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

Adoption of Generative AI in Digital Product Performance: The Moderating Role of Human-AI Collaboration | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Adoption of Generative AI in Digital Product Performance: The Moderating Role of Human-AI Collaboration Jun Cui This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6588490/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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. Generative AI Digital Products Human-AI Collaboration Technology Adoption Structural Equation Modeling Innovation Performance SPSS AMOS software Full Text Additional Declarations The authors declare no competing interests. Participant Consent Statement Participation in this study was entirely voluntary and anonymous. Completion of the online survey was considered as provision of informed consent, as stated in the introductory section of the questionnaire. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Using \u0026nbsp;structural equation modeling and a cross-sectional survey of 284 digital product teams across \u0026nbsp;various industries, we develop and empirically test a theoretical model that explicates the \u0026nbsp;relationships between GAI adoption, digital product performance, and human-AI collaboration. \u0026nbsp;Results indicate that GAI adoption has a significant positive direct effect on digital product \u0026nbsp;performance (β = 0.437, p \u0026lt; 0.001). Moreover, human-AI collaboration positively moderates this \u0026nbsp;relationship (β = 0.218, p \u0026lt; 0.01), suggesting that stronger collaborative practices between humans \u0026nbsp;and AI systems amplify the performance benefits of GAI adoption. The findings contribute to the \u0026nbsp;emerging literature on AI implementation in digital product development and provide actionable \u0026nbsp;insights for practitioners seeking to optimize their AI integration strategies. 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