Intelligence and the Future of Work: A Bibliometric Analysis of Job Displacement, Skills Transformation, and Workforce Adaptation
Abstract
Artificial intelligence is reshaping work through automation, augmentation, algorithmic management, and new demands for skills, yet the literature remains dispersed across management, technology, education, economics, and labor studies. This study maps the development and conceptual structure of research on intelligence and the future of work, with particular attention to job displacement, skills transformation, and workforce adaptation. Bibliographic records were retrieved from Scopus using a structured query combining artificial intelligence, future-oriented terms, work and employment concepts, automation and digital transformation, and impact-related terms. Following the documented screening process, 432 publications covering 1994 to 2025 were analyzed using BiblioSpy®. The corpus recorded 13,550 citations, an annual growth rate of 17.57%, 1,255 unique authors, and an international co-authorship rate of 17.13%. Publication output accelerated sharply after 2019, reaching 151 documents in 2025. The United States led publication output and total citations, while the United Kingdom showed the highest average citation rate among the ten leading countries. Keyword co-occurrence mapping of 432 eligible records identified four connected clusters centered on artificial intelligence, automation, machine learning, and digital transformation. Together, these clusters show that the field links technological capability to changes in employment, human-AI collaboration, education, digital skills, productivity, ethics, and labor-market adjustment. The study provides an integrated map of the field, distinguishes productivity from influence, and identifies a research agenda that emphasizes longitudinal evidence, occupation-level transitions, inclusive reskilling, responsible deployment, and broader participation from underrepresented labor-market contexts. This synthesis offers a basis for comparing how technological change, labor-market institutions, and organizational responses shape workforce outcomes across contexts.