Citation
Abstract
Artificial Intelligence (AI) in the industry 4.0 based technologies is becoming omnipresent and changing the workforce environment from traditional to digital and virtual. While technology continues to evolve, new jobs will be created and the job landscape requires advanced competency elements for new employment forms and processes. The demand for some occupational skills will decline, while others grow, and the transition is likely disruptive, with skill requirements shifting significantly. In the Southeast Asia (SEA) region specifically, there has been a rapid increase in the adoption of AI but empirical approach to competencies is still underdeveloped. Hence, this study sought to fill this gap by conducting a systematic literature review on the competencies required during the intervention of AI in the SEA region. This study conducted a systematic review following the PRISMA publication standard. The articles were selected from two main databases of Scopus and Google Scholar. Based on the thematic analysis, the results revealed four main themes, namely i) technological competency; ii) cognitive competency; iii) social and emotional competency; and iv) change management competency. The four main themes have further produced 15 sub-themes highlighting the uniqueness of human soft skills that are still required although AI is adopted. Based on the pattern of past research, the review presented several recommendations for further consideration by scholars, organisations and communities.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Educational Studies |
DOI Number: | https://doi.org/10.6007/ijarems/v12-i1/15891 |
Publisher: | Human Resource Management Academic Research Society |
Keywords: | Artificial intelligence; Employee competencies; Southeast asia; Systematic literature review; Industry 4.0; Decent work; Economic growth |
Depositing User: | Ms. Nur Aina Ahmad Mustafa |
Date Deposited: | 07 Oct 2024 01:19 |
Last Modified: | 07 Oct 2024 01:19 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.6007/ijarems/v12-i1/15891 |
URI: | http://psasir.upm.edu.my/id/eprint/107665 |
Statistic Details: | View Download Statistic |
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