The Determinants of AI Adoption and Its Impact on Employee Engagement: Evidence from Egyptian Organizations
The Determinants of AI Adoption and Its Impact on Employee Engagement: Evidence from Egyptian Organizations
Author(s): Shorouk Salaheldin, Safaa HusseinSubject(s): National Economy, Business Economy / Management, Financial Markets, Accounting - Business Administration, Human Resources in Economy, ICT Information and Communications Technologies, Socio-Economic Research
Published by: New Millennium Discoveries Ltd
Keywords: Artificial Intelligence Adoption; Employee Engagement; Technology– Organization–Environment Framework; Egypt;
Summary/Abstract: This study examines the determinants of Artificial Intelligence (AI) adoption and its influence on employee engagement in Egyptian organizations, utilizing the Technology–Organization–Environment (TOE) framework. Based on survey data from 210 professionals across various industries and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal that relative advantage, compatibility, and top management support significantly drive AI adoption. In contrast, complexity, security/privacy concerns, organizational readiness, competitive pressure, and external and government support do not show significant effects. Furthermore, AI adoption demonstrates a positive but modest impact on employee engagement, suggesting the presence of other contributing factors. These results reflect the unique socio-economic conditions in Egypt, where internal organizational factors outweigh external influences in shaping technology adoption. The findings have practical implications for organizations and policymakers, emphasizing the need to prioritize internal drivers—such as leadership commitment, perceived benefits, and system compatibility—when promoting AI adoption. Additionally, organizations should align AI initiatives with employee needs and workplace culture to enhance engagement outcomes.
Journal: International Journal of Management and Applied Research
- Issue Year: 12/2025
- Issue No: 2
- Page Range: 45-67
- Page Count: 23
- Language: English
