Contextual Background of the Study: The rapid integration of Artificial Intelligence (AI) into the banking sector has emerged as a defining trend in global financial services, with technologies such as machine learning, natural language processing, predictive analytics, and robotic process automation reshaping core banking operations. Despite growing adoption, the sector continues to grapple with challenges related to data privacy, algorithmic bias, and legacy system integration.

Need of the Study: This study examines the nature, scope, and impact of AIdriven banking, with a focus on its applications in fraud detection, risk management, regulatory compliance, and customer experience enhancement across commercial banking institutions.

Methodology: A review of secondary data and documented case studies of leading global and Indian banking institutions — including JPMorgan Chase, Bank of America, HSBC, DBS Bank, and select Indian commercial banks — was undertaken to analyse AI deployment strategies and their operational outcomes.

Findings of the Study: The study finds that AI significantly improves operational efficiency, realtime decision making, and personalised customer engagement. Indian banks are increasingly aligning with global AI adoption trends, though implementation gaps persist due to data governance issues, ethical concerns, and infrastructural limitations.

Findings of the Study: The findings underscore the strategic imperative for banking institutions to invest in responsible AI frameworks, regulatory compliance mechanisms, and workforce up skilling to fully leverage AI's transformative potential while ensuring secure, inclusive, and customer centric digital banking ecosystems.