The rapid development of generative artificial intelligence (GenAI), particularly large language model–based tools, is reshaping educational practices across Europe (Cukorova et al., 2024), and these tools are transforming teaching and learning practices (UNESCO, 2023). Unfortunately, Higher Education Institutions (HEIs) may be unprepared to equip teacher trainers and future teachers with the knowledge and skills needed to integrate AI into teaching and learning in an ethical and creative manner. Moreover, the inherent ethical and practical risks (Wieczorek et al., 2025) and national regulations set limits on how different institutions and schools can implement GenAI tools. Thus, teachers and teacher trainers face competing demands from various stakeholders and may struggle with conflicting pressures.

While recent research has begun to explore teachers’ AI readiness (Wang et al., 2023) and pre-service teachers’ attitudes towards GenAI (Gamlem et al., 2025), the role of teacher trainers remains under-theorised and under-examined, despite their central position in shaping both initial teacher education (ITE) and continuous professional development (CPD). Therefore, research-based approaches to integrating AI literacy into teacher training are needed. Unfortunately, despite rising scholarly interest (Liu et al., 2023; Cukorova et al., 2024), evidence-based pedagogical strategies for integrating ethical and creative applications of AI in teaching and learning remain limited.

This paper draws on data from EmpowerAId, an Erasmus+ Teacher Academies project involving ITE and CPD providers from eight European countries. The project aims to strengthen AI literacy and ethical awareness among pre- and in-service teachers by developing a European “Train the Trainer” programme and fostering cross-sectoral collaboration between teacher educators, policymakers, and education technology stakeholders. As part of the project’s needs analysis phase, qualitative interviews were conducted with teacher trainers to explore existing practices, institutional conditions, and perceived tensions related to GenAI integration in teacher education. By interviewing teacher trainers across different European countries, we aim to explore how AI is used in teacher training, what pedagogical value it offers, how policies or institutional structures affect training, and what differences exist between these countries.

Our research questions are:

1. How are teacher trainers across eight countries positioned in relation to GenAI?
2. What institutional conditions shape these positions?
3. What recurring cross-country tensions emerge?

The findings inform both institutional decision-making and policy development by foregrounding the voices and practices of teacher trainers as key agents in the AI transition in education.

Altogether, thirty-five teacher trainers were interviewed across the eight partner countries: Cyprus, Finland, Greece, Lithuania, Malta, Romania, Slovenia, and Spain. The semi-structured thematic interviews were conducted around five thematic areas: Practice & Pedagogy, Ethics & Risk, Institutional Support, Capability & Partnerships, and Motivation & Evidence. Each partner conducted their interviews in their native language using a shared interview protocol developed within the project. Using the native languages was intended to support richer, more detailed responses from interviewees. The interviews were conducted either in person or online and were recorded. Subsequently, the recordings were transcribed and summarised in English based on the thematic structure. A joint rubric was used to ensure uniformity and consistency in the summaries across countries. The data were analysed using deductive thematic analysis, guided by predefined thematic domains embedded in the interview protocol. At the same time, the analysis allowed for the identification of cross-cutting and emergent patterns both within and across the themes.

The interviews reveal that most teacher trainers actively use generative AI. Only a small number of respondents reported limited experience with GenAI, and just one expressed clear hesitancy, primarily due to a lack of personal preparedness. GenAI is used both for trainers’ own lesson planning and as a component of teacher education, with an added emphasis on promoting ethical and responsible use in the classroom. A likely reason for the widespread adoption—or the intention to adopt—GenAI is necessity, as one respondent noted: “Generative AI is essential and cannot be ignored.” This sentiment persists even among trainers who might otherwise prefer more traditional teaching approaches. Across countries, GenAI use was commonly described as a professional requirement rather than a pedagogical preference, reflecting the perceived inevitability of AI in contemporary education. Importantly, many teacher trainers reported integrating GenAI despite limited institutional guidance or material support, positioning them as proactive mediators rather than passive policy implementers. A recurring tension emerged between comparatively supportive higher education institutions and more cautious or restrictive governmental policy frameworks. While universities often encouraged experimentation, national regulations and ambiguous guidelines constrained pedagogical implementation. Key limiting factors included a lack of concrete institutional guidance, insufficient access to licensed tools, infrastructural disparities—particularly in rural settings—and, most critically, limited time for pedagogical experimentation and reflection. Conceptually, the study advances the idea of teacher trainers as AI mediators, who navigate structural constraints while shaping ethically grounded and pedagogically meaningful uses of GenAI. The findings highlight the need for policy approaches that recognise and support this mediating role through clearer guidance, sustained professional development opportunities, and realistic resourcing strategies.

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