Abstract
The growing integration of generative artificial intelligence (GenAI) in human resource management is transforming recruitment by enhancing decision-making efficiency and candidate screening worldwide. However, little is known about how HR professionals in resource-constrained settings, such as Uganda’s public health sector, experience and interpret these technologies. Therefore, this study aimed to explore the lived experiences of HR professionals using GenAI tools in recruitment within selected public hospitals in Uganda. The study employed a qualitative phenomenological approach; in-depth semi-structured interviews were conducted with 12 HR officers from regional referral hospitals utilizing AI-assisted recruitment or digital screening systems. Thematic analysis identified five key themes: (1) navigating GenAI with limited formal training, (2) concerns about fairness and algorithmic bias, (3) balancing recruitment speed with human intuition, (4) ethical dilemmas and transparency gaps, and (5) the evolving role of HR professionals in an AI-augmented workplace. Participants expressed a complex mix of optimism about efficiency gains alongside skepticism rooted in infrastructural challenges, inadequate policy frameworks, and digital literacy barriers among applicants. Findings underscore the need for tailored AI training, robust ethical guidelines, and policy reforms addressing the contextual realities of low-resource environments. This study contributes valuable insights to the emerging discourse on AI adoption in HR management by foregrounding the human experiences behind technological change in Sub-Saharan Africa’s public sector. It advances understanding of how AI tools are socially negotiated in complex institutional settings, offering practical implications for enhancing AI integration and governance in healthcare recruitment.
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Kyambade, M., & Namatovu, A. (2026). Exploring HR Professionals’ Experiences with Generative AI in Recruitment: A Phenomenological Study in Public Hospitals in Uganda. SAGE Open, 16(2). https://doi.org/10.1177/21582440261457060
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