Latest Brief
Brief No. 2 · 2026
From Resource Rigidity to Adaptive Capacity:
From Resource Rigidity to Adaptive Capacity:
Dynamic Capabilities in the Age of AI
The generative AI paradigm shift constitutes a discontinuous capability shock that systematically erodes incumbent firms' resource-based advantages. This analysis examines how the VRIN conditions underpinning sustained competitive advantage are restructured by AI, and how the Dynamic Capabilities framework — Sensing, Seizing, and Reconfiguring — defines the adaptive pathways through which incumbents achieve sustained competitive repositioning rather than capability-driven decline.
Read Full ArticleKey Data Points
72%
Organizations reporting AI adoption (2024)
Source: McKinsey Global Survey
Source: McKinsey Global Survey
40%
Productivity gain in AI-augmented knowledge work
Source: MIT, Stanford task-level studies
Source: MIT, Stanford task-level studies
$13T
AI contribution to global GDP by 2030
Source: McKinsey Global Institute
Source: McKinsey Global Institute
Theoretical Lens
RBV · Dynamic Capabilities Framework
Sensing – Seizing – Reconfiguring
Sensing – Seizing – Reconfiguring
Sources: McKinsey (2024), Stanford AI Index (2024), IMF SDN/2024/001, NBER WP 31161.
All Insights
Strategy
From Resource Rigidity to Adaptive Capacity: Dynamic Capabilities in the Age of AI
How the generative AI paradigm shift erodes RBV-based advantages and how incumbent firms sustain competitive advantage through sensing, seizing, and reconfiguring.
Trade Policy
US–China Supply Chain Fragmentation and Dynamic Capability Reconfiguration
US-China supply chain decoupling analyzed through the Dynamic Capabilities framework. Strategic implications at each stage: Sensing, Seizing, and Reconfiguring.