Change Agility as Dynamic Capability: Building AI-Driven Centers of Excellence for Organizational Resilience

Abstract

This paper explores how artificial intelligence (AI)-based Centers of Excellence (CoEs) can help to create a change agility as a dynamic capability to achieve organizational resilience. Although the prevalence of AI is high, where 71 out of 1000 companies have CoE in 2024, adaptive capacity is still elusive. Using a concurrent mixed-methods study, the study examined the information of 178 organizational leaders (C-suite executives, digital transformation officers, and CoE directors) working in 94 multinational companies. Based on the recently tested AI-Driven CoE Maturity Index (ACMI), the results show the organization with CoE Maturity Level 4 was 58 times faster in implementing any change and was 43 times more resilient than when it was at the baseline. On the other hand, the existence of immature CoEs was associated with 39% and 44% change initiative failure and workforce change preparedness erosion. There were five key design principles, namely, algorithmic sensemaking architectures, dynamic resource orchestration, cross-functional learning platform, adaptive governance protocol and resilience feedback loop. This article offers a proven diagnostic tool and implementation plan of CoEs that can change AI potential to organizational resilience. The practical suggestions include incorporating CoEs into strategic planning, promoting the level of algorithm literacy throughout the leadership levels, and developing dynamic ability measurements. The future studies need to examine longitudinal effects of competitive advantage and industry-specific patterns of adaptation.