ARTIFICIAL INTELLIGENCE ADOPTION CHALLENGES IN THE SMALL AND MEDIUM-SIZED ENTERPRISE SECTOR: A COMPARATIVE ANALYSIS OF POLAND, GERMANY AND DENMARK

Abstract

Background and Objective: Recognising the vital role of SMEs in driving economic growth and the uneven AI adoption levels across EU countries, this article explores AI adoption within SMEs in Poland, Germany and Denmark, highlighting the barriers they face. The study aims to enhance understanding of the factors that hinder SMEs from adopting AI technology. Recognising and addressing these challenges is essential for SMEs to succeed.

Materials and Methods: The study compares AI adoption in the SME sectors of Poland, Germany and Denmark within the EU context, focusing on the barriers and challenges. The article synthesises cross-country evidence from prior empirical studies and statistics drawn from Eurostat databases and the Digital Economy and Society Index.

Results: Internal capabilities are the strongest predictors of AI adoption, and environmental support is helpful only when institutions are mature. Barriers typically cluster, with varying intensity, around data availability and quality, skills gaps, costs, integration with legacy systems, privacy, and cultural resistance. The article consolidates scattered EU evidence into an accessible benchmark and offers country-specific recommendations to boost SME AI adoption.

Practical implications: The article provides insights that can support entrepreneurs in successfully integrating AI technologies. It is also helpful for policymakers to promote AI adoption, thereby boosting the competitiveness of small and medium-sized enterprises.

Conclusion and summary: The gap in AI adoption is closely linked to the overall level of digitalisation, and limited digital infrastructure in the economy hampers the deployment of AI solutions in the SME sector. AI programmes for small and medium-sized enterprises need to be tailored to each country’s level of adoption.