The Impact of AI on Decision-Making Agility in SMEs

Abstract Artificial Intelligence (AI) has emerged as one of the most transformative forces shaping modern business, enabling organizations to make faster, smarter, and more adaptive decisions in an increasingly dynamic environment. While large corporations have already integrated AI into their strategic and operational processes, Small and Medium Enterprises (SMEs) often face challenges in understanding, adopting, and effectively utilizing these technologies. The capacity to make agile decisions quickly sensing changes and responding to them has become critical for SMEs seeking to maintain competitiveness in today’s volatile markets. This thesis explores how AI contributes to enhancing decision-making agility within SMEs and examines the broader implications of this transformation for business strategy and organizational performance. It discusses how AI-driven tools such as machine learning, natural language processing, predictive analytics, and robotic process automation are reshaping the foundations of business intelligence and strategic flexibility. The study also highlights the barriers that prevent smaller firms from fully exploiting AI’s potential, including financial constraints, lack of technical expertise, and concerns over data quality and privacy. By connecting insights from recent academic literature, international reports, and empirical evidence from SMEs, this work contributes to understanding the relationship between AI adoption and organizational agility. The findings underline that AI is not only a technological enabler but also a strategic catalyst that empowers SMEs to operate with greater responsiveness, resilience, and innovation in an ever-changing business landscape.