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

Research output: Contribution to journalArticlepeer-review

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 hightech 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 microfirms 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.
Original languageEnglish
Article number200566
JournalJournal of Strategy & Innovation
Volume37
Issue number1
DOIs
Publication statusAccepted/In press - 30 Jan 2026

Keywords

  • Artificial intelligence
  • Generative AI
  • High-tech Micro-firms
  • Risk management
  • Technology adoption

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