This study comprehensively examines the role of artificial intelligence (AI) in the banking sector within the framework of a SWOT analysis. AI’s significant advantages over human resources—such as speed, minimizing errors, being unaffected by emotional factors, treating everyone equally, and operating 24/7 without breaks—have accelerated its adoption in banking and finance. Banks benefit from AI in various areas, including call centers, customer relationship management, fraud detection, credit scoring, automation, and branchless banking applications. Existing literature shows that AI achieves high success in predicting financial success or failure, assessing credit risk, classifying customers, speeding up business processes, reducing error rates, handling more work with fewer employees, lowering costs, and completing customer transactions faster. Additionally, AI is intensively used in customer acquisition, customer loyalty, personalized services, and reducing workload.

In the SWOT analysis, AI’s strengths include providing fast and largely accurate services, reducing errors related to data entry, transactions, customer service, systems, and security, effectively analyzing and interpreting data, and monitoring processes in real time. Opportunities include increased efficiency, cost reduction, enabling employees and managers to focus on more strategic tasks, and accurately calculating personal risk profiles. On the other hand, weaknesses involve lack of empathy, the need for technical expertise, non-transparent models, and difficulties for some digitally inexperienced customers. Threats include initial investment requirements, unemployment risks, cyberattacks, data privacy issues, and costly consequences of algorithmic errors.

In conclusion, the study suggests that evaluating AI in banking with both its strengths and weaknesses indicates that hybrid models, combining human intelligence with AI, can provide significant advantages to institutions, employees, and customers in the sector.