OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education

The evolution of pre-scripted, AI-powered pedagogical agents towards sophisticated generative AI tutors represents a profound shift in educational technology. This chapter has traced this transformation through the lens of the Socratic Playground (SPL), demonstrating that the move from scripted tutor avatars to generative Socratic companions is not merely a technological upgrade, but a reimagining of educational possibilities. GenAI can function as a dynamic conversational partner capable of adaptive guidance and deep dialogue, provided that pedagogy remains the core driver. The “pedagogy-first” principle and integration in the system design is both an ethical imperative and the practical key to success. In essence, AI tutors must be as much products of educational craftsmanship as of computational prowess. Digital innovations in education hinge on the synergy of advanced AI with sound teaching approaches (Hu, Xu and Graesser, 2025).

However, the rapid advancement of these systems necessitates a shift from proof-of-concept to rigorous, continuous evaluation. As GenAI agents become commonplace, the research community must move beyond novelty to conduct large-scale randomised trials that examine holistic outcomes. It is crucial to probe not only subject knowledge gains but also metacognitive shifts: do students develop better learning strategies, greater self-regulation, and sustained interest, or does the motivation fade once the novelty of the AI wears off? Furthermore, as models inevitably evolve (e.g. from GPT-4 to future iterations), the educational quality cannot be assumed to remain static. A robust process is needed to re-validate agents with each major upgrade to ensure they remain aligned with learning goals rather than becoming distractions.

This ongoing validation must prioritise inclusivity and ethics alongside effectiveness. Ensuring factual accuracy, fairness, and privacy are not optional add-ons but fundamental to the integrity of GenAI-powered tutors. To achieve this, various safeguard mechanisms in system implementation could be adopted – ranging from bias audits and human-in-the-loop frameworks to alignment with international guidelines like those from the OECD, UNESCO, and the EU. By implementing such safeguards, the international community can strive to make GenAI pedagogical agents not only effective but also trustworthy and inclusive. As features become more multimodal and autonomous, these efforts must specifically target accessibility, ensuring accommodations for diverse learning needs. When implemented carefully, these measures can foster trust. Students may welcome the personalised support and teachers appreciate the augmented capabilities provided, dispelling fears of AI as an unwanted intruder. Ultimately, navigating these challenges requires deep interdisciplinary collaboration among AI researchers, learning scientists, educators, policymakers, ethicists and other stakeholders, as no single group holds all the expertise needed to perfect these systems.

In Art Graesser’s early work with AutoTutor (Graesser et al., 2005), the dream was to simulate skilled tutoring dialogue. Today, GenAI and systems like the Socratic Playground bring us much closer to fulfilling those aspirations. Yet, this technology should not be pursued for novelty’s sake, but to amplify and democratise the best of teaching – enabling rich, adaptive mentorship for every student, regardless of geography. Realising this vision requires a “pedagogy-first” ethos and the development and use of AI tools that augment rather than diminish human intellect. By combining the empathy of teachers, the rigour of learning and education scientists, and the computational consistency of AI, the education community can author a future where GenAI agents are harnessed responsibly to close the learning divide and become a success story for learners everywhere.