Making AI work for workers

AI advances are shifting the balance of work and capital. The essay identifies three policy and business levers to keep workers better positioned as AI automates tasks: reduce monopoly, create new demand and reskill the workforce.

Large, concentrated AI firms capture a disproportionate share of productivity gains. When a few firms control critical models, training data and cloud infrastructure, the labor-market effects concentrate too: firms with more capital-intensive, AI-driven production expand returns to capital while shrinking labor's share. Reducing monopoly power can help distribute gains more broadly across employers and regions, which in turn creates more employer-side options for workers.

AI will automate many tasks, but not all job functions vanish at once. The essay points to demand creation as a pragmatic route to preserve and grow employment: by encouraging new services, products and business models that complement AI, economies can generate roles that require human judgment, social skills or hands-on capabilities. Examples in the piece include the growing use of humanoid and physical AI in manufacturing and services, which opens support, maintenance and hybrid human–machine positions.

Reskilling and workforce transition

Reskilling is central to the argument. Employers, governments and educational institutions must coordinate to design retraining that maps to realistic labor-market needs. Programs should be targeted, short enough to be practical and tied to actual vacancies. The goal is not generic upskilling but preparing workers for the new tasks and occupations that arise as firms adopt AI.

The author recommends a combined approach rather than single fixes. Antitrust and competition policy can limit excessive concentration. Industrial and fiscal policies can stimulate sectors that generate human-centered roles. Labor-market and education policy can fund and certify retraining pathways so displaced workers have clear transitions into available jobs.

If you are a policymaker, labor leader, employer or worker, focus on three tasks: prevent excessive concentration in AI markets, invest in sectors and services that generate human work, and align retraining programs with concrete job openings. These actions increase the chances that AI's productivity gains translate into broader employment opportunities rather than concentrated wealth for a few firms.