Adoption of artificial intelligence and machine learning in banking systems: a qualitative survey of board of directors

Abstract

The aim of the paper is twofold. First to examine the role of the board of directors in facilitating the adoption of AI and ML in Saudi Arabian banking sector. Second, to explore the effectiveness of artificial intelligence and machine learning in protection of Saudi Arabian banking sector from cyberattacks. A qualitative research approach was applied using in-depth interviews with 17 board of directors from prominent Saudi Arabian banks. The present study highlights both the opportunities and challenges of integrating artificial intelligence and machine learning advanced technologies in this highly regulated industry. Findings reveal that advanced artificial intelligence and machine learning technologies offer substantial benefits, particularly in areas like threat detection, fraud prevention, and process automation, enabling banks to meet regulatory standards and mitigate cyber threats efficiently. However, the research also identifies significant barriers, including limited technological infrastructure, a lack of cohesive artificial intelligence strategies, and ethical concerns around data privacy and algorithmic bias. Interviewees emphasized the board of directors' critical role in providing strategic direction, securing resources, and fostering partnerships with artificial intelligence technology providers. The study further highlights the importance of aligning artificial intelligence and machine learning initiatives with national development goals, such as Saudi Vision 2030, to ensure sustained growth and competitiveness. The findings from the present study offer valuable implications for policymakers in banking in navigating the complexities of artificial intelligence and machine learning adoption in financial services, particularly in emerging markets.

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