Abstract:

The rapid proliferation of artificial intelligence (AI) technologies in education is reshaping how teaching expertise is defined and sustained, making “AI readiness” a systemic rather than purely individual competence. This paper examines teacher trainers’ preparedness to support AI in Education (AIEd) implementation in Greece and Cyprus, arguing that trainers represent a critical leverage point within educational systems. They translate policy ambitions into pedagogical practice while mediating ethical and accountability concerns at the school level. Drawing on evidence from the European Teacher Academies projects EmpowerAId Academy and ACT-AI Academy, alongside a diagnostic instrument capturing Greek-Cypriot teachers’ perceptions, the study conceptualizes readiness as emerging from the interaction between the structural capacity of training ecosystems and practitioners’ demand for contextually relevant guidance.

Methodologically, the study combines inductive thematic analysis of focus groups (n≈50) with European teacher trainers participating in the EmpowerAId project and a Greek-language questionnaire structured across six dimensions: knowledge, attitudes, intentions toward competences, skills, ethical and social implications, and professional development needs. While questionnaire data are treated descriptively, its structure serves as an analytic proxy for teachers’ concerns when responding to institutional pressures to adopt AI tools. Additional consultations conducted within the ACT-AI Academy project involved 32 pre-service teachers, 39 in-service teachers 10 teachers' counselors and 5 policy makers, providing insights into emerging practices, training needs and policy expectations in Greece and Cyprus. Overall, the result argue that teacher education programmes and professional development trainings must move beyond ad hoc exposure and provide systematic support for developing AI literacy and AI-related pedagogical competence as core dimensions of contemporary professional practice, recognising its strong potential to support teaching, lesson planning, differentiation, and student engagement.

Findings identify four interdependent structural pillars supporting trainer readiness:
(1) institutional support through policy guidance, resources and incentives;
(2) communities of practice enabling knowledge sharing and collective sense-making;
(3) pedagogical contextualisation translating AI capabilities into subject-specific classroom applications; and
(4) continuous professional learning sustaining trainers’ technical, pedagogical and ethical expertise.

Weakness in any pillar undermines responsible AI integration by increasing uncertainty, slowing the diffusion of safe practices and reducing perceived classroom relevance. Evidence from the ACT-AI consultations further highlights policy uncertainty regarding AI use in schools, uneven levels of teacher AI literacy and strong demand for professional development on responsible generative AI use and critical evaluation of outputs.

For Greece and Cyprus, these findings suggest that teacher upskilling alone is insufficient without parallel investment in trainer development, governance frameworks and infrastructure. The study proposes a context-sensitive model, linking trainer preparedness to teacher needs and implementation risks -including data privacy, algorithmic bias and unequal access- offering implications for national CPD frameworks and evidence-informed AIEd adoption.

Keywords:

AI in Education, teacher trainer readiness, professional development, communities of practice, educational policy, Greece, Cyprus.