Editorial: Artificial intelligence and the future of work: humans in control

Recent developments in artificial intelligence have generated both excitement about its potential to replace and complement human activities and concern about societal risks. The world of work is experiencing dramatic effects across jobs, wages, working conditions, recruitment, performance monitoring, and dismissal. Prior research has predominantly focused on potential job gains and losses, overlooking impacts on job quality, hours worked, worker mobility, labor relations, and broader societal effects such as environmental burdens. This editorial introduces a collection of nine contributions that expand the focus to these broader, multifaceted implications of AI for the future of work.

The editorial notes that existing research has largely centered on AI’s effects on employment levels (job gains and losses), with comparatively less attention to job quality, average hours worked, worker mobility, labor relations, and environmental impacts. The Research Topic addresses these gaps by bringing together studies that examine wage effects, working conditions, occupational safety and health, internal mobility, managerial control, and ethical frameworks.

• Employment and hours: Using an adapted AI occupational impact measure for 23 OECD countries, Georgieff and Hyee find no overall effect of AI exposure on employment growth. Occupations with high computer use experience faster employment growth when exposed to AI, while those with low computer use see declines in average hours worked without employment losses, indicating distributional rather than aggregate job effects.
• Wages: Fossen et al. report that wage effects depend on the technology. Software and industrial robots are associated with wage decreases (suggesting displacement), whereas AI innovations correlate with wage increases in the U.S., pointing to positive productivity effects.
• Policy responses to inequality: Merola reviews proposals to address AI-driven disparities, including robot taxes, digital taxation, share price taxation, and wage subsidies for low-income earners, assessing implications for employment growth, inequality, and innovation.
• Working conditions and flexibility: Warning et al., using a representative German business survey, show that occupations with high shares of routine cognitive tasks exposed to AI face higher demands for flexibility (self-organization and time management). These deteriorations in conditions disproportionately affect older workers and women.
• Occupational safety and health: Niehaus et al. find that AI increases autonomy in supervisory functions while reducing control over task execution, likely elevating psychological occupational stress beyond concerns over job or earnings loss.
• Internal mobility and HR analytics: Bossi et al. evaluate AI approaches to manage internal mobility to improve future job satisfaction, comparing statistical models and predictive HR analytics methods.
• Productivity–inequality–energy trilemma: Ernst argues that current AI trajectories create a trilemma that precludes simultaneous attainment of high productivity growth, low inequality, and reduced energy consumption, advocating a new technological paradigm prioritizing high social return domains (e.g., mobility, waste management, clean energy, natural capital solutions).
• Managerial control and surveillance: Woodcock’s case study of call centers details how AI-driven surveillance tools reshape managerial work and are contested by employees, influencing the extent and incidence of such tools.
• Ethical AI in the workplace: Cole et al. critique narrow ethical AI frameworks (privacy, transparency, non-discrimination) and propose operational principles to facilitate fairer working conditions and mitigate AI-related workplace risks and harms.

The assembled studies collectively demonstrate that AI’s impact on work extends far beyond headline employment counts. Findings highlight distributional effects across occupations, nuanced wage dynamics by technology type, shifts in working conditions and autonomy that can raise stress, and broader societal trade-offs involving productivity, inequality, and energy use. Managerial control is being transformed through AI-enabled surveillance, prompting workplace contestation, while ethical frameworks must evolve toward actionable principles to address concrete risks. Together, these insights address the overarching question of how AI affects not just the number of jobs but the quality, equity, and sustainability of work, underscoring the need for comprehensive policy and organizational responses.

This editorial synthesizes nine contributions that broaden understanding of AI’s multifaceted effects on the world of work, moving beyond simple job counts to encompass wages, working conditions, internal mobility, managerial control, ethics, and societal trade-offs. The collection aims to spur wider dialogue among researchers and policymakers and to inform the development of appropriate responses to ongoing transformations. It points toward future research on operational policy tools, organizational practices for fair AI deployment, and technological pathways that align productivity gains with equity and sustainability.