Using explainable artificial intelligence to envision the future of work and the workforce – from prediction to explanation

Despite extensive research on the future of work, our understanding remains limited, leaving us ill-prepared for the evolving workforce requirements. Much of the literature focuses on job displacement caused by artificial intelligence (AI) and automation, assuming future work consists merely of "leftovers" after technology takes over. This perspective overlooks which types of work will thrive and emerge in the upcoming future. To address this knowledge gap, the present study employs Explainable AI (XAI) on data from the Occupational Information Network (O∗NET) and the U.S. Bureau of Labor Statistics (BLS) to identify emerging work and workforce archetypes, along with the most in-demand competencies, while contrasting them with those expected to decline by 2031. The results reveal ten rapidly growing work archetypes—Creatives, Sages, Wizards, Supporters, Nurturers, Caregivers, Explorers, Hands-On, Data Scientists, and Frontliners—in contrast to six archetypes facing declines across technical, operative, and administrative domains. The study further identifies eight fastest-growing worker archetypes, including Strategic Tech Workers, Workers of Technology/Engineering Design, Tech-Driven Leadership and Management, Agile Healthcare Workers, Business Analytics Workers, and Empathetic Leaders, emphasizing hybrid talents. Conversely, the four fastest-declining worker archetypes are highly specialized in the technical and administrative roles. Finally, the study outlines the most in-demand workforce competencies, highlighting the need for blended capabilities encompassing technical expertise (Telecommunications, Engineering and Technology, Computers and Electronics), human-centered skills (Customer and Personal Service, Active Listening, Social Perceptiveness, Concern for Others, Relationship Building), as well as analytical and adaptive capabilities (Active Learning, Troubleshooting, Fluency of Ideas, Initiative, Analytical Thinking, Adaptability/Flexibility). These findings offer significant implications for individuals, organizations, educators, and policymakers to navigate the complex interplay between technological advancement and workforce transformation, offering critical insights for managing the social and economic dynamics of our technological future.