Schools are adopting AI, but readiness is lagging. In OECD reporting on TALIS 2024, 37% of lower-secondary teachers in participating education systems said they had used AI for work in 2024, while three in four teachers said they lacked the knowledge or skills to teach using it. The figures show teacher use and a capacity gap—not how many schools have formal AI programs, or whether AI is improving learning.
How widely are teachers using AI?
The OECD’s 2026 Digital Education Outlook, drawing on TALIS 2024, reports that 37% of lower-secondary teachers in participating education systems used AI for their job in 2024. The OECD’s TALIS reporting also describes the rate as around one in three. These are teacher-reported figures, not a global census of school deployments, and they should not be read as the share of schools with an AI policy or system.
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Use varied considerably across participating systems: reported use was much higher in Singapore and the United Arab Emirates, and below one in five teachers in France and Japan. The survey therefore points to uneven adoption rather than a single pace of change across education.
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What teachers use it for
Among teachers who used AI, 68% said they used it to learn about or summarize a topic, and 64% used it to generate lesson plans or activities. Use also extended to student-related work: 25% of teachers reported using AI to review student participation or performance data, and 26% to assess or grade student work.
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In the OECD’s 2026 summary of TALIS 2024, 57% of lower-secondary teachers agreed that AI can help write or improve lesson plans. That is a view about potential usefulness, not evidence that AI-generated plans improve student learning.
Are teachers prepared to teach with AI?
Use is advancing faster than reported preparedness. On average, three in four teachers said they did not have the knowledge or skills needed to teach using AI. Among teachers who did not use AI, about one-third said they felt overwhelmed by the shift to new technologies, including AI.
This gap matters because knowing how to operate a tool is not the same as knowing when it serves a learning goal, how to check its output, or how to help students use it responsibly. Professional development needs to address instructional design and judgment as well as basic familiarity with AI.
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UNESCO’s AI competency frameworks for students and teachers emphasize human agency, critical thinking, and ethics. In the United States, the Department of Education’s July 2025 announcement identified AI literacy and educator professional development among areas covered by federal guidance. These are signals of policy attention, not proof that all teachers have received training or that a nationwide school requirement is in force.
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Does AI help students learn?
It can support learning when it is used with a clear teaching purpose, but a stronger-looking answer or faster completed assignment is not, by itself, evidence of learning. In its Digital Education Outlook 2026, the OECD distinguishes task performance from learning gains. It warns that when generative AI is used without pedagogical guidance, outsourcing tasks can improve performance without producing real learning gains. Purposeful, teacher-guided use may support learning; the result depends on how the activity is designed and evaluated.
A practical distinction is whether AI prompts students to do more of the thinking or does the thinking for them:
| Use design | What the student does | What the teacher should check |
|---|---|---|
| Guided tutoring or feedback | Works through a problem, explains reasoning, or revises an attempt in response to feedback. | Whether the feedback is accurate and whether the student can explain or transfer the learning independently. |
| Finished-answer generation | Submits AI-produced work without demonstrating their own understanding. | Whether the task measures student learning at all, rather than the quality of an AI-assisted output. |
This is a design distinction, not a claim that one category of tool always works. Schools need to evaluate learning, including whether students can explain ideas and apply them beyond the AI-supported task.
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What concerns should school policies address?
Teachers’ concerns include academic integrity, bias, misconceptions, and privacy or security. Around seven in ten teachers in TALIS 2024 believed AI could enable students to misrepresent others’ work as their own; the OECD’s 2026 summary reports 72% of lower-secondary teachers expressing concern that AI can harm academic integrity by letting students pass off work as their own. These figures describe teacher views, not the measured frequency of misconduct.
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A useful school policy makes expectations understandable to students, families, and staff. It should specify when AI assistance is allowed, what students must disclose, and how teachers will assess independent understanding. It should also address the information students and staff may enter into tools, how outputs are checked, and what safeguards apply for age-appropriate use.
- Privacy and security: Define what data may be entered and how student information is protected.
- Accuracy and bias: Require review of outputs for errors, misleading explanations, and biased content.
- Transparency: Set clear expectations for disclosing AI assistance in student work and for explaining AI’s role in school decisions.
- Age-appropriateness: Check that tools and activities are suitable for the students who will use them.
- Educational purpose: Tie each use to a learning aim rather than adopting a tool simply because it is available.
The OECD recommends privacy, safety, bias testing, transparency, age-appropriateness, and alignment with educational aims as parts of trustworthy use. UNESCO’s emphasis on human agency, critical thinking, and ethics offers a complementary test: AI should not displace students’ responsibility for their thinking or the teacher’s professional judgment.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can a school tell whether it is keeping up?
Readiness is more than access to AI. A school can use this checklist to assess whether its practice is developing alongside adoption:
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- Teacher preparation: Do educators have training and time to adapt lessons, evaluate outputs, and decide when not to use AI?
- Student expectations: Are rules for permitted help, disclosure, and independent work explicit?
- Safeguards: Are privacy, security, bias, transparency, and age-appropriateness addressed before use?
- Equitable access: Can students participate regardless of device access, connectivity, language, or disability, with alternatives where needed?
- Evidence: Does evaluation check learning and transfer, not just speed, task completion, or polished-looking work?
- Governance: Have teachers, families, and other stakeholders been engaged, and are responsibilities clear?
The OECD identifies professional learning, equitable digital infrastructure, and trustworthy-use safeguards as parts of effective implementation. Without access to devices and connectivity, an AI-based activity can widen existing barriers; without teacher time and training, access alone does not create good instructional practice.
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What do current policies say—and what do they not prove?
Policy activity is increasing, but policy development is not the same as implementation. An OECD and Fondazione Agnelli inventory published in 2025 recorded AI guidance or policy activity in 26 U.S. states and Puerto Rico as of its July 2025 inventory. That count does not establish that every school in those jurisdictions has adopted a policy, or that policies are being applied effectively.
The U.S. Department of Education’s July 22, 2025 announcement described federal guidance areas including AI-based instructional materials, AI-enhanced tutoring, college and career navigation, privacy, stakeholder engagement, AI literacy, and educator professional development. The announcement also proposed an additional supplemental priority; it should not be treated as evidence that the proposed priority became a finalized nationwide mandate.
More broadly, TALIS covers participating education systems and teacher reports. It is useful for comparing reported teacher use and views, but it does not provide a school-by-school global adoption rate. Nor do these adoption and attitude figures show that AI use itself raises achievement.
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