GenAI and Creative Labor: New Evidence on Valuation,Inequality,and Adoption

Abstract

Creative work has long been viewed as resistant to automation, grounded in human capacities for judgment, interpretation, and expression. The rapid diffusion of generative artificial intelligence (GenAI) challenges this assumption by introducing tools capable of producing plausible creative outputs and destabilizing the boundary between assistance and substitution. This editorial introduces a special issue on AI and creative labor and advances a sociological framework for understanding how GenAI is reorganizing creative work through processes of valuation, collaboration, and inequality. Bringing together four empirical articles and new evidence from a 2025 SNAAP Pulse survey of more than 2,000 arts and design alumni, we examine how GenAI is unevenly incorporated across occupations, workflows, and labor market positions. We show that GenAI adoption among creative workers is not driven by a single logic of efficiency, but is shaped by precarity, autonomy, training, occupational norms, and the visibility of AI within production processes. The findings highlight three core dynamics. First, creativity is increasingly distributed across human and machine contributions, with AI used to augment non-core tasks while reconfiguring authorship and skill. Second, authenticity emerges as a socially organized and context-dependent achievement, with concerns about dilution broadly shared but concerns about social judgment varying across occupations and workflows. Third, inequality operates both downstream and upstream, through unequal capacity to adopt and benefit from AI. Taken together, the special issue and new survey evidence demonstrate that GenAI is reorganizing creative labor unevenly, raising fundamental questions about expertise, authorship, and authority to define value in an AI-mediated economy.