Driving Factors of Generative AI Adoption in New Product Development Teams from a UTAUT Perspective

Recent new product development (NPD) teams apply various generative AI (GenAI) tools in the development process, yet it is not fully understood about the factors affecting teams' adoption of these tools. This research identifies factors driving the use and attitudes toward GenAI in NPD tasks based on the Unified Theory of Acceptance and Use of Technology (UTAUT). We interviewed nine GenAI users in NPD teams and conducted a survey study with 309 participants. By exploratory factor analysis and hierarchical regressions, we identified a composite factor of performance expectancy and anthropomorphism as the strongest positive predictor of attitudes, and task-tool fitness as the strongest positive predictor of behavioral intention. Besides, we also identified significant predictors including several other factors in UTAUT and individual differences in AI self-efficacy. The findings can be used for developing UTAUT models and designing GenAI tools specific to NPD purposes.