ARTIFICIAL INTELLIGENCE AND THE TRANSFORMATION OF EMPLOYMENT AND PRODUCTIVITY IN THE SERVICE SECTOR: A SYSTEMATIC REVIEW

Artificial intelligence is increasingly transforming work processes, employment structures, and productivity outcomes, particularly within service-sector economies. While existing research has extensively debated the potential of AI to displace jobs, less attention has been paid to the combined analysis of employment and productivity effects within service-oriented contexts. This study addresses this gap by conducting a systematic literature review of peer-reviewed research published between 2019 and 2025, drawing from economics, management, and information systems scholarship. The review synthesizes evidence on how AI adoption reshapes task composition, alters skill demand, and influences productivity performance in service organizations. The findings indicate that AI functions predominantly as a labor-augmenting technology in the service sector, reconfiguring work rather than eliminating employment, while productivity gains depend heavily on organizational readiness, workforce reskilling, and ethical implementation practices. By integrating employment, productivity, and well-being perspectives, the study contributes to ongoing debates on human-centered AI and highlights policy and managerial implications for inclusive and sustainable AI adoption in service-based economies.