From automation to augmentation: Economic implications of artificial intelligence in financial decision-making in India

Artificial Intelligence (AI) is fundamentally transforming India’s financial sector, shifting the paradigm from traditional automation-where machines replace routine human tasks-to human-AI augmentation, where AI enhances human judgment and organisational capabilities. This research article investigates the economic implications of AI adoption in financial decision-making across banking, fintech, insurance, and non-banking financial companies (NBFCs). Employing a mixed-method empirical strategy, the study analyses recent data (2020-2025) on AI’s impact on credit decisioning, non-performing assets (NPAs), fraud detection, operational efficiency, workforce dynamics, and financial inclusion. Drawing on text-mining of annual reports, sectoral surveys, case studies of leading institutions, and policy analysis, the findings reveal that AI-driven augmentation yields superior outcomes in risk management, customer experience, and cost efficiency, while simultaneously introducing challenges related to workforce transformation, algorithmic bias, data privacy, and regulatory oversight. Empirical visualisations-including pie charts, histograms, and line graphs-depict key trends in AI adoption, productivity gains, and inclusion metrics. The article concludes with policy recommendations for fostering responsible, inclusive, and sustainable AI integration in India’s financial sector.