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The Impact of Generative Artificial Intelligence on Organizational Innovation Performance: Roles of AI Generated Content Quality, AI Experience, and AI Usage Environment

88 Citations2024
Haonan Xu, Ruoxuan Xu, Hongyu Lin
2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)

The findings reveal substantial positive effects of generative AI on enterprise innovation, and a conceptual model is formulated to elucidate the relationship between generative AI and enterprise innovation.

Abstract

With the progress of artificial intelligence (AI), generative AI has emerged as a novel catalyst for driving innovation within enterprises. This study, rooted in behavior activation theory, endeavors to examine the impact of generative AI on enterprise innovation. A conceptual model is formulated to elucidate the relationship between generative AI and enterprise innovation. Utilizing structural equation modeling to scrutinize this model, the findings reveal substantial positive effects: AI generated content quality significantly influences the activation of enterprise innovation behavior (ß = 0.37, t-value = 7.64, p < 0.01), AI experience has a notable positive impact on innovation behavior activation (ß = 0.19, t-value = 3.47, p < 0.01), and a supportive AI usage environment significantly influences the activation of enterprise innovation behavior (ß= 0.46, t-value = 10.48, p <0.01). Furthermore, innovation behavior activation makes a significant contribution to enterprise innovation performance (ß = 0.65, t-value = 18.23, p < 0.01).