Unlocking the Potential of ESG and AI in Higher Education Finance: Insights from a Study across Five European Countries

Tina Vukasović

DOBA Business School, Maribor; International School for Social and Business Studies, Celje, and University of Primorska – Slovenia

Rok Strašek

University of Primorska – Slovenia

Liliya Terzieva; Esmee Messemaker

The Hague University of Applied Sciences

Elenita Velikova

University of National and World Economy

Justyna Tomala, Maria Urbaniec,

Jarosław Pawlik

Krakow University of Economics

Michael Murg, Anita Maček

JOANNEUM University of Applied Sciences, Graz, Austria

https://doi.org/10.53656/str2025-6-1-unl

Abstract. This paper presents the results of a qualitative study conducted in five European countries (Austria, Slovenia, Poland, Bulgaria, and the Netherlands) as part of the GenESG Erasmus+ project. The research explored how Environmental, Social, and Governance (ESG) content and Artificial Intelligence (AI) tools are integrated into higher education finance programmes. Data was collected through focus groups with academic staff and analyzed thematically. The study identified several systemic barriers to effective ESG and AI integration, including fragmented curricula, limited interdisciplinarity, lack of standardized competencies, and insufficient ethical frameworks for AI use. Nonetheless, good practices were observed, especially in Slovenia and the Netherlands, where project-based and AI-supported pedagogical models are emerging. The findings highlight the importance of practical skills development, ethical guidance, and motivation-enhancing teaching strategies. Recommendations include curriculum standardization, interdisciplinary cooperation, ethical AI integration, and targeted faculty training. The study contributes novel insights into aligning education with the goals of sustainable and digital transformation in Europe’s higher education systems.

Keywords: Sustainable Finance, ESG Education, Artificial Intelligence in Higher Education, Curriculum Innovation, Interdisciplinarity, Ethical AI Use JEL classification code: I23, Q56, O33

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