Adoption of Generative AI in Digital Product Performance: The Moderating Role of Human-AI Collaboration

This study investigates the impact of generative artificial intelligence (GAI) adoption on digital product performance while examining the moderating effect of human-AI collaboration. Using structural equation modeling and a cross-sectional survey of 284 digital product teams across various industries, we develop and empirically test a theoretical model that explicates the relationships between GAI adoption, digital product performance, and human-AI collaboration. Results indicate that GAI adoption has a significant positive direct effect on digital product performance (β = 0.437, p < 0.001). Moreover, human-AI collaboration positively moderates this relationship (β = 0.218, p < 0.01), suggesting that stronger collaborative practices between humans and AI systems amplify the performance benefits of GAI adoption. The findings contribute to the emerging literature on AI implementation in digital product development and provide actionable insights for practitioners seeking to optimize their AI integration strategies. This research addresses the critical gap in understanding sociotechnical dynamics in GAI implementation and offers a foundation for future research on human-AI collaborative systems.