Towards Conceptualizing Ai Washing: Unpacking The Characteristics, Motivations, And Consequences

The rise of artificial intelligence (AI) has spurred an emerging phenomenon: AI washing, which is commonly vaguely described as an analogy to greenwashing. Despite its societal and economic relevance, AI washing remains underexplored in research. Drawing on a phenomenon-driven theorizing approach, we present findings of two studies. First, we analyze regulatory documents and media reports to unpack the focal dimensions, motivations and consequences of AI washing. Based on this qualitative analysis, we propose an empirically grounded definition of AI washing and derive a theoretical model conceptualizing AI washing as a self-reinforcing process that challenges AI authenticity and generates consequences for consumers and businesses. Second, we conducted interviews to understand how consumers as one of the groups most directly affected by AI washing, react to it. Our study lays the foundation for further theorizing AI washing and offers a base to address psychological, communicative, and regulatory aspects of this emerging phenomenon.