This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: As artificial intelligence (AI) rapidly enters classrooms and learning environments, how can societies ensure that its benefits reach learners and educators while avoiding new forms of inequality? A new international study led by Associate Professor Rwitajit Majumdar at Kumamoto University in Japan provides a roadmap for responsible AI integration in education.
Published in Computers and Education Open, the study examined emerging trends and challenges in AI-supported education through a Delphi study involving 70 experts from 18 countries, representing academia, research, industry, policymaking and teaching. The research was conducted by an international team of researchers from institutions in Japan, Germany, Ireland, Australia, the Netherlands and Finland, bringing together diverse perspectives on the future of education. The researchers identified five key priorities for AI in education.
The highest-rated was AI-related competencies for learners and educators, highlighting the need for people to understand not only how to use AI tools, but also how to critically evaluate their outputs, limitations and ethical implications. The second and third priorities were automated formative assessment and feedback and the evolving role of teachers working alongside AI agents. AI could provide students with rapid, personalized feedback, but the study emphasizes that teachers will remain central to learning.
Rather than simply adopting AI tools, educators may increasingly act as orchestrators of learning, combining AI capabilities with professional judgment. Two further priorities—explainability and trustworthiness and accessibility and equal access—highlight an important challenge: technological progress alone does not guarantee better education. AI systems must be transparent, reliable and fair, while students from different socioeconomic, geographic and linguistic backgrounds must have equitable opportunities to benefit from them.
Importantly, the researchers argue that AI adoption should not be treated as a purely technological issue. Education is an interconnected ecosystem involving learners, educators, institutions, data, infrastructure, policies and society. Sustainable AI integration therefore requires coordinated action across research, educational practice and policymaking.
The study concludes that the future of AI in education should be built around human capability, pedagogical innovation, ethical governance and equity, positioning AI not as a replacement for educators, but as a tool to support teachers, empower learners and strengthen educational ecosystems. Rwitajit Majumdar et al., Fostering collaborative futures: Multidisciplinary approaches to AI integration in educational ecosystems, Computers and Education Open (2026). DOI: 10.1016/j.caeo.2026.100405 BSc Life Sciences & Ecology.
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