Over the past year, the ICEP Europe research team have been working on the Erasmus+ funded AIRED project, along with partners Haikara, ICN Business School (France), and AEG (Spain), with the central aim of investigating the pedagogical, ethical, and inclusive use of artificial intelligence (AI) across the education sector in Europe. Through this work, it has become evident that the rapid development of AI presents several unique challenges to training providers in creating teacher training programmes that are pedagogically sound, ethical, and future-proof. These include:
#1 Training remains short-sighted and tool-specific
Training programmes tend to focus on tool-specific instruction primarily. While there is value in a practical, hands-on approach to learning (Szproch et al., 2025), training quickly becomes outdated when it exclusively focuses on tool implementation. Unlike past technological advances that have reshaped education, such as the internet, AI is unique in its extremely rapid development (Osorio Venegas et al., 2025). As such, traditional one-off training structures are insufficient in preparing educators to navigate AI-assisted classrooms. Educators can easily become stuck in loops where they need to constantly revisit training to keep up with AI’s rapid pace, taking limited time away from professional duties.
#2 Policy advice often fails to catch up to training needs
While policy advice on AI implementation has gradually emerged across Europe over the last few years (DEY, 2026), it often struggles to respond to on-the-ground challenges educators face. Policy is also slow to implement (Marcus-Quinn & McCoy, 2025), meaning that several new challenges often arise by the time policy guidance is published. Additionally, the lack of practical, pedagogy-focused policy makes it difficult for providers to develop policy-compliant training for educators. Often, this may result in training that is vague and detached from contextually specific issues educators face.
#3 AI challenges what it means to be an educator
Perhaps the biggest challenge that AI presents for training providers is that, for many, it brings into question what the role of educators has now become, and even more so, questions the purpose of education as a whole (Levasseur, 2020). With the refinement of easily accessible tools such as chatbots and AI tutors, students can turn to technology for tasks that have been traditionally delegated to teachers. It is still unclear how AI will reshape the role of educators in the long-term, and yet, this uncertainty often lingers at the forefront of AI training and may lead to several educators remaining ambivalent or reluctant to engage with AI.
Through consultations of the academic literature, surveys and one-on-one interviews with various education stakeholders, the following recommendations have been identified to mitigate these challenges:
#1 Shifting the focus from tool mastery to AI literacy
It is not enough for training to be pedagogically focused when curriculums emphasise short-term knowledge acquisition goals, such as mastery over specific AI tools. Instead, training should centre AI literacy and the ways it can support educators. AI literacy refers to the set of skills a person has that allow them to gain a full understanding of AI systems, its applications, and broader implications. In training, this concept should be operationalised based on evidence-based, international standards, such as the AI Lit framework (OECD, 2025). By shifting focus away from tools and toward AI literacy, educators can understand AI at a deeper level, facilitating independent learning.
#2 Promoting short, ongoing, and peer-focused training
Providers should move away from the traditional CPD model comprising long, information-heavy, one-off training sessions. Instead, training should shift to shorter, ongoing formats that can be easily embedded into educators’ busy schedules. It is crucial to continually centre the experience of educators by emphasising peer learning activities and fostering learning environments that facilitate network building. By following this structure, educators can regularly engage with new tool developments, pedagogical applications, and input from colleagues on best practices.
#3 Redefining the role of the educator
AI training should consider the impact that AI has on educators’ identity and meaningfully engage with how they can reframe their role and relationship with AI. One way of doing this is decentering utility and functionality as the core purpose of education. Instead, educators and students alike should see AI as a tool which can only assist them in learning for the broader purposes of personal development, critical thinking, and achievement (Levasseur, 2020). Training should assist educators in developing competencies that enhance their capacity as leaders, including AI literacy, adaptability and lifelong learning, collaboration, and human-centred practices (Ghamrawi et al., 2024).
With AI evolving at an increasing pace and its role becoming more embedded in modern education, it is crucial that all relevant stakeholders, from policymakers, researchers, educators, to training providers, reframe traditional approaches to better respond to the unique challenges AI poses.
To find out more about this research, contact our Senior Research Officer at a.szproch@icepe.eu
You can also learn more about the AIRED project and its outputs at https://www.air-education.eu/
References
Department of Education & Youth. (2026). Digital Strategy for Schools to 2027. https://www.gov.ie/en/department-of-education/publications/digital-strategy-for-schools-to-2027/#guidance-on-artificial-intelligence-in-schools
Levasseur, A. (2026). What Is Education For in the Age of Artificial Intelligence? Greater Good Magazine. Retrieved from https://greatergood.berkeley.edu/article/item/what_is_education_for_in_the_age_of_artificial_intelligence?utm_source=Greater+Good+Science+Center&utm_campaign=f8960b1488-ED_NEWSLETTER_May_2026&utm_medium=email&utm_term=0_5ae73e326e-f8960b1488-51357615
Ghamrawi, N., Shal, T., & Ghamrawi, N. A. R. (2024). Cultivating teacher leadership: evidence form a transformative professional development model. School Leadership & Management, 44(4), 413–441. https://doi.org/10.1080/13632434.2024.2328056
Marcus-Quinn, A., & McCoy, S. (2025). Future Proofing Schools: Bringing School Policies into the AI Era. The Economic and Social Review, 56(3, Autumn), 363–382. Retrieved from https://esr.ie/index.php/esr/article/view/3089
OECD (2025). Empowering learners for the age of AI: An AI literacy framework for primary and secondary education (Review draft). OECD. Paris. https://ailiteracyframework.org
Osorio Vanegas, H. D., Segovia Cifuentes, Y. D. M., & Sobrino Morrás, A. (2025). Educational technology in teacher training: A systematic review of competencies, skills, models, and methods. Education Sciences, 15(8), 1036. https://doi.org/10.3390/educsci15081036
Szproch, A., Kummer, R., & O’Brien, M. (2025). WP4: Ethical and Inclusive use of AI. Retrieved from https://www.air-education.eu/2025/09/15/wp4-ethical-and-inclusive-use-of-ai-d4-3-a-framework-for-inclusive-design/