Title: Artificial Intelligence Adoption And Organisational Sustainability Of Deposit Money Banks In Rivers State, Nigeria
Authors: Nwiyii Blessing Joseph, Jacob Chidinma Sandra
Volume: 10
Issue: 6
Pages: 80-91
Publication Date: 2026/06/28
Abstract:
This scholarly investigation scrutinized the nexus between the adoption of artificial intelligence (AI) and the sustainability of deposit money banks within Rivers State. The primary aim was to elucidate how various dimensions of AI integration, including virtual assistance, process automation, and personalized banking solutions correlate with key indicators of organizational sustainability, namely social, economic, and environmental sustainability, in the context of deposit money banking institutions in Rivers State. The theoretical framework underpinning this inquiry was grounded in the Technology Acceptance Model (TAM). Employing an explanatory cross-sectional survey research design, the study targeted the entire accessible population of twenty-seven deposit money banks operating within Rivers State, specifically those with headquarters situated in Port Harcourt, as sourced from the Central Bank of Nigeria, Rivers State Chapter (refer to Appendix I). Given that the entire population was encompassed, the research was conducted as a census rather than a sample-based study. Regarding respondent selection, a purposive sampling technique was employed to select one hundred and sixty-two (162) senior managers tasked with responding on behalf of their respective institutions. Data collection was primarily facilitated through a structured questionnaire, serving as the principal instrument for primary data acquisition. To ensure the instrument's validity, copies of the questionnaire were evaluated by two experts from the Department of Business Administration at the Federal University of Environment, whose feedback informed the refinement of the final instrument. Reliability analysis was conducted utilizing Cronbach's Alpha coefficient. A total of 162 questionnaires were distributed with the assistance of two independent research assistants, and a response rate of 89% was achieved, yielding 145 completed questionnaires suitable for analysis. Data analysis was performed using the Pearson Product-Moment Correlation Coefficient (r), facilitated by the Statistical Package for Social Sciences (SPSS) version 26.0. The findings demonstrated a statistically significant positive correlation between the extent of AI adoption and the organizational sustainability of deposit money banks in Rivers State. The results suggest that leveraging AI-driven technologies such as virtual assistance, automation, and personalized services can contribute to enhanced operational efficiency, cost reduction, and improved service delivery. Consequently, the study recommends that the management of deposit money banks in Rivers State should prioritize the development and enhancement of virtual assistance systems to bolster social sustainability by fostering improved customer engagement, accessibility, and responsiveness.