AI AND THE RESTRUCTURING OF JOB'S AND CODING

The research investigates how Artificial Intelligence (AI) affects employment structures and coding practices from 2015 until 2026. The research examines task automation together with productivity measurement systems and workforce development patterns to show how artificial intelligence technology is changing both employment systems and workplace environments. The research results show that organizations do not mostly experience job losses when they implement artificial intelligence systems. The main impact of AI systems results in companies redistributing tasks among their existing job positions. The industry moves toward automation of basic coding tasks while employees dedicate their efforts to advanced duties which involve creative thought and decision making and solving difficult issues. The research demonstrates that software development processes achieved major productivity and efficiency gains through its findings. AI-powered tools deliver benefits through their ability to execute tasks at higher speed while they enhance code quality and streamline operational activities. The advantages of the system come with new skill needs which demand employees to develop higher levels of technical and cognitive skills. The study reached another main finding which shows that labor markets have started to experience polarization. The demand for entry-level and routine jobs has decreased while high-skilled positions show continuous growth. People must develop their skills through learning and adaptability to maintain their job security within AI-based work environments. Research findings show that AI technologies do not eliminate coding jobs but instead create new requirements for those positions. The long-term effects of these modifications will depend on how well people and organizations and institutions can handle technological progress. The development of effective reskilling methods needs policies that support workforce inclusion to help distribute AI advantages throughout society.

[1] C. B. Frey and M. A. Osborne, “The Future of Employment: How Susceptible Are Jobs to Computerization?,” Technological Forecasting and Social Change, vol. 114, pp. 254–280, 2017.   [2] E. Brynjolfsson and A. McAfee, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York, NY, USA: W. W. Norton, 2014.   [3] E. Brynjolfsson and A. McAfee, “Artificial Intelligence, Automation, and the Economy,” NBER Working Paper No. 24449, 2018.   [4] D. Autor, “Why Are There Still So Many Jobs? The History and Future of Workplace Automation,” Journal of Economic Perspectives, vol. 29, no. 3, pp. 3–30, 2015.   [5] D. H. Autor, F. Levy, and R. J. Murnane, “The Skill Content of Recent Technological Change,” Quarterly Journal of Economics, vol. 118, no. 4, pp. 1279–1333, 2003.   [6] M. Arntz, T. Gregory, and U. Zierahn, “The Risk of Automation for Jobs in OECD Countries,” OECD Social, Employment and Migration Working Papers, no. 189, 2016.   [7] World Economic Forum, The Future of Jobs Report 2020. Geneva, Switzerland, 2020.   [8] World Economic Forum, The Future of Jobs Report 2023. Geneva, Switzerland, 2023.   [9] McKinsey Global Institute, Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation, 2017.   [10] McKinsey Global Institute, The Future of Work After COVID-19, 2021.