EFFECTIVENESS OF ARTIFICIAL INTELLIGENCE IN RECRUITMENT
https://doi.org/10.55452/1998-6688-2025-22-2-412-422
Abstract
This study aims to explore the use of Artificial Intelligence in recruitment, focusing on its impact on decisionmaking, transparency, and trust. Artificial Intelligence has rapidly become a vital tool in modern recruitment processes, automating key tasks such as screening and interview scheduling. This research applies comprehensive analysis, utilizing both descriptive and network methodologies, to examine how Artificial Intelligence-driven recruitment affects stakeholders, particularly in terms of trust in Artificial Intelligence systems. The findings show key areas in the application of Artificial Intelligence in recruitment, including automated decision-making, stakeholder interaction, and the ethical concerns surrounding bias and transparency. Transparency not only enhances the perceived fairness of Artificial Intelligence processes but also builds trust among both recruiters and candidates. However, overreliance on Artificial Intelligence, especially without proper human oversight, may cause discomfort, leading to a potential erosion of trust. Artificial Intelligence helps organizations improve their recruitment outcomes, particularly in achieving diversity and minimizing biases. Artificial Intelligence in recruitment hinges on transparency, trust, and a balanced integration of Artificial Intelligence and human input. These insights are valuable for organizations looking to optimize their recruitment processes and foster trust in Artificial Intelligence-driven systems.
About the Authors
A. OralbayevKazakhstan
master’s student
Almaty
N. Bekbolat
Kazakhstan
master’s student
Almaty
A. Begdildayev
Kazakhstan
master’s student
Almaty
A. Azhibay
Kazakhstan
master’s student
Almaty
D. Serikbay
Kazakhstan
PhD candidate
Almaty
E. Keser
Turkey
MBA
Istanbul
References
1. Britannica. (n.d.). Industrial Revolution. URL: https://www.britannica.com
2. Makridakis S., & Hyndman R.J. Forecasting the impact of AI on work. Wiley Online Library. – 2020. URL: https://onlinelibrary.wiley.com.
3. MIT Technology Review. Generative AI and its applications. MIT Technology Review. – 2021. URL: https://www.technologyreview.com.
4. Stone D.L., & Dulebohn J.H. AI in human resources // Human Resource Management Review. – 2018. – Vol. 28. – No. 3). – P. 260–275. URL: https://www.journals.elsevier.com/human-resource-managementreview
5. Forbes Insights. The ethical implications of AI in recruitment // Forbes. – 2023. URL: https://www.forbes.com
6. Society for Human Resource Management (SHRM). AI and behavioral analytics in recruitment // SHRM. – 2022. URL: https://www.shrm.org.
7. Behavioral Sciences. Artificial intelligence decision-making transparency and employees’ trust: The parallel multiple mediating effect of effectiveness and discomfort // Behavioral Sciences. – 2022. – Vol. 12. – No. 5. – P. 127. URL: https://www.mdpi.com/journal/behavsci.
8. Jarrahi M.H. Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision-making // Business Horizons. – 2018. – Vol. 61. – No. 4. – P. 577–586. URL: https://www.journals.elsevier.com/business-horizons.
9. Zhang T., Song M., & He Z. Exploring how perceived trust in AI systems affects continuous usage intentions: Evidence from the recruitment industry // Journal of Business Research. – 2021. – Vol. 125. – P. 597–605. URL: https://www.journals.elsevier.com/journal-of-business-research
10. Von Krogh G. Artificial intelligence in organizations: new opportunities for phenomenon-based theorizing // Acad Manage Discoveries. – 2018. – Vol. 4. – No. 4. – P. 404–409.
11. Johnson R.D, Laszewski K.M, Stone D.L The evolution of the field of human resource information systems: co-evolution of technology and HR processes // Commun Assoc Inf Syst. – 2016. – Vol. 38. – P. 28.
12. Rajagopal N.K, Qureshi N.I, Durga S. Asis E.H.R., Soto R.M.H., Gupta S.K., Deepak S. Future of business culture: an artificial intelligence-driven digital framework for organization decision-making process // Complexity. – 2022. – Article ID 7796507. – P. 14. https://doi.org/10.1155/2022/7796507
13. Upreti K., Syed M.H., Ali Khan M., Fatima H., Alam M.S., Sharma A.K. Enhanced algo- rithmic modelling and architecture in deep reinforcement learning based on wireless communication Fintech Technology // Optik. – 2023. – Vol. 272. – P. 170309. https://doi.org/10.1016/j.ijleo.2022.170309
14. Sneha K., Shekhar S.K. Impact of artificial intelligence and digitalization in the evolu- tion of recruitment marketing. In: Kozhikode 4th international conference on marketing, technology & society 2019, Indian Institute of Management, Peer-review under responsibility of the 04th ICMTS 2019.
15. Rajesh S., Kandaswamy U., Rakesh A. The impact of artificial intelligence in talent acquisition lifecycle of organizations // Int J Eng Dev Res. – 2018. – Vol. 6. – No. 2. – P. 709–717.
Review
For citations:
Oralbayev A., Bekbolat N., Begdildayev A., Azhibay A., Serikbay D., Keser E. EFFECTIVENESS OF ARTIFICIAL INTELLIGENCE IN RECRUITMENT. Herald of the Kazakh-British Technical University. 2025;22(2):412-422. https://doi.org/10.55452/1998-6688-2025-22-2-412-422