Future Economic Implications of Artificial Intelligence


  • Dr. A. Shaji George Independent Researcher, Chennai, Tamil Nadu, India




Automation, Job displacement, Reskilling, Productivity, Innovation, Regulation, Bias, Inequality, Growth, Ethics


The rise of artificial intelligence (AI) technology promises to substantially transform economies around the globe in the coming decades. This paper examines the likely economic impacts of advancing AI in areas such as jobs, business productivity, new markets, and policy challenges. It argues that while AI will displace many existing jobs through automation, it will also boost business productivity and lead to new products and markets that can expand opportunities. However, realizing the benefits of AI while mitigating downsides will require thoughtful policy responses. The paper first provides background on the acceleration of AI capabilities driven by machine learning and big data. It then discusses how AI automation of routine physical and cognitive tasks may disrupt labor markets, eliminating millions of jobs while also creating new skill demands. Next, it highlights AI’s potential to vastly augment business productivity and performance by automating routine processes and enhancing human capabilities. The creation of personalized AI services and intelligent robotics could also spawn new market opportunities. However, the paper notes AI may widen economic inequalities and create ethical dilemmas around regulation, workforce adaptation, and access to benefits. In conclusion, it argues that while AI’s economic impacts will be profound, its risks can be mitigated through collaborative policy efforts between government, industry, and academia focused on workforce transition support, equitable access, and responsible AI design. Careful management of AI’s economic transformation will allow societies to realize substantial prosperity and progress.




How to Cite

Dr. A. Shaji George. (2023). Future Economic Implications of Artificial Intelligence. Partners Universal International Research Journal, 2(3), 20–39. https://doi.org/10.5281/zenodo.8347639