Integration of AI agents in recruitment: opportunities and 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.