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AI can support tutoring, feedback, lesson planning, research and school administration—but using it does not automatically mean students have learned. The strongest educational uses give learners purposeful practice, keep teachers in control and protect privacy, inclusion and student agency. The difference is whether a tool advances a clear learning goal or simply produces work on a student’s behalf.
What does AI in education include?
AI in education is broader than chatbots and generative AI (GenAI). It also includes established systems that can help personalize practice, support tutoring or organize school workflows. GenAI adds tools that can produce or revise text and other content in response to prompts. These approaches have different capabilities and risks, so a school should assess a particular tool for its intended use rather than treating “AI” as one uniform product.
Education has a reciprocal role: it can use AI to support teaching and learning, and it must help learners understand AI’s capabilities and limitations so they can live and work with it. UNESCO’s policy guidance frames that work around opportunities and risks, inclusion and equity, and preparation for an AI-enabled society. UNESCO, AI and education: guidance for policy-makers
How can AI help students learn?
AI is most promising when it is part of a deliberate learning design. A student can use a dialogue-based tutor to get a hint, answer a follow-up question or try a new strategy. A group can use a system to examine competing claims and strengthen an argument. In both cases, the goal is to make students think, explain and revise—not just obtain a finished response.
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The OECD’s Digital Education Outlook 2026 describes evidence that inexperienced tutors using educational GenAI tools improved tutoring quality and student outcomes. That finding concerns educational tools designed for tutoring; it should not be assumed to apply to every general-purpose chatbot. The OECD also reports stronger evidence for intentional pedagogical approaches, including collaborative learning and educational tutoring systems, than for unguided outsourcing of cognitive work. OECD, OECD Digital Education Outlook 2026
Match the tool to the learning task
| Educational role | Potential use | What to keep in view |
|---|---|---|
| Tutor or dialogue partner | Offer hints, ask questions and support practice or revision. | Check that it prompts student reasoning and that a teacher can review its guidance. |
| Collaborative learning aid | Help a group explore a question, compare ideas or develop an argument. | Make the learning objective and each student’s contribution visible. |
| Research assistant | Help organize an inquiry or guide a student through research tasks. | Students still need to assess the quality and relevance of the information and explain their conclusions. |
| Teacher assistant | Support feedback, resource development or professional learning. | Teachers should review and adapt outputs before using them with students. |
How are teachers using AI in education?
Teachers use AI for planning and other work, while also expressing concerns about how students may use it. In the OECD’s 2026 summary, which attributes the teacher-use indicator to TALIS 2024, 37% of lower-secondary teachers used AI for their job in 2024. In the same OECD summary, 57% of lower-secondary teachers agreed that AI helps write or improve lesson plans, and 72% believed AI can harm academic integrity by letting students pass off work as their own. These figures describe lower-secondary teachers, not all educators or students. OECD, OECD Digital Education Outlook 2026
Beyond lesson planning, AI may help teachers develop resources, provide feedback, review curriculum alignment or generate assessment items. Schools may also explore resource classification and administrative workflows. These are possible uses, not proof that an automated output is accurate, unbiased or suitable for a particular class. Teacher review remains important, especially when outputs affect instruction, assessment or student support.
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It can support learning, but a stronger-looking assignment is not enough to show that a student learned more. The OECD’s 2026 synthesis finds that general-purpose GenAI can improve work products without necessarily producing learning gains. In some studies, output advantages disappear or reverse when students take exams without access to the tools. The OECD sums up the distinction this way: “Successfully performing a task with GenAI does not automatically lead to learning.”
To judge whether an approach is helping, look for evidence that students can explain ideas, apply them independently and retain or transfer what they have practiced—not only submit polished work. Assessment can include process evidence, discussion, oral explanation and tasks completed without AI access. These checks help teachers see what learners understand while preserving room for appropriate AI-supported work.
What are the risks of AI in schools?
Shallow learning and cognitive offloading
If students delegate the thinking a task is meant to develop, they may finish faster without gaining the underlying knowledge or skill. Build in moments when students generate their own ideas, explain a tool-assisted answer or demonstrate a skill independently. This is particularly important for foundational skills that students need both with and without GenAI.
Academic integrity and unclear expectations
Students and teachers need to know what assistance is permitted, when AI use should be disclosed, and what evidence of the student’s own process is expected. Set expectations for attribution and for demonstrating learning. The sources cited here do not establish the accuracy of AI-detection tools, so an automated detector should not be the sole basis for an academic-integrity decision.
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Privacy, age suitability and safety
Before students use a platform, schools should examine what personal information it collects, how that information is used, and whether the product is appropriate for the learners’ ages. UNESCO’s GenAI guidance emphasizes privacy protections, age-appropriate interaction, human-centred policy and ethical validation and pedagogical design. It also notes that rapid GenAI releases have outpaced many national frameworks, leaving institutions with a need to build capacity to evaluate tools. UNESCO, Guidance for generative AI in education and research
Bias, transparency and poor fit
A system may not suit a school’s curriculum, student population or educational purpose. OECD guidance calls for attention to privacy, safety, bias testing, age appropriateness, transparency and alignment with clear educational objectives. A tool that cannot be evaluated against those expectations is difficult to use responsibly, even if its output looks fluent.
Unequal access
Students do not benefit equally when access depends on reliable devices, connectivity, accessible resources, language and cultural coverage, or teacher support. UNESCO places inclusion and equity at the centre of its approach and warns of widening technology divides. OECD likewise emphasizes equitable infrastructure and alternatives where divides persist. UNESCO, Artificial intelligence in education
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can schools use AI responsibly?
- Start with a learning or operational goal. State what the tool is meant to improve—such as practice, feedback or lesson preparation—and decide how the school will tell whether it is working.
- Choose the educational role deliberately. Decide whether AI will act as a tutor, collaborative partner or assistant. Set up tasks so students remain active participants rather than handing over the core thinking.
- Involve teachers in selection and design. Give educators a meaningful role in choosing, adapting and reviewing tools. OECD guidance highlights teacher expertise and end-user co-design; UNESCO’s teacher competency framework covers a human-centred mindset, AI ethics, AI foundations and applications, AI pedagogy, and AI for professional learning, with progression through Acquire, Deepen and Create levels. UNESCO, AI competency framework for teachers
- Review student protections and tool quality. Examine privacy, age suitability, safety, bias testing, transparency and fit with the curriculum before classroom use. Establish who can access the tool and what student information may be entered.
- Plan for access and support. Consider connectivity, devices, accessibility and language coverage, and provide alternatives when students cannot use the same tools. Include sustained professional learning so staff can use and evaluate AI with confidence.
- Check learning, not just output. Use student explanations, process work and independent demonstrations to assess whether the approach supports understanding. Adjust or stop the use if the evidence does not match the goal.
How should schools compare AI tools?
Compare products and approaches against the same educational criteria instead of choosing solely by a polished demonstration or a long feature list. The following questions bring together OECD recommendations and UNESCO’s human-centred and inclusion principles:
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- Pedagogical role: Is it a tutor, partner or assistant, and does that role fit the task?
- Teacher agency: Can teachers shape the use, review outputs and retain meaningful control?
- Protection and transparency: Are privacy, age suitability, safety, bias and system limitations addressed clearly?
- Access and relevance: Does it work for learners’ accessibility needs, languages, cultures and available infrastructure?
- Ongoing support: Is professional learning available so teachers can apply the tool appropriately and evaluate its effects?
How should education prepare students for AI?
Using AI in a lesson and teaching about AI are related but distinct goals. Students need opportunities to understand what AI can and cannot do, consider ethical and social implications, and develop the judgement to use it appropriately. UNESCO’s teacher competency framework offers a structure for educator development across human-centred practice, ethics, foundations and applications, pedagogy and professional learning. For students, the practical aim is not simply familiarity with a tool: it is the ability to question outputs, protect personal information and make informed decisions about when AI assistance is useful.
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