Artificial intelligence used to sound like something schools would deal with in the distant future.
Today, students can ask an AI tool to explain algebra, generate practice questions, improve a draft, translate instructions, or simulate a conversation in another language within seconds.
Teachers are using the same technology to brainstorm lesson activities, develop quizzes, adapt materials, and reduce repetitive administrative work.
Understanding how artificial intelligence is changing teaching and learning therefore involves much more than discussing whether students should be allowed to use chatbots.
AI is beginning to influence how lessons are prepared, how students practise, how feedback is delivered, and even which skills schools need to prioritize.
The change is already visible. OECD data reported in 2026 showed that 37% of lower-secondary teachers surveyed had used AI for their work in 2024, while 57% agreed that AI could help write or improve lesson plans.
But faster work does not automatically mean better learning. The real challenge is using AI without removing the thinking students need to do themselves.
AI Can Give Students More Personalized Support
Traditional classrooms naturally contain students with different levels of understanding.
One learner may immediately understand a mathematics concept, while another needs a slower explanation and several additional examples.
AI tools can potentially provide more personnalized practice.
A student might ask:
“Explain photosynthesis as if I were 12.”
Then:
“Give me a more advanced explanation.”
Finally:
“Quiz me with five questions, but don’t show the answers until I respond.”
This type of interaction allows students to request explanations and practice at the moment they need them.
The OECD’s 2026 Digital Education Outlook notes that educational generative AI can function as a tutor or pedagogical agent when it is intentionally designed around learning principles.
Instead of simply giving answers, well-designed systems can question students, offer hints, and adjust their approach during a conversation.
That distinction matters.
An AI that immediately solves homework may save time.
An AI that helps students reach the solution themselves may support learning.
AI Tutors Can Make Practice More Interactive
Digital tutoring systems existed long before modern generative AI.
What has changed is the ability to communicate through natural conversation.
Instead of clicking through a rigid sequence of questions, students can now ask follow-up questions such as:
“Why is my answer wrong?”
“Can you give me a hint instead of the solution?”
“Show me a similar example.”
“Explain the difference between these two concepts.”
That flexibility can make digital learning feel more responsive.
For example, a student learning economics could explain inflation to an AI tutor. The system could identify a missing idea and ask the student to consider how supply disruptions affect prices.
The student remains intellectually involved.
UNICEF’s updated guidance on AI and children identifies AI-enabled tutoring, personalized learning, formative assessment, and accessible educational resources as potentially valuable uses when evidence supports their benefits and risks are appropriately managed.
The strongest AI tutor may therefore be the one that does less answering and more questioning.
Teachers Are Using AI to Reduce Planning Work
Teachers spend considerable time outside classroom hours creating resources.
That can include writing questions, adapting worksheets, designing examples, developing model answers, and preparing differentiated activities.
Generative AI can accelerate some of these tasks.
For example, a science teacher could ask an AI system to produce ten questions about forces at three difficulty levels.
The teacher can then review, correct, and adapt the questions before using them.
Recent evidence suggests this can produce meaningful time savings.
An Education Endowment Foundation trial involving 259 teachers across 68 schools found that teachers using ChatGPT with implementation guidance spent an average of 56.2 minutes per week preparing relevant lessons and resources, compared with 81.5 minutes for the comparison group.
That represented an average reduction of about 31%, while expert reviewers found no apparent reduction in resource quality.
That does not mean AI should write entire courses automatically.
Teachers still understand their students, curriculum, school context, and learning goals better than a general-purpose chatbot.
AI works best as an assistant rather than an invisible replacement teacher.
Feedback Can Become Faster and More Frequent
Students benefit from knowing what they misunderstood while the learning is still fresh.
AI can potentially shorten the feedback cycle.
Imagine a student writing a paragraph about climate change.
Instead of simply asking AI to rewrite the paragraph, the student might ask:
“Identify the weakest part of my argument without rewriting it.”
The system could highlight that an important claim lacks supporting evidence.
The student then has to improve the argument.
Similarly, an AI-supported mathematics platform could identify repeated errors with fractions and provide additional practice before the student moves forward.
The U.S. Department of Education has identified feedback, formative assessment, pattern detection, and instructional support as important potential applications of AI while also warning that automated systems introduce questions involving bias, fairness, transparency, and decision-making responsibility.
Automated feedback can be useful.
But important educational judgments should not simply disappear into an algorithm.
Teachers still need to interpret what the data means.
AI Is Changing What Good Assessment Looks Like
Generative AI has created an obvious problem for traditional homework.
If an AI system can produce a respectable essay, solve common problems, summarize readings, and generate code within seconds, teachers can no longer assume that a polished take-home assignment automatically represents independent student understanding.
The OECD reported that 72% of lower-secondary teachers surveyed believed AI could damage academic integrity by allowing students to present AI-generated work as their own.
Schools are responding in different ways.
Some assessments may need more supervised work.
Others may include oral explanations, drafts, process notes, practical demonstrations, presentations, or follow-up questions.
Instead of asking only for a finished essay, a teacher could request the initial argument, source evaluation, draft, final version, and a short explanation of how the student’s thinking changed.
AI can even become part of the assessment.
Students might critique an AI-generated answer, identify factual mistakes, evaluate weak reasoning, or improve an inaccurate explanation.
The question changes from:
“Can students avoid AI?”
to:
“Can students use and evaluate AI intelligently?”
That is a much more realistic educational challenge.
Students Need to Learn When Not to Use AI
One of the most important lessons about artificial intelligence may be knowing when to turn it off.
The OECD’s 2026 review makes an important distinction between improved performance and actual learning.
Students using general-purpose generative AI can sometimes produce stronger immediate work without developing stronger knowledge or skills. When AI access is removed, the performance advantage may disappear or even reverse.
Consider a student learning to write.
If AI generates every thesis statement, reorganizes every paragraph, and rewrites every sentence, the final essay may look impressive.
But whose writing skills improved?
The student’s or the AI’s?
Schools therefore need learning periods where students think without assistance.
A useful pattern might be:
First, try independently.
Then, use AI for feedback or alternative explanations.
Finally, explain the answer without AI.
Technology should support cognitive effort rather than permanently replacing it.
Teachers Are Becoming Guides for AI-Assisted Learning
AI does not eliminate the importance of teachers.
It may actually make teacher judgement more important.
Students now face an environment where generating information is incredibly easy.
Evaluating that information is harder.
Teachers increasingly need to help students ask questions such as:
Is this claim accurate?
Where did the information come from?
What evidence supports it?
Could the response contain bias?
What information is missing?
Should AI even be used for this task?
UNESCO recommends a human-centred approach to generative AI in education, emphasizing privacy, ethical validation, age-appropriate use, human agency, and pedagogical purpose.
The future teacher may spend less time being the sole provider of information and more time helping students interpret, question, apply, and challenge information.
That is not a smaller role.
It is a different one.
AI Literacy Is Becoming a Basic Educational Skill
Students do not only need to know how to use AI tools.
They need to understand their limitations.
Generative AI can produce confident answers that are inaccurate. It can reproduce biases from data, misunderstand context, invent references, or present incomplete information convincingly.
Students should therefore learn how to verify AI-generated content.
If an AI tool gives a historical statistic, check the original source.
If it generates a scientific explanation, compare it with a reliable textbook or academic reference.
If it summarizes an article, read the original when the details matter.
Students should also understand why entering personal or confidential information into AI systems can create privacy concerns.
UNICEF’s child-centred AI framework emphasizes safety, privacy, fairness, transparency, inclusion, accountability, and preparing children with the skills needed to navigate an AI-shaped world.
AI literacy may eventually become as normal as digital literacy or information literacy.
Knowing how to operate the tool is only the beginning.
AI Can Improve Accessibility and Inclusion
Artificial intelligence can also remove certain barriers to learning.
Text-to-speech systems can support students who have difficulty reading conventional text.
Speech recognition can help students who struggle with typing.
Translation tools can support multilingual learners.
AI can simplify complex explanations, provide alternative examples, generate captions, and help adapt materials into more accessible formats.
UNICEF specifically identifies improved accessibility for children with disabilities as an important opportunity created by AI while emphasizing that systems must still protect children’s rights and avoid discriminatory outcomes.
However, AI can also introduce new inequality.
Students with reliable internet, modern devices, paid AI tools, and strong digital skills may have very different opportunities from students without those resources.
UNICEF’s Digital Education Strategy 2025-2030 therefore places equity at the center of digital and AI-enabled education, including gender, disability, language, and broader digital divides.
AI in education should expand access rather than create another divide.
Schools Need Clear Rules Instead of Simple Bans
When generative AI first entered education, banning it seemed like an obvious response.
But AI is increasingly embedded in search tools, writing applications, productivity software, learning platforms, and everyday technology.
The boundary is becoming harder to draw.
Schools need clearer expectations instead.
For example:
AI might be prohibited during an independent writing assessment.
It might be permitted for brainstorming during a project.
It could be encouraged when students are asked to critique an AI response.
Students should know which rule applies before they begin.
Policies also need to address privacy, age appropriateness, bias, transparency, and data security.
UNESCO’s global guidance stresses that institutions need frameworks for the ethical and pedagogically appropriate use of generative AI rather than adopting technology without adequate validation.
Clear rules protect both teachers and students.
Confusion creates opportunities for misuse.
The Evidence Is Promising but Still Developing
AI is moving faster than educational research.
That creates a risk of making large claims based on exciting demonstrations rather than strong evidence.
A 2026 Stanford review examined a repository containing more than 800 academic papers related to AI in K–12 education and concluded that rigorous causal evidence remains relatively thin despite rapidly growing research activity.
This does not mean AI has no educational value.
It means schools should be careful about assuming that every new tool improves learning.
Ask practical questions.
Does the technology improve understanding?
Does it save teachers time?
Does it increase student independence or reduce it?
What happens when students no longer have access to the tool?
Are there effects on disadvantaged learners?
Good education has always involved testing methods, observing outcomes, and improving practice.
AI should recieve the same scrutiny.
Human Skills May Become Even More Valuable
As AI becomes better at generating routine content, distinctly human abilities may become more important.
Students will still need critical thinking.
They will need creativity, judgement, communication, collaboration, curiosity, ethical reasoning, and the ability to recognize when something does not make sense.
They will also need foundational knowledge.
Critical thinking is difficult when you know nothing about the subject you are evaluating.
The goal of AI-supported education should therefore not be to eliminate intellectual effort.
It should help students use effort more productively.
A calculator changed mathematics education, but students still need mathematical understanding.
Search engines changed research, but students still need information literacy.
AI will probably create a similar shift.
The tool changes.
The need to learn remains.
Artificial intelligence is changing teaching and learning through personalized support, conversational tutoring, faster feedback, lesson preparation, accessibility tools, and new approaches to assessment.
It can help teachers reduce repetitive work and give students additional ways to practise and explore difficult ideas.
But AI can also make it dangerously easy to produce work without developing the knowledge behind it. That is why human judgement, academic integrity, AI literacy, privacy, and independent thinking must remain central.
Schools do not need to choose between completely rejecting AI and using it everywhere. A better approach is to identify where it genuinely improves learning and where students still need to work independently.
Start with one classroom task. Ask whether AI should replace, assist, challenge, or stay out of that activity. Making that decision deliberately is the first step toward using AI as a learning tool rather than simply a shortcut.