Achieving operational excellence through artificial intelligence: The case of Ghanaian banks

Using the resource-based theory as the lens, this research proposes a conceptual model to explore the determinants of AI in the Ghanaian banking sector and also examine its impact on the OpEx of the banks. The study adopted a quantitative research approach with a survey method to collect data from 331 CIOs/IS/IT Managers/Data Scientists/Business Analysts and other knowledgeable managers in the Ghanaian banks who were sampled via stratified and purposive sampling techniques. The data analysis was done via partial least squares structural equation modelling (PLS-SEM). The findings revealed the determinants of AI adoption in the Ghanaian banks are Absorptive Capacity, Agility and Capabilities of the banks. Also, it was established from the empirical results that the adoption of AI enhances OpEX of the banks. The determinants obtained in this study would lay a foundation for future research which could be incorporated into a new theoretical model of AI adoption.