Artificial Intelligence and Machine Learning: A Review of Literature and Challenges
Abstract
Artificial Intelligence (AI) refers to the development and programming of computer systems and machines capable of simulating human reasoning, decision-making, and problem-solving processes. Machine Learning (ML), a subset of AI, involves the design of algorithms and computational models that enable systems to learn, adapt, and perform tasks with minimal human intervention. The financial sector has significantly benefited from the adoption of AI and ML through enhanced technological integration and automation in service delivery. The primary objective of this study is to examine the intricacies of existing research on the application of AI and ML within the financial industry. Specifically, the study undertakes a systematic literature review and explores the challenges associated with the adoption of AI and ML in financial service delivery. The paper adopts a systematic approach to critically review research articles published between 2011 and 2025, in line with established reporting standards on AI and ML applications in the financial sectors of both developed and emerging economies. Qualitative analysis was employed to validate and interpret the findings of the study. The findings reveal that AI and ML have emerged as disruptive technologies with immense potential to transform financial services by enhancing operational efficiency, accuracy, and effectiveness. Furthermore, the study highlights emerging trends in the application of AI and ML across the financial sector.