AI for the underdogs: Navigating risk and growth in high-tech micro-firms through generative artificial intelligence
Faisal Shahzad, Mohammad Tayeenul Hoque, Iqra Sadaf Khan, Ahmad Arslan
Abstract
Generative Artificial Intelligence (Gen-AI) has gained significant traction in larger firms, yet its adoption among micro-firms remains underexplored particularly in contexts marked by resource scarcity and heightened operational risk. This study addresses this gap by investigating how high-tech micro-firms adopt Gen-AI for risk management and growth. Drawing on semi-structured interviews with decision-makers from eight Finnish micro-firms, the research applies the Technology-Organization-Environment (TOE) framework to identify critical enablers and barriers. The findings highlight five key dimensions influencing adoption: technological readiness, leadership engagement, regulatory compliance, data-driven decision-making, and competitive pressures. While Gen-AI fosters operational resilience and strategic agility, its impact is constrained by limited data quality and high implementation costs. By offering a holistic and theoretically grounded perspective, this study advances understanding of Gen-AI adoption in micro-firms and contributes to literature on digital transformation under resource constraints. The insights also inform policymakers and practitioners aiming to enhance AI accessibility and governance for micro-enterprises.