disruptor in financial inclusion, proposing strategies to align technological innovation with socio-economic landscape rural Odisha.