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ARTIFICIAL INTELLIGENCE ADOPTION IN THE INDIAN BFSI SECTOR: AN EMPIRICAL ASSESSMENT OF OPERATIONAL TRANSFORMATION AND STRATEGIC IMPLICATIONS

Shraddha Gupta & Urvashi Shrivastava

Pesquisa Operacional2025https://doi.org/10.1590/0101-7438.2025.045.00292981article
AJG 1
Weight
0.37

What the paper says

This research presents a comprehensive empirical assessment of Artificial Intelligence (AI) adoption in the India’s Banking, Financial Services, and Insurance (BFSI) sector, examining its operational transformation and strategic implications. Through systematic analysis of current AI implementations, this study investigates how financial institutions are leveraging AI technologies to enhance operational efficiency, improve customer experience, and strengthen risk management frameworks. The research employs a mixed-methods approach, combining quantitative analysis of industry data with qualitative assessment of AI adoption patterns across 128 responding Indian BFSI institutions from a sample frame of 165 institutions during January 2023 March 2024, achieving a 77.6% response rate. Key findings reveal that 69% of Indian banks have implemented AI/ML solutions, resulting in 30-40% reduction in operational costs and 50% improvement in processing times. The study identifies critical challenges including data privacy concerns (cited by 62% of institutions), skill gaps in AI expertise (70% of institutions), and regulatory compliance complexities. This research contributes to operations research literature by providing empirical evidence of AI’s transformative impact on financial services operations and proposing a framework for strategic AI implementation in emerging economies.

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https://doi.org/https://doi.org/10.1590/0101-7438.2025.045.00292981

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@article{shraddha2025,
  title        = {{ARTIFICIAL INTELLIGENCE ADOPTION IN THE INDIAN BFSI SECTOR: AN EMPIRICAL ASSESSMENT OF OPERATIONAL TRANSFORMATION AND STRATEGIC IMPLICATIONS}},
  author       = {Shraddha Gupta & Urvashi Shrivastava},
  journal      = {Pesquisa Operacional},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1590/0101-7438.2025.045.00292981},
}

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ARTIFICIAL INTELLIGENCE ADOPTION IN THE INDIAN BFSI SECTOR: AN EMPIRICAL ASSESSMENT OF OPERATIONAL TRANSFORMATION AND STRATEGIC IMPLICATIONS

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.