Integration of AI Agents in Recruitment: Opportunities and Challenges

Authors

  • Labiba Fairuz Hassan Independent University, Bangladesh image/svg+xml
    Competing Interests

    -

  • Md. Aminul Islam Independent University, Bangladesh image/svg+xml
    Competing Interests

    -

  • Abdullah Al Mamun Independent University, Bangladesh image/svg+xml
    Competing Interests

    -

Keywords:

Artificial Intelligence (AI), AI-Agent, Hiring, Opportunities, Challenges

Abstract

This research illustrates the potential implications of AI agent deployment in the 
recruitment ecosystem, primarily through a Bangladeshi multinational cultural lens. The 
goal is to streamline procedures, accelerate recruitment, introduce a paperless workflow, 
and facilitate more rigorous, robust evaluations of prospective candidates, reducing human 
error and bias to ensure optimal job alignment. However, a few international studies have 
highlighted AI’s utility in the hiring process, but its actual use and impact in Bangladesh 
remain largely unstudied. Hence, the results of this study are anticipated to have a broader 
impact on Bangladesh’s digitalization of the traditional hiring process, reducing time and 
human intervention while addressing algorithmic and behavioral biases.  More importantly, 
the research also emphasizes the need to educate applicants and recruiters about technical 
errors in AI systems, including the trial period of operation and the duration of data feeding. 
Ultimately, this study supports not only AI implementation but also responsible adoption 
of AI, backed by a regulation framework, stakeholder understanding, and capacity
building initiatives, which can help digitally transform the hiring landscape. These gaps 
were addressed through a mixed-method approach combining quantitative surveys with 
qualitative interviews of job seekers and human resource professionals. Data has been 
collected from multiple organizations through surveys at different levels, secondary sources, 
interviews, and relevant case studies. Here, Gibson’s Theory of Affordance serves as the 
analytical structure supporting the study by evaluating user acceptance and engagement 
with the AI-agent-based system. Future studies and cases should investigate the long-term 
feasibility of integrating AI agents into HR operations, especially the recruitment process, 
and evaluate the new challenges arising in other Bangladeshi companies.

Author Biography

  • Labiba Fairuz Hassan, Independent University, Bangladesh

    -

References

Akhter, F., Bhattacharjee, A., & Hasan, A. (2024, January). Application of artificial intelligence in

human resource management: A Bangladeshi perspective. Munich Personal RePEc Archive. URL:

https://mpra.ub.uni-muenchen.de/122222/

Bonti , M. (2025, April 7). A systematic literature review on artificial intelligence in recruiting and

selection: A matter of ethics. In M. Mori, S. Sassetti, & V. Cavaliere (Eds.), Personnel Review,

54(3). DOI: https://doi.org/10.1108/PR-03-2023-0257

Borsos, P. (2024, July 19). The possibilities of using artificial intelligence as a key technology

in the current employee recruitment process are discussed. In G. Koman & M. Kubina (Eds.),

Administrative Sciences, 14(7), 157. DOI: https://doi.org/10.3390/admsci14070157

Colbak, L. (2025, May). AI agents: From co-pilots to autopilots. Financial Times. URL: https://

www.ft.com/content/3e862e23-6e2c-4670-a68c-e204379fe01f

Faraj, S., & Azad, B. (2012). The materiality of technology: An affordance perspective. In P. M.

Leonardi, B. A. Nardi, & J. Kallinikos (Eds.), Materiality and organizing: Social interaction in

a technological world (pp. 237–258). Oxford University Press. DOI: https://doi.org/10.1093/

acprof:oso/9780199664184.003.0009

Fritts M., Cabrera F. (2021). AI recruitment algorithms and the dehumanization problem. Ethics and

Information Technology, 23(4), 791–801. DOI: https://doi.org/10.1007/s10676-021-09589-z

Geetha, R., & Reddy, D. M. (2018). Recruitment through artificial intelligence: A conceptual study.

International Journal of Mechanical Engineering and Technology, 9(7), 63–70.

Gelinas, J., Vézina, M., & Dumont, B. (2022). Data-driven human resource management:

Prospects and challenges. Human Resource Management Review, 32(2), 100832. DOI: https://doi.

org/10.1016/j.hrmr.2022.100832

Gibson, J. J. (1979). An ecological approach to visual perception. Houghton Mifflin.

Handunge , V. (2021, September). The lifecycle of algorithmic decision-making systems:

Organizational choices and ethical challenges. In M. Marabelli & S. Newell (Eds.), The Journal

of Strategic Information Systems, 30(4), 101695. DOI: https://doi.org/10.1016/j.jsis.2021.101695

Horodyski, P. (2023). Applicants’ perspectives on AI-assisted recruitment: Opportunities and threats.

Frontiers in Psychology, 14, Article 1020270. DOI: https://doi.org/10.3389/fpsyg.2023.1020270

Lashkari, M., & Cheng, J. (2023, January 27). Fairness in AI-driven recruitment: Challenges, metrics,

methods, and future directions. arXiv Preprint arXiv:2405.19699. DOI: https://doi.org/10.48550/arXiv.2405.19699

Marabelli, M., Newell, S., & Handunge , V. (2021, September). The lifecycle of algorithmic

decision-making systems: Organizational choices and ethical challenges. The Journal of Strategic

Information Systems, 30(4), 101695. DOI: https://doi.org/10.1016/j.jsis.2021.101695

Mori, M., Sassetti, S., Cavaliere, V., & Bonti , M. (2025, April 7). A systematic literature review on

artificial intelligence in recruiting and selection: A matter of ethics. Personnel Review, 54(3). DOI:

https://doi.org/10.1108/PR-03-2023-0257

Mujtaba, B. G., & Mahapatra, S. (2024). Artificial intelligence in recruitment and selection:

Organizational practices and ethical implications. International Journal of Human Resource

Management, 35(4), 1289–1315. DOI: https://doi.org/10.1080/09585192.2023.2267857

Rahman, M., Hossain, A., Miah, S., Alom, M., & Islam, M. (2025, January). Artificial intelligence

(AI) in revolutionizing sustainable recruitment: A framework for inclusivity and efficiency.

International Research Journal of Multidisciplinary Scope. URL: https://www.researchgate.net/

publication/388936696

Statista. (2022). According to talent acquisition professionals worldwide, artificial intelligence

benefits hiring. Statista Research Department.

Tambe, P., Cappelli, P., & Yakubovich, V. (n.d.). Artificial intelligence in human resource

management: Challenges and a path forward. California Management Review. DOI: https://doi.

org/10.1177/0008125619867910

Vedapradha, K., Anuradha, J., & Hema, J. (2019). Machine learning techniques for recognizing the

emotional states of autistic children. Microprocessors and Microsystems 74, 103–111. DOI: https://

doi.org/10.1016/j.micpro.2020.103111

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Published

2026-07-09

How to Cite

Hassan, L., Aminul, M. A., & Mamun, A. A. (2026). Integration of AI Agents in Recruitment: Opportunities and Challenges. Independent Business Review, 15(1), 56-70. https://ibr.iub.edu.bd/Journals/article/view/33

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