Sensing Without Scale: How Platform-Delivered AI Reshapes Dynamic Capabilities in Emerging-Economy SMEs
Year: 2026
Type: preprint
Abstract: Small and medium-sized enterprises (SMEs) in emerging economies have historically competed without the functions that large firms take for granted: no environmental scanning unit, no analytics team, no strategic planning staff. Their disadvantage was, in part, a disadvantage of scale in sensing the environment and acting on what they sensed. Platform-delivered artificial intelligence (AI) — generative and agentic systems rented by subscription through cloud platforms — now offers versions of those missing functions at a price a small firm can pay. This conceptual paper asks what that change does to the dynamic capabilities explanation of SME performance. Drawing on the sensing–seizing–transforming framework, I argue that platform-delivered AI lowers the three capability barriers unevenly: it lowers the sensing barrier most, the seizing barrier only partially, and the transforming barrier least. The result is a "capability staircase" that narrows at the bottom rather than the top — small firms can increasingly see what large firms see, while remaining less able to commit resources to what they see and least able to reconfigure themselves around it. I further argue that rented capability creates new dependencies — on platforms, on data exposure, and on subscription economics — that the older literature on owned capability did not have to consider. I close with implications for SME owners, policymakers, platform providers and lenders, and three propositions for empirical research.
Source: Preprints.org
Author: Lalit Gautam
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7223875313