The Applicability of Artificial Intelligence in Candidate Interviews in the Recruitment Process
DOI:
https://doi.org/10.56741/jmsd.v2i02.388
Keywords:
Artificial Intelligence , AI in HRM, AI in Recruitment, AI in Recruitment & Selection , AI in Interviews , HR Innovation, Industry 4.0 and HRM
Abstract
This research paper examines the applicability of artificial intelligence (AI) in the recruitment and selection process, with a specific focus on the Interview phase. The study conducted qualitative interviews with 17 recruitment professionals, including hiring managers, recruiters, and HR executives, to gather their perspectives on AI adoption. The Unified Theory of Acceptance and Use of Technology (UTAUT) framework was utilized as the theoretical model to guide the research.
The findings indicate that the recruitment professionals were generally receptive to using AI in various recruitment phases. However, when it came to the interview phase, there was a distinct lack of enthusiasm for AI adoption among the professionals. They expressed concerns about providing a better candidate experience and perceived AI-based interviews as a lack of commitment to candidates. As a result, regardless of the hiring volume or job group, the professionals were hesitant to integrate AI into the interview phase.
The research underscores the importance of carefully selecting the appropriate recruitment stage for integrating AI and addressing the concerns raised by recruitment and selection professionals. It highlights the need to consider the candidate's experience and maintain a sense of commitment throughout the recruitment process.
Downloads
References
Flinders University Ethics Approval Committee. (n.d.). Flinders University ethics approval committee. Retrieved from https://www.flinders.edu.au/research/research-services/research-ethics/integrity-ethics-and-compliance/ethics-approval-committees
Black, J. S., & van Esch, P. (2020). AI-enabled recruiting: What is it and how should a manager use it? Business Horizons, 63(2), 215–226. https://doi.org/10.1016/j.bushor.2019.12.001
Black, J. S., & van Esch, P. (2020a). Assessing resume review for selection: The latest research. Human Resource Management Review, 30(2), 100708. https://doi.org/10.1016/j.hrmr.2019.100708
Spradley, J. P. (1979). The ethnographic interview. Holt, Rinehart and Winston.
Azeem, M. F., & Yasmin, R. (2016). HR 2.0: linking Web 2.0 and HRM functions. Journal of Organizational Change Management, 29(5), 686–712. https://doi.org/10.1108/JOCM-09-2015-0152
Azeem, M. U., & Yasmin, R. (2016). The impact of recruitment and selection criteria on organizational performance. Global Journal of Management And Business Research, 16(3), 1-9.
Balasundaram, S., Venkatagiri, S., & Sathiyaseelan, A. (2022). Using AI to enhance candidate experience in high volume hiring: A conceptual review and case study. Researchgate.Net, March. https://www.researchgate.net/profile/Sathiyaseelan-Balasundaram/publication/359199987_Using_AI_to_enhance_candidate_experience_in_high_volume_hiring_A_conceptual_review_and_case_study/links/622dacc2a39db062db999714/Using-AI-to-enhance-candidate-experience
Ferdiana, S., Khan, Z., & Ray, S. (2023). Investigating the Impact of Career Development, Organizational Commitment, and Organizational Support on Employee Retention. Journal of Management Studies and Development, 2(02), 117–128. https://doi.org/10.56741/jmsd.v2i02.108
Fernández-Martínez, C., & Fernández, A.. (2020, May 28). AI and recruiting software: Ethical and legal implications. https://scite.ai/reports/10.1515/pjbr-2020-0030
Kalleberg, A. L. (2018). Good Jobs, Bad Jobs: The Rise of Polarized and Precarious Employment Systems in the United States, 1970s to 2000s. New York: Russell Sage Foundation.
Kvale, S. (1996). Interviews: An introduction to qualitative research interviewing. Sage Publications.
Kwon, S., & Wen, K. (2018). The impact of stakeholder involvement on recruitment fairness and job pursuit intentions. Journal of Business and Psychology, 33(3), 341-355. https://doi.org/10.1007/s10869-017-9518-6
Sridevi, G., & Suganthi, S.K. (2021). Artificial Intelligence-Based Job Applicant Profile Quality Assessment and Relevance Ranking Using Clusters in Talent Acquisition Process.
Allal-Chérif, O., Yela Aránega, A., & Castaño Sánchez, R. (2021). Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence. Technological Forecasting and Social Change, 169(April). https://doi.org/10.1016/j.techfore.2021.120822
Panchal, P., & Gupta, A. (2019). Artificial intelligence in recruitment and selection: A review of current literature. Journal of Organizational Psychology, 19(1), 24-35.
Sengupta, A., Lalwani, S., Goswami, S., & Srivastava, P. (2020). Materials Today : Proceedings Reinventing HR functions with SMAC technologies- an exploratory study. Materials Today: Proceedings, xxxx. https://doi.org/10.1016/j.matpr.2020.10.875
Skrobotov, A. (2021). The perceptions of recruitment practitioners on the adoption of artificial intelligence in recruitment and selection. The International Journal of Human Resource Management, 1-25. https://doi.org/10.1080/09585192.2021.1947917
DeVaro, J.. (2016, January 1). Internal hiring or external recruitment?. https://scite.ai/reports/10.15185/izawol.237
Rose, M. A., & Sandhya, S. (2022). Building employee engagement through talent acquisition: a literature review. Journal of Management Development, 41(2), 167-181.
Miles, J. A., & McCamey, R. B. (2018). Employment branding: A review and future directions. Journal of Business and Psychology, 33(2), 207-224.
DeVaro, J., & Waldman, M. (2012). Screening devices and the recruitment of overeducated workers. Journal of Labor Economics, 30(2), 285–315. https://doi.org/10.1086/664655
Esawi, E. A., & Ashby, A. (2003). Screening and selecting job candidates. Journal of Business and Industrial Marketing, 18(8), 708-718. https://doi.org/10.1108/08858620310504552
Firdausa Nuzula, I., & Miftahul Amri, M. (2023). Will ChatGPT bring a New Paradigm to HR World? A Critical Opinion Article. Journal of Management Studies and Development, 2(02), 142–161. https://doi.org/10.56741/jmsd.v2i02.316
Elia, M. L., & Rodríguez, M. L. (2019). Big data in human resource management: A systematic literature review. International Journal of Human Resource Management, 30(15), 2157-2181. doi: 10.1080/09585192.2017.1404435
AI Litigation Database, GW Law, George Washington University, 2000 Pennsylvania Avenue NW
Washington, DC 20006
Creswell, J. W. (2014). Research design: qualitative, quantitative, and mixed methods approaches. Sage publications.
Dignum, V., & van der Torre, L. (2019). Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way. In The AI in Business, Finance and Industry Book (pp. 91-111). Springer, Cham.
Baratelli, G., & Colleoni, E.. (2022, January 13). Does Artificial Intelligence (AI) Enabled Recruitment Improve Employer Branding?. https://scite.ai/reports/10.5539/ijbm.v17n2p45
Barber, A. E. (1998). Recruiting employees: Individual and organizational perspectives. Sage Publications.
Salgado, J. F. (1997). The five-factor model of personality and job performance in the European Community. Journal of Applied Psychology, 82(1), 30-43. https://doi.org/10.1037/0021-9010.82.1.30
Gottfredson, L. S., & Holland, J. L. (1996). Dictionary of Holland occupational codes. Psychological Assessment Resources.
Galanaki, E., & Papalexandris, A. (2020). Human resource management and artificial intelligence: The future is here. In Handbook of research on human resources strategies for the new millennial workforce (pp. 88-105). IGI Global. https://doi.org/10.4018/978-1-7998-2924-4.ch005
Hallam, C. (2009). The handbook of employee benefits. John Wiley & Sons.
Deloitte. (2021). Human Capital Trends 2021: The social enterprise in a world disrupted. Retrieved from https://www2.deloitte.com/us/en/insights/focus/human-capital-trends/2021/hiring.html
Venkatesh, Viswanath, et al. "User Acceptance of Information Technology: Toward a Unified View." MIS Quarterly, vol. 27, no. 3, 2003, pp. 425–78. JSTOR, https://doi.org/10.2307/30036540. Accessed 18 July 2023.
Lincoln, Yvonne and Guba, Egon (1985) Naturalistic Inquiry. Beverly Hills, CA: SAGE.
Cook, M., Cripps, B., & Tuckey, M. R. (2019). How do selection methods influence the cost and time taken to recruit new employees? Journal of Business and Psychology, 34(6), 761-774.
Clear, F. (2007). Dealing with recruitment bias: A review of field experiments. Work, Employment & Society, 21(4), 657-675. https://doi.org/10.1177/0950017007081984
Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G
Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review, 1(1).
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2023 Anusha Hewage

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.








