Skill Forecasting and Reskilling in the Age of Automation

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Authors: Muhammad Shahzeb Khan, Syeda Masooma Zehra, Syed Muhammad Noaman Ahmed Shah, Salman Hameed
Cited by: 1
References: 14

Abstract

The accelerating integration of automation and artificial intelligence into the labor market necessitates a paradigm shift in workforce preparedness, emphasizing proactive skill forecasting and adaptive reskilling strategies. This chapter examines the critical role of AI in anticipating labor market evolution through real-time analysis of employment trends and emerging competency gaps. It further explores the application of AI in designing dynamic reskilling frameworks, incorporating personalized learning trajectories and immersive training methodologies to optimize skill acquisition. Performance metrics derived from AI-driven analytics enable continuous refinement of reskilling initiatives, ensuring alignment with evolving industry demands. Ultimately, the synthesis of predictive workforce analytics and AI-enhanced education models presents a scalable solution to mitigate technological displacement, fostering workforce resilience in an era of rapid automation. The findings underscore the imperative for policymakers, educators, and corporate entities.

Fields of Study & Subjects

AI and HR Technologies Labor market dynamics and wage inequality Artificial Intelligence Applications

Publication details

Journal / source
Advancing Organizational Excellence Through Human-Machine Synergy in Human Resources
Publisher
IGI Global Scientific Publishing
Pages
261–284
Publication date
2 April 2026
Language
NG
Document type
Book chapter