Pengaruh Artificial Intelligence in Talent Development dan Talent Acquisition Terhadap Efektivitas Pengembangan SDM

Authors

  • Mugi Puspita Universitas Informatika dan Bisnis Indonesia
  • Yuli Nurfitriani Universitas Informatika dan Bisnis Indonesia

DOI:

https://doi.org/10.37278/eprofit.v7i2.1371

Keywords:

Manajemen Talenta, Artificial Intelligence, AI for Talent Development, AI for Talent Acquisition, Sumber Daya Manusia

Abstract

Penelitian ini bertujuan untuk menganalisis Pengaruh Artificial Intelligence in Talent Development dan Talent Acquisition Terhadap Efektivitas Pengembangan SDM   pada sektor manufaktur di Jawa Barat. Metode penelitian menggunakan pendekatan kuantitatif dengan teknik analisis Partial Least Squares Structural Equation Modeling (PLS-SEM). Populasi penelitian adalah perusahaan manufaktur di Jawa Barat yang sudah menggunakan teknologi AI pada penerapan manajemen talenta. Sampel diperoleh dengan menggunakan purposive sampling sebanyak 48 perusahaan. Data dikumpulkan melalui kuesioner yang disebarkan kepada responden yang terlibat dalam pengelolaan SDM. Hasil penelitian menunjukkan bahwa AI for Talent Development berpengaruh positif dan signifikan terhadap efektivitas pengembangan SDM, dengan nilai koefisien inner weight sebesar 0,578 dan p-value 0,02. Demikian pula, AI for Talent Acquisition terbukti berpengaruh signifikan dengan nilai koefisien 0,349 dan p-value 0,01. Penelitian ini merekomendasikan penerapan teknologi AI secara terintegrasi sebagai strategi penting untuk efektivitas pengembangan SDM di era transformasi digital.

References

Bahl, S., Kaur, P., & Ali, F. (2022). Artificial intelligence in talent management: A review and research agenda. International Journal of Human Resource Management, 33(4), 789–815. https://doi.org/10.1080/09585192.2021.1939943

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108

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

Chatterjee, S., Rana, N. P., Tamilmani, K., & Sharma, A. (2023). Examining the role of artificial intelligence in workforce learning and development. Computers in Human Behavior, 140, 107562. https://doi.org/10.1016/j.chb.2022.107562

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications. https://doi.org/10.4135/9781071804117

Huang, M.-H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30–50. https://doi.org/10.1007/s11747-020-00749-9

Jatobá, V. F., Gomes, M. F., & de Oliveira, J. (2023). Artificial intelligence in human resource management: A systematic literature review. Journal of Business Research, 155, 113426. https://doi.org/10.1016/j.jbusres.2022.113426

Rana, N. P., Dwivedi, Y. K., Hughes, L., & Wright, R. (2022). Exploring the role of AI in HRM: A systematic review and future research agenda. Technological Forecasting and Social Change, 179, 121650. https://doi.org/10.1016/j.techfore.2022.121650

Osly Usman, Suryadi, & Rindi Nurlaila Sari. (2025). The Effect of AI Integration in HR Practices on Employee Performance: Mediating Roles of Engagement and Perceived Job Security. Bina Bangsa International Journal of Business and Management, 5(2), 529-541.

Prasetyo, D. (2023). Artificial Intelligence, Big Data, and Deep Learning in Human Capital Management: Evidence from Indonesia. Journal of Human Resource and Digital Transformation, 5(2), 87–99.

Rahman, A., & Lee, C. (2022). Challenges of AI integration in human resource management: Employee resistance and ethical concerns. Asia Pacific Journal of Management Research and Innovation, 18(3), 155–168. https://doi.org/10.1177/2319510X221098547

Suryadi, T., & Sari, N. (2025). Artificial intelligence adoption, employee training, and human resource performance: Evidence from manufacturing companies in Indonesia. International Journal of Strategic Human Capital, 9(1), 45–62.

Upadhyay, A. K., & Khandelwal, K. (2018). Applying artificial intelligence: Implications for recruitment. Strategic HR Review, 17(5), 255–258. https://doi.org/10.1108/SHR-07-2018-0050

van Esch, P., Black, J. S., & Ferolie, J. (2021). Marketing AI recruitment: The next phase in job applicant sourcing. Journal of Business Research, 124, 353–365. https://doi.org/10.1016/j.jbusres.2020.11.013

Downloads

Published

2025-10-24

How to Cite

Puspita, M., & Nurfitriani, Y. (2025). Pengaruh Artificial Intelligence in Talent Development dan Talent Acquisition Terhadap Efektivitas Pengembangan SDM . Economics Professional in Action (E-Profit), 7(2), 212–220. https://doi.org/10.37278/eprofit.v7i2.1371

Issue

Vol. 7 No. 2 (2025): Economic Professional in Action (E-PROFIT)

Section

Articles

License

Copyright (c) 2025 Mugi Puspita, Yuli Nurfitriani

Creative Commons License

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

Authors who publish articles in Economics Professional in Action (E-Profit) agree to the following terms:

  1. Authors retain copyright of the article and grant the journal right of first publication with the work simultaneously licensed under a CC-BY-SA or The Creative Commons Attribution-ShareAlike License.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).