Get started
Work

Artificial Intelligence Adoption and Bank Performance in Nigeria: The Moderating Role of Cybersecurity Risk

Year: 2026
Type: article
Study design: Observational Study
Abstract: Artificial intelligence (AI) is becoming embedded in Nigerian banking through process automation, predictive analytics, personalised service, credit and risk analytics, and automated customer interfaces. Yet the organisational value associated with these capabilities is realised in an environment of expanding cyber exposure. This study examined the relationship between AI adoption and employee-rated bank performance in Nigeria and tested whether cybersecurity risk conditions affects the relationship. A quantitative cross-sectional explanatory survey was conducted among managerial, supervisory and specialist employees of 12 deposit money banks across major Nigerian banking hubs. From an accessible population of 6,214 eligible employees, 450 questionnaires were distributed through proportionate stratified and systematic sampling; 401 usable responses were analysed. AI adoption was operationalised through AI-driven process automation, predictive analytics and decision intelligence, and AI-enabled customer engagement. Bank performance captured perceived operational efficiency, service quality/customer responsiveness and financial/competitive performance, while cybersecurity risk measured perceived exposure to data compromise, social engineering, system intrusion, third-party/API vulnerabilities and AI-enabled fraud. Descriptive statistics, Pearson correlation, HC3-robust ordinary least-squares regression and mean-centred moderation analysis were used. The three AI dimensions jointly explained 37.3% of the variance in bank performance. Predictive analytics showed the strongest positive association (β = .387, p < .001), followed by process automation (β = .210, p < .001) and customer engagement (β = .132, p = .005). Cybersecurity risk was negatively associated with performance (β = -.278, p < .001). Most importantly, the AI adoption × cybersecurity risk interaction was negative and significant (B = -.360, p < .001), adding 3.7 percentage points to explained variance. Simple-slope analysis showed that AI adoption remained positively associated with performance at low, average and high cyber risk, but the association weakened materially as risk increased. The study concludes that deeper AI adoption is associated with stronger employee-rated bank performance, while cybersecurity risk attenuates that relationship. Nigerian banks should therefore govern AI investment and cybersecurity investment as one integrated performance architecture rather than as separate technology programmes.
DOI: 10.51699/k4dy7y70
Language: English
Open Access status: hybrid
OpenAlex ID: W7223408946
FWCI:
Cites:
Cited by:
Related to: