Artificial intelligence and employee performance in Uganda’s healthcare institutions: exploring the mediation effects of perceived ease of use and skills enhancement

Abstract

PURPOSE: The purpose of this study is to investigate the relationship between artificial intelligence (AI) and employee performance in Uganda's healthcare institutions, with a specific focus on exploring the mediating effects of perceived ease of use (PEOU) and skills enhancement. As AI becomes increasingly integrated into healthcare operations, understanding how these factors influence employee performance is crucial for optimizing the implementation of AI technologies. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to examine the relationships among AI, PEOU, skills enhancement and employee performance. Data were collected from a sample of 185 healthcare professionals working in Uganda's healthcare institutions through a structured questionnaire. Smart PLS - structural equation modeling (SEM) was used to analyze the data and test the proposed mediation model. FINDINGS: The results indicate a positive and significant relationship between AI and employee performance. Furthermore, both PEOU and skills enhancement were found to mediate the relationship between AI and employee performance. Specifically, AI was positively related to PEOU, which in turn was positively associated with employee performance. Similarly, AI positively influenced skills enhancement, which also positively impacted employee performance. PRACTICAL IMPLICATIONS: The findings of this study suggest that healthcare institutions should focus on enhancing the perceived ease of use of AI technologies and investing in skills development programs to maximize the benefits of AI on employee performance. By designing user-friendly AI systems and providing continuous training, healthcare organizations can improve the effectiveness and efficiency of their workforce. This approach can lead to better patient outcomes and operational efficiencies in the healthcare sector. ORIGINALITY/VALUE: This study contributes to the existing literature by integrating the technology acceptance model (TAM) and resource-based view (RBV) theory to explore the mediating roles of PEOU and skills enhancement in the context of AI adoption in healthcare. It provides empirical evidence from Uganda, a developing country context, thereby extending the understanding of AI's impact on employee performance in diverse healthcare settings. The study's findings highlight the critical importance of user perceptions and skill development in the successful implementation of AI technologies.

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