Regional Lessons on Teaching in the Age of AI

A teacher raised her hand during the final panel discussion of our AI in Education Conference and asked a question that stopped the room, “If AI [artificial intelligence] can now write a convincing essay, grade it, and give feedback on it, what exactly is my role?”

Nobody had a clean answer. That moment, more than any keynote or workshop slide, captured why we needed this event in the first place.

In May 2026, Haileybury Astana hosted its regional conference dedicated to AI in education in Kazakhstan and Central Asia. Building on the dialogue established in our region, this was not a technology showcase. It was a day-long exploration of questions that educators around the world are facing, and that schools in our region are increasingly confronting without the benefit of an established local dialogue.

Why Central Asia, Why Now

Much of the global conversation about AI in education has been centred in North America, Western Europe, and parts of East Asia. Research, policy debates, and professional development resources often reflect those contexts. For educators in Kazakhstan, this creates a particular challenge: the technology arrives faster than the guidance surrounding it.

Teachers are encountering AI-generated work in their classrooms, school leaders are revisiting academic integrity policies, and students are experimenting with tools that did not exist a few years ago. Schools are being asked to make decisions in real time.

When my colleague Liam Stewart, Head of junior school, and I began planning the conference, our goal was simple: create a space where educators could move beyond headlines and explore how AI can be used thoughtfully, ethically, and effectively in schools. We wanted the discussion to be practical, honest, and grounded in the realities of teaching in Kazakhstan.

What we had not fully anticipated was how much innovative work was already taking place. The conference brought together teachers, school leaders, university lecturers, consultants, and specialists from across the country. Participants represented international schools, state schools, higher education institutions, and educational organisations. The range of experiences in the room quickly became one of the event’s greatest strengths.

What We Explored: Moving from Theory to Tools

The opening keynote, delivered by Natalya Zyryanova, set the tone for the day. Titled BrAIn Damage: How to Remain a Thinking Individual?, it challenged participants to consider what it means to preserve critical thinking, creativity, and independent judgement in an age of increasingly capable digital tools.

The workshops that followed quickly shifted from asking whether AI should be used in education to sharing exact examples of how educators are already deploying it. Rather than talking about “AI capability” in the abstract, sessions focused on specific platforms that teachers can immediately bring into their classrooms:

• Streamlining Lesson Design: Katrine Altiok demonstrated how teachers are using MagicSchool AI to co-create high-impact learning experiences, build differentiated resources, and drastically cut down on administrative planning time.
• Individualised Research: Simon Armstrong highlighted the power of Google’s NotebookLM, showing how students can upload specific source materials to create a closed, reliable AI environment for personalized research and independent learning.
• Custom AI Tutors: Aigerim Batyrbayeva led a hands-on session on building custom AI assistants, showing teachers how to program specific personas or rubrics into custom chatbots to act as tailored co-tutors for students.

Redefining the Post-AI Curriculum

One of the core highlights of the day came from Dominic Briffa’s workshop, which tackled the overarching question, “What does a post-AI curriculum look like?” Dominic challenged the traditional structures of assessment, arguing that if AI can flawlessly execute standard knowledge-retrieval tasks, our curricula must pivot. The insight that resonated most was that we must transition from evaluating final products to evaluating the learning process itself.

In a post-AI landscape, a student's final essay or code script is no longer definitive proof of understanding. Instead, Dom emphasized that educators need to design “AI-resistant” or “AI-integrated” assessments—such as live viva-voce defenses, real-time collaborative problem-solving, and reflective learning journals where students actively document how they prompted, critiqued, and iterated alongside an AI assistant.

What Surprised Me

While the invited speakers brought valuable expertise, some of the most memorable moments came from conversations between participants. One educator from a state school described using AI to create differentiated learning materials for students with varying language abilities. There was no formal strategy behind it. She had identified a challenge in her classroom and found a tool that helped address it. Similar stories emerged throughout the day, demonstrating how educators are adapting to change through practical problem-solving rather than waiting for perfect guidance.

What struck me most was the willingness of participants to engage with uncertainty. Few people claimed to have definitive answers about what AI will mean for education in five years' time. Yet there was a clear commitment to exploring the opportunities and challenges openly and thoughtfully.

Contributing to a Broader Conversation

One of the most encouraging aspects of the conference was seeing educators from different sectors engaging with the same questions. International schools, state schools, universities, and independent consultants all brought different perspectives, but many of the challenges they described were remarkably similar.

Too often, discussions about AI in education focus on developments elsewhere. What became clear throughout the day was that educators in Kazakhstan are not simply adopting ideas from abroad. They are testing approaches, adapting them to their own contexts, and generating valuable insights of their own.

The conference was never intended to provide definitive answers. Artificial intelligence is evolving too quickly for that. Its purpose was to create a space for honest discussion, practical sharing, and critical reflection. By the end of the day, nobody had solved the challenges AI presents to education. What had changed was that educators from different schools, sectors, and backgrounds had begun discussing those challenges together. For a region where these conversations are still emerging, that felt like a worthwhile place to start.