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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteAI is already part of teachers’ work in many education systems, especially for preparing lessons and exploring or summarising information. But adoption is uneven, and survey reports of use do not show that AI has improved student learning. The emerging picture is a practical shift accompanied by a need for training, human oversight and clear safeguards.
How widely are teachers using AI?
In its 2025 publication of results from TALIS 2024, the OECD reported that around one in three teachers across participating education systems had used AI in their work. The rate differed substantially between systems, so the overall figure should not be read as a uniform global adoption rate. TALIS reports teachers’ own use and views; it is not a census of every teacher worldwide.
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The OECD’s definition of AI in this report is broader than generative AI or chatbots. It also includes technologies such as natural-language processing, speech recognition, learning analytics, data mining, image recognition and autonomous agents. The results therefore are not statistics about any one product or type of AI. OECD, Teaching for today’s world: Results from TALIS 2024.
What are teachers using AI to do?
Among teachers who said they used AI, the most commonly reported tasks were practical preparation and information work. On average across OECD education systems, 68% used AI to learn about or summarise a topic, while 64% used it to generate lesson plans or activities. Those percentages apply to AI-using teachers, not to all teachers.
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Reported use was lower for tasks involving student evidence and evaluation: 25% of AI-using teachers said they used AI to review data on student participation or performance, and 26% to assess or grade student work. These differences describe reported use, not rules that permit or prohibit a particular task.
| Task reported by AI-using teachers | Average across OECD education systems |
|---|---|
| Learn about or summarise a topic | 68% |
| Generate lesson plans or activities | 64% |
| Review student participation or performance data | 25% |
| Assess or grade student work | 26% |
Source for all figures: OECD TALIS 2024 results, published 2025. The percentages describe teachers who reported using AI, averaged across participating OECD education systems.
What does this change in a teacher’s work?
The task pattern points to AI being used more often as a preparation aid than as a decision-maker on student work. A teacher might use a tool to gather or summarise background information, draft activities, or generate a starting point for a lesson. The teacher still needs to check accuracy, suitability for the class, and alignment with learning goals; an automatically generated draft is not evidence that an activity is effective.
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For grading or interpreting student data, the stakes are different. An error or biased output can affect how a learner is understood or evaluated. The comparatively lower reported use for these tasks is not proof of safety, policy restrictions, or a deliberate global boundary. It does underline why teachers and schools need clear rules about when AI may assist and who remains accountable for the result.
What benefits and risks do teachers report?
AI may help with selected parts of preparation, but the same survey records concerns alongside use. Around seven in ten teachers believe AI could enable students to misrepresent other people’s work as their own. Teachers also report concerns about bias and privacy or security. These are reported concerns, not measured rates of cheating, discriminatory outcomes or data breaches.
Practical safeguards follow from those risks: teachers should verify generated material, avoid entering identifiable or sensitive student information into tools unless school policy and applicable protections allow it, and make assessment expectations explicit when AI use is relevant. Human review matters most when a tool’s output could shape a student’s evaluation, support or opportunity.
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The evidence does not establish that AI has improved learning outcomes at scale. TALIS captures reported use, opinions and professional learning, rather than testing whether AI causes better teaching or achievement. The OECD cautions: “Although AI is playing a larger role in people’s lives, the short- and long-term influence of AI on education remains uncertain.” OECD TALIS 2024 results.
What AI skills and training do teachers need?
Use alone does not guarantee informed or responsible use. Across participating systems, 29% of teachers reported a high professional-learning need for skills in using AI for teaching and learning; 38% said they had participated in professional learning on AI. These figures show both existing training activity and a substantial self-reported need. OECD, Developing teacher expertise: Results from TALIS 2024.
UNESCO’s 2024 AI Competency Framework for Teachers offers a way to organize that preparation. It sets out 15 competencies across five dimensions, with three progression levels—Acquire, Deepen and Create:
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- Human-centred mindset: keep human agency, teacher rights and learners’ needs central.
- Ethics of AI: consider responsibility, fairness, privacy and the consequences of using AI.
- AI foundations and applications: understand what AI systems can do and where their limits matter.
- AI pedagogy: make informed choices about whether and how AI supports teaching and learning.
- AI for professional learning: use AI thoughtfully to support teachers’ own continuing development.
The levels describe a progression from acquiring foundational competence to deepening practice and creating new approaches. The framework is guidance for policy, training programmes and assessment parameters—not evidence that teachers have already attained these competencies. UNESCO presents the relationship as a “teacher-AI-student dynamic,” emphasizing that AI enters a learning relationship rather than replacing the teacher. UNESCO, AI competency framework for teachers.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why school guidance matters
Teachers’ individual skills are only part of responsible adoption. Schools and education systems also need policies that make expectations clear: which tools and tasks are allowed, what information may be entered, how generated material should be checked, and when a human must make the final decision.
A UNESCO survey conducted from 4 to 19 May 2023 received responses from slightly more than 450 institutions. Fewer than 10% of responding schools and universities reported having formal guidance on AI. This was an early survey of UNESCO-associated networks, not a representative census or a current estimate of policy coverage. It illustrates the uncertainty institutions were reporting at that time, rather than establishing today’s global state. UNESCO’s 2023 survey report.
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What the evidence can—and cannot—tell us
TALIS offers a current cross-system view of teachers’ reported AI use, opinions and training in participating education systems. Differences between systems are real in the survey, but the figures alone do not explain why adoption varies. They also do not establish that AI improves learning, that all teachers use generative AI, or that a particular tool is suitable for a classroom.
The best-supported conclusion is narrower and more useful: teachers are incorporating AI into selected work tasks, use is uneven, and reported training needs remain. Whether that shift benefits students depends on choices about pedagogy, accuracy, privacy, fairness and human accountability—not simply on access to an AI tool. For broader education policy context, see UNESCO’s Artificial Intelligence and the Futures of Learning.
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