Pre-Service Teachers Not Ready for AI: Study Reveals Gaps in Training and Confidence

A cross-national study from Portugal and Spain reveals that pre-service teachers lack sufficient training and confidence to integrate AI into their future classrooms. Despite policy frameworks, AI education in teacher training remains superficial and largely ineffective.

A recent cross-national study conducted by researchers from the University of Aveiro in Portugal and the University of Seville in Spain reveals a concerning lack of readiness among pre-service primary teachers to integrate artificial intelligence (AI) into their future classrooms. The investigation brought together the expertise of Margarida Lucas, Pedro Bem-haja, Yidi Zhang, Carmen Llorente-Cejudo, and Antonio Palacios-Rodríguez, representing the Laboratory of Digital Contents and CIDTFF (Research Centre on Didactics and Technology in the Education of Trainers) in Portugal and the Department of Didactics and Educational Organization in Spain. Their research shines a spotlight on the educational systems of both countries, pointing to critical shortcomings in the preparation of future teachers for AI-enhanced learning environments.

Exploring Readiness Across Borders

The study surveyed 203 pre-service teachers, 116 from Portugal and 87 from Spain, on their trust in AI, knowledge of AI, digital competence, and the presence of AI-focused training in their teacher education programmes. These four dimensions were chosen to provide a holistic view of what it means to be “ready” to work with AI in education. While both countries have formally adopted European digital competence frameworks such as DigComp and DigCompEdu, the findings suggest that these policy advances have yet to translate meaningfully into ITE curricula. Using structured questionnaires, the research team collected both qualitative and quantitative data that measured how well participants felt prepared to engage with AI in their professional future.

The results demonstrated that, in general, both Portuguese and Spanish teacher trainees share similar levels of digital competence and trust in AI, with no statistically significant differences between the two groups. Participants in both samples averaged around the B1 level of digital competence, indicating intermediate skills. In terms of AI knowledge, most respondents rated themselves between “limited knowledge” and “knowing what AI is,” but not beyond. These modest levels of AI understanding suggest a lack of structured exposure to the topic during training.

Training That Misses the Mark

One area where the Spanish sample outperformed their Portuguese counterparts was in their exposure to AI content within their education programmes. Spanish participants showed slightly higher agreement with statements about the benefits and ethical implications of AI being discussed in their courses. However, the difference was marginal, mostly shifting from disagreement to neutrality rather than demonstrating strong consensus or confidence. In Portugal, responses more frequently indicated disagreement, suggesting a more severe lack of curriculum coverage on AI.

Still, this modest edge for Spain is hardly a cause for celebration. In both countries, the majority of pre-service teachers did not feel they were being prepared to integrate AI into their teaching. These findings underscore that, while AI may be a topic of general awareness, its pedagogical relevance is not being addressed comprehensively in initial teacher education.

Disconnect Between Training and Competence

One of the most striking revelations of the study is the disconnect between ITE training and actual preparedness indicators like knowledge and digital competence. Network analyses conducted by the researchers revealed that the inclusion of AI topics in training (such as ethical discussions or benefit analysis) had little to no measurable impact on students’ overall readiness. In fact, variables related to AI-specific training were not significantly correlated with either AI knowledge or digital competence. This means that even when AI is being mentioned in classrooms, it is not making a tangible difference in preparing students to use or trust AI tools in their teaching.

Moreover, while digital competence and AI knowledge were found to be interdependent, particularly in the Portuguese sample, this relationship operated largely outside the influence of the training programmes themselves. In many cases, students appeared to be self-teaching or learning through informal means, rather than benefiting from structured academic instruction.

Global Challenges, Local Reflections

These findings are not unique to Portugal or Spain. Across various international contexts, including Estonia, Nigeria, and Germany, studies have similarly shown that teachers often acquire digital and AI-related skills through incidental learning or personal initiative. This results in knowledge that is uneven, sometimes superficial, and rarely pedagogically grounded. The authors highlight a pressing need to reform teacher education, not just in their studied countries, but globally, to better reflect the realities of today’s AI-driven educational systems.

They point out that although frameworks and guidelines are increasingly being proposed, such as UNESCO’s AI Competency Framework for Teachers, very few institutions have implemented comprehensive strategies for developing AI literacy among educators. Without this foundation, ethical discussions around AI remain abstract and unanchored, unable to foster true engagement or informed use of these technologies.

A Call for Urgent Curriculum Reform

The study concludes with a clear call to action. Educational policymakers, teacher training institutions, and curriculum developers must take bold steps to embed AI literacy meaningfully into teacher education. This includes not only technical know-how but also critical reflection, ethical understanding, and practical application in real teaching contexts. Future teachers need to be equipped not just to understand AI but to confidently and creatively use it to enhance learning.

Until these changes are made, the integration of AI into classrooms will remain hindered by a workforce that is curious but unprepared. As AI continues to evolve, the education sector must ensure its educators are not left behind. The classroom of the future, the study warns, may arrive sooner than the systems preparing teachers for it.