EXPLORING THE USE OF ARTIFICIAL INTELLIGENCE FOR HIRING: A QUALITATIVE INVESTIGATION OF DIVERSITY-RELATED CHALLENGES AND THEIR MITIGATION
Background. More and more organizations are integrating artificial intelligence (AI) into organisational functions, including human resource management to gain an added advantage over others. While this integration fetches numerous benefits, there is a dark side of the use of AI , which results in biased outcomes, discrimination, and the controlling effect of these algorithms. This dark side is especially detrimental for organisational diversity. There is equivocality related to the use of AI for hiring decision making especially in the context of diversity hiring. While managers on one hand may find it difficult to justify the use of AI for diversity hiring, at the same time, they may be inclined to use it for its efficiency. Therefore, it is worth uncovering what diversity-related challenges do they perceive from the use of AI for hiring and possible ways to mitigate them.
Objective. Since the literature does not offer a comprehensive picture of different diversity related challenges which arise from the use of AI for hiring and how these challenges can be resolved, I set to examine two research questions:
RQ1. How does the integration of AI for hiring in organisations create challenges for diversity management?
RQ2. How can the challenges for diversity management arising from use of AI for hiring in organisations be overcome?
Design. I used a qualitative research design for this study, because this topic has little and inconclusive existing research, meriting an approach which is exploratory. I gather data from hiring managers who are well-versed with the use of AI for hiring and diversity programs in their organisations. These managers were identified through screening survey run on the crowdsourcing platform, Prolific Academic Limited. The data has been gathered using openended essays from selected participants. I analyse the data using the principles of qualitative data analysis outlined by Glaser & Strauss (1965) and tri-lens theoretical framework to interpret my study findings.
Result. The study findings demonstrate that use of AI for hiring creates both challenges and opportunities for organisational diversity. Furthermore, I find that diversity-related challenges and consequently the strategies to mitigate them, emerge from three sources: technical, people and organisational sources. I further explain that unless organisations assume an integrated approach to manage both social and technical aspects of integrating AI for hiring for diversity management, the issues will remain stagnant. It also calls for addressing the shift in power through the use of these algorithms and restoring it back to human actors. Thereafter, I demonstrate how AI exercises social power.
Objective. Since the literature does not offer a comprehensive picture of different diversity related challenges which arise from the use of AI for hiring and how these challenges can be resolved, I set to examine two research questions:
RQ1. How does the integration of AI for hiring in organisations create challenges for diversity management?
RQ2. How can the challenges for diversity management arising from use of AI for hiring in organisations be overcome?
Design. I used a qualitative research design for this study, because this topic has little and inconclusive existing research, meriting an approach which is exploratory. I gather data from hiring managers who are well-versed with the use of AI for hiring and diversity programs in their organisations. These managers were identified through screening survey run on the crowdsourcing platform, Prolific Academic Limited. The data has been gathered using openended essays from selected participants. I analyse the data using the principles of qualitative data analysis outlined by Glaser & Strauss (1965) and tri-lens theoretical framework to interpret my study findings.
Result. The study findings demonstrate that use of AI for hiring creates both challenges and opportunities for organisational diversity. Furthermore, I find that diversity-related challenges and consequently the strategies to mitigate them, emerge from three sources: technical, people and organisational sources. I further explain that unless organisations assume an integrated approach to manage both social and technical aspects of integrating AI for hiring for diversity management, the issues will remain stagnant. It also calls for addressing the shift in power through the use of these algorithms and restoring it back to human actors. Thereafter, I demonstrate how AI exercises social power.
Publisert i 2026
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