Abstract

This study investigates the role of Artificial Intelligence (AI), automation, and data-driven decision-making in enhancing banking efficiency and business process optimization in Nigeria. The research employed a predictive research design, targeting 78,000 banking personnel, with a purposive sample of 444 respondents from top-tier commercial banks across six geopolitical zones. Data were collected using a validated and reliable questionnaire (Cronbach’s α = 0.82), and analyzed through descriptive statistics and multiple regression to examine the predictive impact of AI functions on banking efficiency. Findings reveal that AI-driven automation, digitalization, and data-based decision-making significantly improve operational efficiency, customer service, risk management, and workflow optimization. Regression results indicated that AI functions collectively explain 62% of the variance in banking efficiency (R² = 0.62, F = 143.18, p < 0.001), with automation and digitalization having the strongest predictive effect. The study recommends wider AI adoption, infrastructural support, and regulatory facilitation to maximize banking performance and competitive advantage in Nigeria.

Keywords

  • Artificial Intelligence AI
  • Automation
  • Banking Efficiency
  • Business Process Optimization
  • Data-Driv

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