Factors affecting Employees’ Acceptance and Use of Artificial Intelligence in the Saudi Arabian Energy Sector

This study investigates the determinants of artificial intelligence (AI) acceptance and use in the Saudi Arabian energy sector. A pre-tested surveys was self-administered to 154 employees in the Saudi Arabian energy sector. The study delves into the unified theory of acceptance and use of technology (UTAUT) and develops an extended model of UTAUT using structural equation modeling (SEM) via Smart PLS version 4. Unlike UTAUT and the results of previous research on AI adoption in business, the key findings confirm the direct significant impact of facilitating condition, personal attitude and risk management on employees’ use of AI in the energy sector. The results also confirmed the significant positive impact of effort expectancy and social influence on employees’ behavioral intention to adopt AI. The results did not confirm the significant impacts of factors like performance expectancy, data management and risk management on employees’ intention of using AI nor on their actual use in the energy sector. The study provides implications for policymakers, industry stakeholders, and scholarly communities and offers an insight to foster AI adoption within Saudi Arabian energy sector. The study provides a comprehensive insight into organizational behaviors and decision-making processes surrounding AI integration in the energy sector.