Leveraging AI Technology to Facilitate Innovation Management at System-of-Systems Level from Second-Order Science: A Study Based on VSM and Reflexivity Theory

The recognized importance of systemic and dynamic perspectives on both AI and innovation management calls for the retheorization to support the AI technology adoption in innovation management. As extant knowledge about a systems approach to realize dynamic roles of both augmentation and automation of AI-human collaboration in innovation management is limited, this study aims to explore how to leverage AI technology to facilitate innovation management at system-of-systems (SoS) level from second-order science systemically and dynamically. By doing so, different typologies of AI technology and innovation were first reviewed and identified, where the need to combine both AI technology and innovation as complex systems from second-order science is highlighted. Second, a key approach named Viable System Model (VSM) was argued as the one capable of setting the SoS level and providing a systemic framework for AI technology adoption. Third, the key theory of reflexivity was used as a support to understand the dynamic capability of VSM for the changing external environment in innovation management. Finally, a conceptual model of leveraging AI technology to innovation management at SoS from second-order science was built based on VSM and reflexivity. This study not only sheds new light on combining AI and innovation research from second-order science by combing systemic and dynamic perspectives but also provides managers instructions to leverage AI technology to innovation management from second-order science at SoS level.