In response to the rapid spread of AI systems in recent years, the European Union has sought to support member states, for example by creating a common regulatory and legal framework for AI, the Artificial Intelligence Act, and making AI a prioritized area in education (European Commission, 2020). Meanwhile, education institutions, confronted already with AI systems in various areas, find limited support in EU-related skills frameworks to address AI-related technological change. Key frameworks such as DigComp 2.2 (Vuorikari et al., 2022) and DigCompEdu (Punie & Redecker, 2017) outline expectations for Europeans’ digital competence, albeit with limited attention to AI. There is little policy consensus generally on what constitutes essential AI skills, echoing the situation some 20 years ago with regard to digital competence.

Amid these tensions, teachers in Europe run the risk of facing AI-related challenges alone. This could lead to, for example, neglect of technological change or uncritical adoption of AI technology at the expense of student privacy and educational quality (Bozkurt et al., 2024). While education researchers are grappling with what AI literacy includes, there is even less agreement on the AI literacy required specifically for educators and teacher training programmes. A broader working definition of AI literacy, used by UNESCO (2022) and many scholars (Laupichler et al., 2022), is ‘a set of competences that enable individuals to critically evaluate AI technologies, communicate and collaborate effectively with AI, and use AI as a tool online, at home and in the workplace’ (Long & Magerko, 2020, p. 2).

The Erasmus+ Teacher Academy AI2PI (Project number: 101196121 — AI2PI) directly responds to these challenges through a consortium that brings together expertise from seven European countries. Selected for funding by the European Education and Culture Executive Agency, the project employs design-based research to examine and support educators' professional and critical use of AI in teaching and learning. AI2PI specifically addresses how teachers across diverse European contexts can develop and implement AI literacy when it comes to, for example, developing information and data literacy, teaching in multilingual classrooms with mixed language learners, and the cultivation of responsible digital citizenship in innovative and inclusive learning environments.

AI2PI’s approach recognizes the challenges of integrating a wide range of AI-related skills and knowledge into curricula in European schools and teacher training and translate these into high-quality teaching and learning activities (cf. Giannakos et al., 2024). Through pedagogical labs across European contexts, AI2PI is developing and examining professional development opportunities for individual teachers while fostering communities of practice that address self-identified pedagogical challenges in effectively engaging with AI in teaching and learning.

The development of the Teacher Academy will be scientifically monitored and evaluated using a design-based research methodology. As a result, it is not only expected that a high-quality training module will be created, it will also be capable of gaining knowledge about and for the use of AI in educational contexts.

This panel discussion brings together consortium members to share their project contributions, research approaches, and early insights from the pedagogical labs, fostering collaborative dialogue about AI literacy development in Europe.

Bozkurt et al. (2024). The Manifesto for Teaching and Learning in a Time of Generative AI: A Critical Collective Stance to Better Navigate the Future. Open Praxis, 16(4), 487–513. https://doi.org/10.55982/openpraxis.16.4.777 European Commission. (2020). On Artificial Intelligence - A European approach to excellence and trust. COM(2020) 65 final, White paper. European Union. (2024). EU Artificial Intelligence Act. https://artificialintelligenceact.eu/article/4/ Giannakos et al. (2024). The promise and challenges of generative AI in education. Behaviour & Information Technology, 1–27. https://doi.org/10.1080/0144929X.2024.2394886 Laupichler et al. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence, 3, 100101. https://doi.org/10.1016/j.caeai.2022.100101 Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). Punie, Y (2017)., editor(s), Redecker, C., European Framework for the Digital Competence of Educators: DigCompEdu , EUR 28775 EN, Publications Office of the European Union, Luxembourg. UNESCO (2022). K-12 AI curricula, A mapping of government-endorsed AI curricula https://unesdoc.unesco.org/ark:/48223/pf0000380602 Vuorikari, R., Kluzer, S. and Punie, Y. (2022), DigComp 2.2: The Digital Competence Framework for Citizens - With new examples of knowledge, skills and attitudes, EUR 31006 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-76-48882-8, doi:10.2760/115376