Barriers to the implementation of artificial intelligence in small and medium-sized enterprises: Pilot study

Aim/purpose – This pilot study explores the main obstacles hindering the effective implementation of Artificial Intelligence (AI) in small and medium-sized companies (SMEs). By thoroughly understanding these barriers, organizations can develop customized strategies and interventions to overcome them, facilitating smoother and more successful AI adoption. The paper’s primary goal is to help organizations understand the barriers to AI adoption to develop tailored strategies and interventions to overcome these challenges, leading to a more efficient and successful integration of AI. Through a rigorous examination of real-world experiences and perceptions, this paper seeks to elucidate the multifaceted challenges that impede the effective deployment of AI solutions. Design/methodology/approach – The study identifies four main impediments to AI implementation based on data from 22 interviews with industry experts in the Czech Republic and Austria. Findings – First, a notable lack of trust emerges as a significant barrier, with stakeholders harboring apprehensions regarding AI’s reliability, ethical implications, or potential consequences. Second, the knowledge gap hampers progress, indicating a need for better understanding and expertise in AI technologies and applications. Third, infrastructure limitations, including inadequate computing resources, outdated systems, or insufficient technical support, pose a challenge. Lastly, a shortage of skilled professionals proficient in AI further complicates implementation efforts, highlighting the importance of nurturing talent and expertise. Research implications/limitations – The findings regarding AI implementation strategies are significant for small and medium-sized enterprises. Although the research focuses on Czech and Austrian companies, the findings may apply to other countries. Additionally, it is worth noting that this is qualitative research with a smaller sample size. Originality/value/contribution – By addressing these barriers proactively, organizations can navigate the complexities of AI adoption more effectively and unlock its transformative potential.