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Yes, AI can help with specific education tasks, but it has not been shown to improve learning automatically. A student may produce a stronger assignment with a chatbot and still learn little that they can recall or use without it. AI is more promising when it is designed for education and used with a clear teaching purpose that keeps students thinking and teachers involved.
Does AI improve learning, or just help students finish work?
The difference is between task performance—the quality or speed of work completed with AI—and learning: knowledge and skills students retain and can apply when the tool is unavailable. The OECD’s Digital Education Outlook 2026, published January 19, 2026, warns that better performance on an AI-assisted task does not by itself show that learning has taken place.
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The OECD describes evidence that general-purpose generative AI can improve the quality of student outputs, while gains may disappear or reverse in exams when AI access is removed. That is why a polished essay, completed worksheet, or fluent explanation generated with AI is not sufficient evidence of understanding. Assessment should also reveal what a student can explain, remember, or do independently.
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The Outlook says purpose-built educational tools used intentionally are more likely to support sustained learning than general-purpose AI used without a learning design. This is a qualified finding, not a guarantee that an education-focused label makes a tool effective. The OECD’s 2025 review of digital technologies in education likewise cautions that access to technology alone does not ensure educational gains.
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What the evidence says about teachers’ use of AI
AI is already part of many teachers’ work, though reported use varies across education systems. OECD publications reporting results from TALIS 2024 say around one in three lower secondary teachers used AI for their job in 2024 on average across participating systems; the OECD’s 2026 Outlook presents the average as 37%. These figures refer to lower secondary teachers in participating TALIS systems, not all teachers worldwide. The survey’s definition of AI is broad and includes technologies beyond generative AI and large language models.
Use differs sharply by system: the OECD’s TALIS 2024 results report use around 75% in Singapore and the United Arab Emirates, and below 20% in France and Japan. The OECD also cautions that some estimates carry a higher risk of non-response bias, so these comparisons should be read as survey findings rather than a complete census of teacher practice.
Among teachers who said they used AI, the OECD’s 2025 report on TALIS 2024 results found that 68% used it to learn about or summarize a topic and 64% to generate lesson plans, on average across participating systems. Those are self-reported uses by AI-using teachers, not evidence that students learned more as a result.
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Where teachers report value—and where evidence is limited
In the OECD’s 2026 summary of TALIS 2024, 57% of lower secondary teachers agreed that AI helps them write or improve lesson plans. Around 40% of teachers in the 2025 TALIS report said AI helps them support students individually. These figures capture teachers’ views; they do not measure the quality of the resulting lessons or establish a causal effect on achievement. Views about lesson-planning help vary substantially by country.
Reported use is less common for work that directly evaluates or monitors students. In the OECD’s TALIS 2024 results, 25% of teachers who use AI said they use it to review participation or performance data, and 26% to assess or grade student work. These are reported uses, not a recommendation to delegate consequential judgments to AI. Reviewing AI-generated material and making decisions about students still require professional judgment.
General-purpose AI and education-focused tools are not interchangeable
The key difference is not simply which product is newer or more capable. It is whether the tool and the activity help students practise and develop the intended knowledge or skill, and whether teachers can guide that process. The OECD, UNESCO, and U.S. Department of Education identify considerations that schools can use to assess both kinds of tool.
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| What to assess | Questions for a general-purpose chatbot | Questions for an education-focused tool |
|---|---|---|
| Learning design | Does it encourage explanation, practice, questions, and feedback, or mainly supply finished answers? | Does its instructional design prompt students to think and practise, rather than merely complete work? |
| Evidence of learning | Is there evidence of retained or transferable learning, beyond the quality of AI-assisted output? | Does evidence measure what learners can do after using the tool, including when they no longer have access to it? |
| Teacher agency | Can teachers shape how students use it, review outputs, and keep their judgment central? | Does it support teachers’ instructional decisions rather than displace them? |
| Privacy and age suitability | What student information is collected and how is it used? Is the tool appropriate for the students’ ages and setting? | Are data practices, age suitability, and safeguards clear for the school’s context? |
| Equity and policy fit | Can students access it, and does its use fit school rules, curriculum, assessment expectations, and local law? | Can different learners use it accessibly, and is it consistent with school policy and local requirements? |
An education-focused tool may offer a more purposeful learning experience, but the label alone does not establish its effectiveness, privacy protections, or accessibility. For either type, schools need to check the actual design, evidence, and terms of use.
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Academic integrity is a prominent teacher concern. In the OECD’s 2026 summary of TALIS 2024, 72% of lower secondary teachers believed AI could harm academic integrity by allowing students to pass off work as their own. This measures a perception, not the verified share of students who have done so. Schools can respond by making expectations for permitted AI assistance explicit and using assessments that give students a chance to demonstrate their own understanding.
The OECD’s 2025 TALIS report says around 40% of teachers agreed that AI may amplify bias, reinforce misconceptions, or compromise privacy and security. These are concerns reported by teachers, not measured incidence rates. They point to concrete issues to check: whether a response may mislead, whether outputs work fairly for different learners, and what happens to information students enter.
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UNESCO’s guidance on AI in education calls for a human-centred approach that protects inclusion and equity. It also notes that technological development has outpaced policy debate and regulatory frameworks. A school should therefore treat safeguards and oversight as part of implementation, not assume that a tool is suitable simply because it is available.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How schools can use AI without outsourcing learning
A practical approach is to start with the learning goal, then decide whether AI has a role. The OECD recommends selective use that enriches learning without replacing cognitive effort or weakening teacher–student relationships. In practice, a classroom plan can follow these checks:
- Name the skill students must learn. Decide what students should be able to explain, remember, or do independently—not only what they need to submit.
- Choose a role for AI that supports that skill. Use it, if appropriate, to prompt practice, questions, feedback, or exploration rather than to do the core thinking for the learner.
- Make the rules visible. Tell students what AI assistance is allowed for the activity and what work or explanation must be their own.
- Check understanding without AI assistance. Include a way for students to show what they can do independently, so task completion is not mistaken for learning.
- Review the tool and its effects. Check privacy, age suitability, accessibility, and policy fit, and look at whether students are developing the intended skill rather than only producing better outputs.
This is consistent with UNESCO’s emphasis on human-centred, inclusive use and with the OECD’s distinction between supported task performance and learning that lasts. It also keeps teachers responsible for interpreting student work and deciding what instruction should follow.
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What U.S. federal guidance says about responsible use
For U.S. schools and institutions using federal education funds, the Department of Education’s July 22, 2025 announcement describes a Dear Colleague Letter addressing responsible AI integration in the use of formula and discretionary grant funds. The announcement identifies instructional materials, high-impact tutoring, and college and career pathway exploration as areas covered, and highlights user privacy and engagement with affected stakeholders, especially parents.
The same announcement described an additional supplemental grantmaking priority as proposed and gave an August 2025 comment deadline. That announcement does not establish that the proposal became a final rule. The guidance is specific to its U.S. federal-funding context; schools elsewhere need to follow their own applicable policies and laws.
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