The Impact of Generative AI on the Future of Work: Opportunities, Risks, and Human Skills

Background: Generative artificial intelligence (GenAI) has expanded the range of cognitive tasks that can be assisted by software, raising questions about productivity, job displacement, and the future value of human skills. Objective: To critically synthesize selected empirical and institutional evidence concerning productivity, occupational exposure, adoption, and skill complementarity. Methods: This narrative review draws on a purposively selected set of peer-reviewed studies, working papers, and institutional reports published primarily between 2023 and 2026. It does not claim systematic coverage or PRISMA-ScR compliance. Findings: Controlled experiments document substantial productivity gains for some writing and programming tasks, while workplace evidence suggests heterogeneity across experience levels. Occupational exposure estimates indicate the scope for task transformation but do not measure realized job losses. Adoption studies show that workplace use is growing, yet aggregate outcomes remain uncertain. Creative assistance may raise individual performance while narrowing output diversity. Conclusions: The future of work is better understood through task reallocation, complementary skills, organizational implementation, and distributional choices than through simple predictions of mass replacement. Further longitudinal and cross-country research is needed. Keywords: generative artificial intelligence; future of work; productivity; employment; occupational exposure; human skills; narrative review