IMPACT OF ARTIFICIAL INTELLIGENCE ON JOB AUTOMATION: A SYSTEMATIC REVIEW

Authors

  • Baharuddin Baharuddin Universitas Ichsan Sidenreng Rappang, South Sulawesi, Indonesia Author

DOI:

https://doi.org/10.62207/zcz2yn27

Keywords:

job automation, artificial intelligence, retraining, social inequality, inclusive policies, algorithmic bias

Abstract

AI-driven job automation has driven global economic transformation, increased efficiency and created innovation opportunities, but has also presented serious challenges such as structural unemployment and social inequality. This research aims to explore mitigation strategies through policy analysis, retraining, and ethical approaches in technology development. Using a systematic literature review method, this study found that AI-based training and multisectoral collaboration are effective approaches to support workforce transition. The results of this research provide practical insights for governments and companies in creating inclusive strategies to mitigate the negative impacts of automation.

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Published

2024-10-10

How to Cite

IMPACT OF ARTIFICIAL INTELLIGENCE ON JOB AUTOMATION: A SYSTEMATIC REVIEW. (2024). Information Technology Studies Journal (ITECH), 1(3), 102-119. https://doi.org/10.62207/zcz2yn27