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Quantification of relationships between artificial intelligence adoption in entrepreneurial enterprises and green innovation in European Union countries

B. Gavurová,Samuel Ribeiro-Navarrete,M. Rigelský,Andrea Mara Pimenta-Alonso

2026 · DOI: 10.1108/ijebr-06-2025-0836
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TLDR

It was found that Bulgaria, Poland, Hungary, Romania and Slovakia were among the countries with the lowest outcomes in the field of AI use in the business sector and eco-innovation, and the Nordic countries, such as Denmark, Finland and Sweden, were among the countries with the most positive outcomes.

Abstract

The goal of the study was to quantify the relationships between AI adaption in enterprises regarding their size and the green innovation outcomes represented by the eco-innovation index in the European Union countries. Achieving this goal was supported by seven research questions based on the outcomes of available research studies and the defined research gap.

The data for the year 2021 was examined for all the EU countries (n = 27). The seven areas of AI use were processed in enterprises classified by size into small, medium and large entities. The Eco-innovation Index was applied as part of eco-innovation. Regression and cluster analysis (CA) were used for analytical processes. The results of the regression models revealed the existence of significant relationships, but these relationships were closest, especially in large enterprises.

Medium-sized enterprises demonstrated a lower level of interconnection between AI and eco-innovation outputs; the least significant interconnections were found in small enterprises. The results of the CA pointed to the position of the EU countries. It was found that Bulgaria, Poland, Hungary, Romania and Slovakia were among the countries with the lowest outcomes in the field of AI use in the business sector and eco-innovation, and the Nordic countries, such as Denmark, Finland and Sweden, were among the countries with the most positive outcomes.

The study outcomes will be significant for policymakers dealing with the digital transformation processes, for regulators and creators of strategic development plans at the regional and national levels. They will also support the creation of international databases for the preparation of comparative analyses, the implementation of complementary qualitative research and experiments revealing the barriers to the adoption of digital transformation technologies and their impact on the eco-innovation outputs of enterprises.

The study outcomes will be significant for policymakers dealing with the digital transformation processes, for regulators and creators of strategic development plans at the regional and national levels.