A Survey on Automation and its Impact on Employment and Skill Transformation in the IT Sector
Keywords:
Automation, Artificial Intelligence, IT employment, Job displacement, Reskilling, Workforce transformationAbstract
Technologies in automation driven by Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA) are revolutionizing the Information Technology (IT) industry. Automation is not only changing productivity, operational efficiency, and service delivery in the IT sector but also affecting employment. This study focuses on the impact of automation on IT employment, considering both the negative and positive effects. Automation in IT is affecting employment in terms of job destruction in routine and rule-based jobs, as well as job creation in emerging areas such as AI engineering, cloud computing, and cybersecurity. According to this research, there is a rising need for high-level technical skills, critical thinking, and reskilling among IT professionals. The results show that automation is not destroying jobs but changing their nature and structure in organizations. With the evolution of automation technologies in the IT sector, the workforce must learn to adapt to such changes through continuous learning and skill development.
References
E. Filippi, M. Bannò, and S. Trento, “Automation technologies and their impact on employment: A review, synthesis and future research agenda,” Technological Forecasting and Social Change, vol. 191, Art. no. 122448, Jun. 2023.
M. J. Handel, “Growth trends for selected occupations considered at risk from automation,” Monthly Labor Review, Jul. 2022.
D. Deckker, “Artificial intelligence and the future of job security: A narrative review of risks, resilience, and policy responses,” International Journal of Research and Innovation in Social Science, Jan. 2025.
H. Schwabe and F. Castellacci, “Automation, workers’ skills and job satisfaction,” PLoS One, vol. 15, no. 11, Art. no. e0242929, Nov. 2020.
N. J. Itoe Mote and G. Karadas, “The impact of automation and knowledge workers on employees’ outcomes: Mediating role of knowledge transfer,” Sustainability, vol. 14, no. 3, Art. no. 1377, Jan. 2022.
D. Xu, H. Yang, M.-A. Rizoiu, and G. Xu, “Being automated or not? Risk identification of occupations with graph neural networks,” Proceedings of the International Conference on Advanced Data Mining and Applications (ADMA 2022, Cham, Switzerland: Springer, 2022, pp. 520–534.
P. Ozgul, M. C. Fregin, M. Stops, S. Janssen, and M. Levels, “High-skilled human workers in non-routine jobs are susceptible to AI automation but wage benefits differ between occupations,” Arxiv preprint arXiv:2404.06472, Apr. 2024.
V. R. Ganuthula and K. K. Balaraman, “Skill-based labor market polarization in the age of AI: A comparative analysis of India and the United States,” arXiv preprint arXiv:2501.15809, Jan. 2025.
C. B. Frey and M. A. Osborne, “The future of employment: How susceptible are jobs to computerisation?,” Technological Forecasting and Social Change, vol. 114, pp. 254–280, Jan. 2017.
S. Joshi, “The transformative impact of artificial intelligence on US labor markets: Workforce disruption, skill evolution, and the emergence of prompt engineering,” SSRN Electronic Journal, Oct. 2025.
