Resilience Coefficient: Measuring the Strategic Adaptability of Long-Term Investors Triggered by Artificial Intelligence

Abstract

A core dilemma for long-term investors (LTIs) is that the very stability and patience which once defined them can breed strategic inertia. Artificial Intelligence (AI) is widely touted as the solution, yet conventional thinking often uncritically frames it as just a tool for efficiency. This study contends that this narrow perspective overlooks AI’s truly transformative role. This paper reconceptualizes AI as a catalytic force that operates on an organization's foundational elements. Its impact reaches deeper than accelerating processes to actively reshape how institutions function by rewriting routines, shifting mental models, and redirecting resources. This study identifies three types of AI triggers that target routines, cognitive frameworks, and resource allocation. Each category presents distinct avenues for value creation alongside significant risks. Crucially, the ultimate effect of AI is not determined by its technical specifications but by the organization's absorptive capacity and its ability to learn, integrate knowledge, and adapt. Integrating dynamic capabilities theory with a micro foundations perspective, this study proposes a conditional model that reframes the essential challenge from one of technology adoption to organizational adaptation. Ultimately, this framework provides leaders with a diagnostic tool for guiding transformation. It highlights that in the AI era, sustainable competitive advantage is rooted not in technology itself, but in an organization's fundamental capacity to learn.