AI as a cognitive collaborator: Assimilation and accommodation in human–machine teaming for innovation
Min Jae Park
Abstract
This study investigates how generative artificial intelligence (GenAI) transforms collaborative innovation by serving not only as a productivity tool but also as a cognitive partner in workplace problem-solving. Drawing on Piaget’s theory of assimilation and accommodation, we propose that the impact of GenAI depends on how users cognitively engage with it, either by fitting it into existing schemas (assimilation) or using it to restructure mental models and workflows (accommodation). To address our hypotheses, we conducted a randomized 2 × 2 factorial field experiment involving 371 professionals in South Korea to compare individuals and teams with or without access to GenAI. Participants completed an open-ended innovation challenge, and their cognitive strategies, emotional responses, and solution outcomes were measured using surveys, behavioral data, and expert evaluations. The results show that GenAI significantly improves innovation quality and emotional engagement, especially when users adopt accommodative strategies. Furthermore, accommodation mediates the integration of cross-functional knowledge, suggesting that cognitive adaptation is a critical mechanism for unlocking GenAI’s collaborative potential. These findings provide new theoretical insights into human–AI teaming, highlighting the importance of organizational support for cognitive flexibility in AI adoption. We conclude that GenAI’s value is maximized not through passive use, but through reflective collaboration and schema-level transformation.