The convergence of Artificial Intelligence (AI) and sustainable banking is transforming the global financial landscape, presenting both extraordinary opportunities and significant challenges. This paper provides an in-depth review of AI applications in the banking sector, elaborating on their role in advancing efficiency, enhancing customer experience and promoting financial inclusion, while also examining their implications for sustainability. Drawing on a thematic analysis of scholarly literature, case studies, industry reports and studies, this analysis identifies key applications of AI in fraud identification, credit risk management, wealth management, customer service automation and regulatory compliance. Further than operational welfare, the review centre is evolving sustainability-focused on uses of AI, comprising environmental, social and governance (ESG) risk calculation and green finance simplification. However, major challenges remain, notably data privacy risks, algorithmic bias, regulatory uncertainty, high operational costs, workforce disruptions and the environmental impact of AI systems. The analysis underscores significant gaps in aligning AI adoption with broader sustainability goals, regulatory expectations and ethical standards. To address the identified loopholes, this research recommends future research strategies focused on the development of accountable AI frameworks, explainable AI, stronger regulatory harmonization and inclusive financial contact. The findings contribute to both theory and practice by combining fragmented insights, providing a structured framework for indulgent AI’s dual role in efficiency and sustainability and offering legal guidance for policymakers, regulators and banking authorities. Ultimately, this study highlights AI not only as a driver of operational conversion but also as a catalyst for building a more comprehensive, robust and practical global banking environment.