Abstract
Abstract
Small and medium-sized enterprises (SMEs) play a critical role in economic growth yet remain disproportionately vulnerable to environmental turbulence. While entrepreneurial resilience has traditionally been explained through behavioural flexibility, leadership adaptability, and network embeddedness, comparatively limited attention has been given to the role of artificial intelligence (AI) as a strategic enabler of adaptive capacity. Existing research frequently positions AI adoption as a technological or efficiency-enhancing decision rather than as a capability-building mechanism within entrepreneurial contexts.
This developmental paper advances a conceptual framework that reconceptualises AI as a resilience-enabling strategic capability in SMEs. Drawing on Dynamic Capabilities Theory, the study argues that AI—particularly machine learning-based predictive analytics, optimisation algorithms, and decision-support systems—strengthens the core processes of sensing, seizing, and reconfiguring. By enhancing environmental scanning, improving decision precision, and enabling flexible resource reallocation, AI functions as an adaptive capability amplifier rather than merely an operational tool.
The framework develops five propositions linking AI integration to entrepreneurial resilience outcomes and identifies important boundary conditions, including founder digital literacy and organisational data maturity. The paper further argues that AI adoption may shift SMEs from reactive to anticipatory strategic behaviour by embedding probabilistic reasoning into managerial routines.
By integrating digital transformation research with entrepreneurial resilience scholarship, this study contributes to ongoing debates concerning the strategic implications of AI in small firm environments. The proposed framework offers a structured foundation for future empirical research, including survey-based and longitudinal studies examining how AI-enabled dynamic capabilities influence SME adaptation under uncertainty.