Track leaders:  

• Samuel Fosso Wamba, TBS Education, France 

• Maciel M. Queiroz, FGV EAESP, Brazil 

• Elaine Mosconi, Université de Sherbrooke, Canada 

 

This track explores in a multifaceted view how Artificial Intelligence (AI) is changing the way we manage technology and innovation. With the rapid and unprecedented growth of digital technologies, businesses across all sectors are experiencing profound impacts from digital transformation. This shift often necessitates adopting new strategies and innovative business models and developing dynamic capabilities, particularly in building data-driven enterprises. In this outlook, research in information technology, information science, knowledge management, and data analytics, for example, has helped us extract useful insights, improve innovation processes, and make better decisions. However, there are still gaps in our understanding of how AI affects data management, information retrieval, and its application in driving technological advancements and innovation.  Research investigating how AI, data-driven strategies, and information management are reshaping technology management and innovation is still scarce, mainly considering the strategies, deployment, and processes from generating ideas to putting them into action and creating a competitive edge in different industries. Additionally, there is an urgent need for research on AI and data analytics skills and knowledge from different actors and levels (e.g., individual, organizational, network) that are required to accept, adopt, and use digital technologies in technology management. Therefore, this track aims to invite scholars, researchers, industry practitioners, managers, and decision-makers to shed light, unlock, and identify at the individual, organizational, and inter-organizational levels the dynamics of AI in changing the way we manage technology and innovation.