Artificial intelligence in sales (2017-early 2026): field consolidation and the rise of human-AI collaboration

This study examines the consolidation phase of artificial intelligence (AI) research in sales between 2017 and early 2026. Using a bibliometric analysis of Scopus data, with robustness checks across Web of Science, we identify the field’s intellectual and thematic structure during its rapid expansion. Contrary to the assumption that AI in sales primarily reflects a technological efficiency paradigm, we find three structural shifts. First, predictive analytics remains foundational but is increasingly embedded in human-AI collaboration. Second, interactional and trust-related themes move from peripheral to central, indicating a shift from performance optimization toward socio-technical integration. Third, legitimacy pressures such as transparency and corporate digital responsibility emerge as organizing dimensions rather than auxiliary concerns. Applying the TOE framework to explain these shifts across technological, organizational, and environmental dimensions, this study clarifies how AI in sales evolves through layering rather than replacement. The findings provide a research agenda for AI-enabled selling’s next phase.