AI-Enabled Recruitment in Qatar’s Events Sector: Implications for Smart Tourism Workforce Capability

Abstract

Artificial intelligence (AI) is increasingly shaping smart tourism ecosystems, yet its role in workforce recruitment remains underexplored. This study investigates AI-enabled recruitment within Qatar’s events sector, a labour-intensive and rapidly expanding component of the nation’s smart tourism agenda. Using a convergent mixed-methods design (survey n = 122; interviews n = 12), the study examines how AI tools are adopted, perceived, and strategically leveraged. The analysis is anchored in the Technology Acceptance Model (TAM) as the primary theoretical framework, complemented by the Resource-Based View (RBV) to examine organisational-level strategic positioning. Constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT) extend the individual-level analysis, while Diffusion of Innovation (DOI) and Sociotechnical Systems Theory serve as interpretive lenses for understanding adoption patterns and human–technology dynamics. Findings show that AI enhances scalability and efficiency but adoption is shaped by cultural expectations, regulatory ambiguity, and organisational digital capability. Moderation analysis reveals that organisational size significantly conditions the relationship between perceived usefulness and adoption intention, with SMEs showing weaker effects than larger firms. Hybrid human–AI recruitment models dominate, reflecting the service-oriented nature of event roles. The study contributes to smart tourism workforce research by empirically demonstrating how technology acceptance and organisational capability jointly shape AI recruitment adoption in a non-Western, service-intensive tourism context.