Transformative function of AI in talent acquisition
Lawrence, Salomie Valantina and Sankar Singh, K. (2026) Transformative function of AI in talent acquisition. In: PROCEEDINGS OF THE 2025 12TH INTERNATIONAL CONFERENCE ON MECHANICS, MATERIALS AND MANUFACTURING: ICMMM2025, 5–7 June 2025, Bangkok, Thailand.
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Abstract
AI technologies are to have continuous learning and adaptation. This paper details how AI is going to change talent acquisition by redefining the search, attraction, and retention of talent. Artificial intelligence tools in recruitment today are helping revolutionize each part of the process, from sourcing to screening, interviewing, and making decisions. Technologies enhance efficiency, make strategic roles within HR possible, facilitate data-driven decision-making, and put recruiters in a vantage position to identify and quickly engage qualified candidates. This paper also acknowledges the
challenges presented, including ethical concerns related to algorithmic decision-making and perpetuating biases that exist. Moreover, concerns grouping about lack of human touch during recruitment and heavy concerns on data privacy and security. Against these odds, AI can take away administrative load and allow human resource professionals to concentrate on strategic activities like talent development and workforce planning. In light of the above, the research thereby submits that these fast-changing AI technologies are a continuous learning process and adaptation of the same. Ultimately, although AI potentially imparts several benefits to talent acquisition, it requires the management of ethical, technical, and operational challenges for it to yield optimal recruitment results and to place organizations at the forefront of managing talent in the best way.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Management Studies > Human Resource Management |
| Domains: | Management Studies |
| Depositing User: | Mr IR Admin |
| Date Deposited: | 12 May 2026 10:22 |
| Last Modified: | 31 Jul 2026 05:08 |
| URI: | https://ir.vistas.ac.in/id/eprint/18925 |
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