The Transformative Impact of AI and Automation on Employment Patterns: An Analysis of Workforce Adaptation, Skills Demand, and Socioeconomic Inequality in the Digital Age

  • Intekhab Alam
  • Show Author Details
  • Intekhab Alam

    Student at Aligarh Muslim University, India

  • img Download Full Paper

Abstract

The Rapid advancement of artificial intelligence (AI) and automation technologies is fundamentally altering employment patterns across the globe. This study investigates the multifaceted impact of these technologies on the labour market, focusing on workforce adaptation, evolving skills demand, and the widening socioeconomic inequalities in the digital era. While automation threatens to displace millions of routine jobs, it simultaneously generates new opportunities requiring advanced technical and cognitive skills. The research explores how workers and organizations adjust to these changes through reskilling and upskilling initiatives, as well as the role of policy frameworks in shaping equitable labour market outcomes. By analysing sectoral variations and demographic disparities, this paper highlights the challenges and opportunities presented by the ongoing digital transformation. The findings underscore the need for comprehensive strategies to foster inclusive growth, mitigate inequality, and prepare the workforce for the demands of a technology-driven future.

Keywords

  • labour market transformation
  • workforce adaptation
  • skills development
  • socioeconomic inequality
  • digital economy

Type

Research Paper

Information

International Journal of Law Management and Humanities, Volume 8, Issue 4, Page 2299 - 2308

DOI: https://doij.org/10.10000/IJLMH.1110689

Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution -NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.

Copyright

Copyright © IJLMH 2021