Enhancing Job Design with Artificial Intelligence: What We Know and What Lies Ahead

Abstract

As businesses undergo digital transformation, artificial intelligence (AI) is reshaping job design by automating tasks and redefining human roles. This shift presents a critical challenge for human resource professionals and managers: how to integrate AI into work while maintaining productivity, fairness, and employee well-being. To clarify the evolving landscape, this study synthesizes the state-of-the-art literature on AI-driven job design through a multi-technique bibliometric analysis and a systematic literature review, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyzing 67 Scopus-indexed publications, we use descriptive bibliometrics, co-authorship mapping, bibliographic coupling, and co-occurrence analysis to trace past research directions and outline a future research agenda. Our findings reveal key themes, including AI’s impact on job characteristics, data-driven human resource management (HRM) practices, group-level AI integration, emerging job skills, human-AI trust, labor relations, and algorithmic HRM. As one of the first bibliometric studies in this field, this research provides a foundational framework for understanding AI’s role in job design and identifies seven distinct pathways for future investigation.