Managing the Unknown: Strategic Decision-Making in SME AI Adoption

Abstract

As Artificial intelligence (AI) becomes increasingly integrated into businesses and organizational life, small and medium-sized enterprises (SMEs) face new strategic dilemmas about how exactly to adopt and use these technologies. While larger corporations often follow formal strategies made by experts and supported by dedicated resources and higher budgets, little is known about how smaller firms navigate AI integration given the limited resources. This thesis addresses this gap by exploring AI adoption strategies across different Swedish SMEs and a national Swedish organization dedicated to promoting AI implementation. The research uses a qualitative approach, and 18 semi-structured interviews were conducted with managers in the tech field, focusing on their daily practices with various AI applications. By utilizing the Technology-Organization-Environment (TOE) framework and Mintzberg and Waters’ (1985) theory of deliberate and emergent strategies, the study shows how AI adoption in SMEs is often driven by employee initiatives, informal experimentation and constant learning rather than top-down deliberate planning. More specifically a pattern of “Umbrella strategy” emerges, where leadership provides general direction while the actual implementation is decentralized and adaptive. All in all, this research contributes to management literature by showing how AI adoption unfolds through emergent practices and positions AI not just as a tool or a technological asset but as a catalyst for operational and strategic transformation of SMEs.