Abstract
This study investigates how Performative Artificial Intelligence (AI), an active form of AI that enacts phenomena, boundaries, and control, supports supply chains in building temporal resilience. Temporal resilience is examined through three main responses: adjusting, absorbing, and adopting. We further explore how the intensity of extreme event contexts, namely emergency and disruptive contexts, moderates these relationships. Using a mixed-methods design, the study draws on survey data from 252 U.S. business-to-business (B2B) organizations and qualitative insights from 53 structured interviews. The findings demonstrate that Performative AI contributes to all three temporal resilience responses, with the strength of most of these relationships influenced by the intensity of the extreme event context. This research primarily contributes to the supply chain literature by conceptualizing and empirically validating Performative AI as a resilience enabler in technologically mature B2B environments, and by extending temporal resilience theory to organizational and supply chain levels. The study also highlights the growing importance of AI for organizations and supply chains to respond effectively to disruptions, mitigating the impact on their time-based operations.
•Introduces “Performative AI” as active AI that enacts actions and boundaries to enhance resilience.•Examines temporal resilience via adjusting, absorbing, and adapting in supply chains.•Uses mixed methods: survey data from 252 U.S. B2B firms and 53 structured interviews.•Finds Performative AI strengthens resilience, moderated by intensity of extreme events.•Extends resilience theory, positioning Performative AI as key to adaptive supply chains.