The Impact of Artificial Intelligence on Human Jobs in the Near Future: An Analysis

Abstract

The rapid proliferation of artificial intelligence (AI) technologies including machine learning, deep learning, robotic process automation, and natural language processing has triggered unprecedented discourse regarding the future of human employment. This research paper undertakes a comprehensive, multi-dimensional analysis of the impact of AI on human jobs in the near future (2025–2035), synthesizing empirical findings, theoretical models, and case studies from diverse economic sectors. Drawing upon the Technological Unemployment Theory, Skill-Biased Technological Change (SBTC) framework, and the Task-Based Model of the Labour Market, the paper examines patterns of job displacement, emerging occupational categories, sector-specific vulnerabilities, and the socioeconomic implications of AI-driven labour market transformation. The analysis reveals that while AI poses significant disruption to routine, cognitive, and manual task-intensive roles with an estimated 85 million jobs potentially displaced globally by 2025 (World Economic Forum, 2025) it simultaneously catalyzes the creation of approximately 97 million new roles, suggesting a net positive but highly unequal transition. The research identifies manufacturing, logistics, financial services, and customer support as sectors facing the highest displacement risks (40–70%), while healthcare, education, creative arts, and strategic management demonstrate greater resilience and opportunity for human-AI collaboration. The paper further argues that the magnitude of disruption is mediated by policy responsiveness, access to reskilling infrastructure, and the pace of institutional adaptation. Recommendations include universal reskilling programmes, adaptive regulatory frameworks, investment in lifelong learning ecosystems, and the development of a Human-AI Collaboration Index as a governance metric.