A Qualitative Research Study into The Effectiveness of Artificial Intelligence in Recruitment & Selection, From The Perspective of Recruitment Specialists in Ireland

McGearty, Brian James (2025) A Qualitative Research Study into The Effectiveness of Artificial Intelligence in Recruitment & Selection, From The Perspective of Recruitment Specialists in Ireland. Masters thesis, Dublin, National College of Ireland.

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Abstract

The adoption of Artificial Intelligence to aid with functions such as Recruitment and Selection has grown rapidly in recent years. This research study will explore the effectiveness of utilizing AI tools and systems from the perspective of recruitment specialists working in Ireland. Previous research in the field has focused on organizational benefits such as cost reduction, and competitive advantage, this has left a significant gap in the research, to get a better understanding of the viewpoints, opinions and experiences from the professionals using AI daily. This research uses a qualitative semi-structured interview approach to address the gap in literature.

The research adopts an interpretivist research philosophy and qualitative methodology. The study was conducted by semi-structured interviews with six participants working as recruitment specialists in Ireland, participants worked as both in-house recruiters and for recruitment agencies. The interview questions were designed to gather deep insight and firsthand information, avoiding closed ended questions. To analyse the data from the transcripts, this research utilised Braun and Clarke (2006) thematic analysis framework, identifying four main themes: Recruitment & Selection, Organisational Advantages, Strategic Management, and Ethical & Legal Obstacles.

The findings in this research highlight a complex relationship between the recruiters and artificial intelligence. Participants noted the AI tools and systems ability to handle repetitive tasks such as screening applications and CVs, drafting emails, and keeping communication channels open with candidates, for example sending deadline reminders for unfinished applications. Participants mentioned using tools such as LinkedIn recruiter, Loxo, Gamma and Chat GPT, which in return has saved them time to focus on strategic objectives.

Human oversight and supervision were a recurring theme across the research study, participants voiced their concerns about over-reliance on AI and the ethical issues that may follow. Participants pointed out limitations such as AI developing an algorithm bias, potentially overlooking highly skilled candidates. It was a general consensus amongst participants that AI was not going to replace their role but rather assist and enhance their performance, using the AI tools as a personal assistant to perform administrative tasks, allowing more time for the recruiter to engage with clients and candidates on a personal level. The research suggest that AI lacks the ability to identify nonverbal cues and body language, unable to identify an individual’s suitability for the organisation. This reflects the findings of many previous research papers, that AI should be used to enhance the recruiter’s role rather than replace it. Participants strongly suggested the training and development of individuals using Artificial Intelligence, noting the importance of identifying a bias in the system, conducting regular audits to mitigate this factor and have a strong policy in place regarding the fair use of AI, noting that noncompliance may result in legal issues surrounding bias discrimination, breaches of GDPR and European legislation.

In conclusion, this research study suggests that Artificial Intelligence tools are most effective in recruitment and selection when they are aligned closely with human intervention and supervision. AI tools are most effective at administrative task, but their success depends heavily on the training and experience of the user, and maintaining the human element of recruitment and selections. The limitation of this study is the small sample size and geographical restrictions provide clear avenue for future research, for example getting the candidates perspective and expanding the research on an international level.

Item Type:	Thesis (Masters)
Supervisors:	Name Email MacDonald, Robert UNSPECIFIED
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Human Resource Management D History General and Old World > DA Great Britain > Ireland H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Human Resource Management > Recruitment
Divisions:	School of Business (- 2025) > Master of Arts in Human Resource Management
Depositing User:	Ciara O'Brien
Date Deposited:	08 Dec 2025 15:55
Last Modified:	08 Dec 2025 15:55
URI:	https://norma.ncirl.ie/id/eprint/9014

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