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This research examines the factors influencing the intention to use artificial intelligence (AI) technology in the recruitment process in UN agencies in Yemen, considering the influence of AI on the responsibilities of recruiters and human resources (HR) experts. Although AI technologies have made significant progress and can automate the recruitment process, limited research exists on recruiters’ comprehension of AI systems and the factors driving AI adoption. This study aims to fill this gap in knowledge by examining the factors that influence the intention to use AI in the context of the recruitment process, integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Perceived Risk (PR) model as the underlying theories, providing an understanding of the factors affecting AI adoption in recruitment. Through a quantitative approach, data was collected from 93 HR and recruiting professionals in United Nations (UN) agencies in Yemen and analyzed using correlation and regression analyses. Results showed significant positive relationships between performance expectancy (PE), effort expectancy (EE), and the intention to use AI in recruitment, highlighting their roles in productivity and task completion. Social influence (SI) also positively impacts AI adoption. Conversely, time risk (TR) negatively affects the intention to use AI, underscoring the need to address and mitigate TR. No relationship was found between performance risk (PER) and behavioral intention (BI). These findings assist in mitigating time and performance concerns and implementing AI in recruitment with transparency.

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Examining Factors Influencing Behavioral Intentions to Use Artificial Intelligence in the Recruitment Processes of United Nations Agencies

  • 章节

  • 发表日期：

    2025年

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  • Noor Al-Sabri,
  • Redhwan Al-amri,
  • Gamal Alkawsi

摘要

This research examines the factors influencing the intention to use artificial intelligence (AI) technology in the recruitment process in UN agencies in Yemen, considering the influence of AI on the responsibilities of recruiters and human resources (HR) experts. Although AI technologies have made significant progress and can automate the recruitment process, limited research exists on recruiters’ comprehension of AI systems and the factors driving AI adoption. This study aims to fill this gap in knowledge by examining the factors that influence the intention to use AI in the context of the recruitment process, integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Perceived Risk (PR) model as the underlying theories, providing an understanding of the factors affecting AI adoption in recruitment. Through a quantitative approach, data was collected from 93 HR and recruiting professionals in United Nations (UN) agencies in Yemen and analyzed using correlation and regression analyses. Results showed significant positive relationships between performance expectancy (PE), effort expectancy (EE), and the intention to use AI in recruitment, highlighting their roles in productivity and task completion. Social influence (SI) also positively impacts AI adoption. Conversely, time risk (TR) negatively affects the intention to use AI, underscoring the need to address and mitigate TR. No relationship was found between performance risk (PER) and behavioral intention (BI). These findings assist in mitigating time and performance concerns and implementing AI in recruitment with transparency.