The Role of AI in Mathematics Education

Artificial intelligence (AI) is no longer a futuristic concept; it’s here in classrooms, shaping how we teach and learn mathematics. Recent data shows a sharp divide: nearly half of surveyed educators believe AI will have a negative impact on education in the next five years, while 27% see it as a positive force, with many others still undecided (EdWeek Research Center, 2023). This split in opinion highlights the uncertainty ahead, but it also makes one thing clear: education is not on the cusp of a slow evolution, but a transformation.

For mathematics in particular, a subject often seen as both challenging and essential, the question is: what role will AI play, and how will it change the way we approach teaching, learning, and the curriculum?

AI and the Changing Role of the Teacher

The familiar picture of a maths teacher standing at the board while pupils silently copy notes into their books already feels outdated. AI systems can now generate step-by-step worked solutions, provide instant feedback, and adapt explanations to the learner’s level. This sounds really positive. In fact, a recent UNESCO report highlighted that AI tools have the potential to reduce teacher workload by up to 30% through automated assessment, feedback and marking, and lesson planning.

At first glance, this may sound as if technology is poised to replace teachers. But the opposite is true. Teachers are still central, but the role is shifting. Rather than spending hours marking, they can dedicate more time to higher-value activities: facilitating discussion, connecting mathematical concepts to real-world contexts, and supporting learners who feel anxious or stuck. If AI can provide valuable data within seconds, surely this is a better use of time so that teachers can use time saved to instead act upon it, rather than just review it?

Take, for example, a Year 6 classroom working on fractions. An AI tool might instantly identify which students are struggling with equivalence and whether there are any trends within the class. It might even suggest targeted activities to help them progress, ideas the teacher can then adapt to the needs of their learners.

Still, challenges remain. Many teachers worry about becoming over-reliant on AI or losing professional autonomy. The reality is that AI should not be seen as a replacement for teacher expertise, but as an assistant that strengthens it. When used as one tool among many, AI can lighten workload, free up time for richer interactions, and open up space for creativity and connection. The future of maths education, then, is not teachers versus technology, but teachers empowered by technology.

AI and the Learner’s Experience

For students, AI promises personalised learning at a scale that was previously unimaginable. Adaptive platforms, like Doodle Maths for example, can track how a child solves problems and then adjust the difficulty or style of questions in real time. This can feel empowering: instead of waiting for the whole class to 'catch up', learners can move forward at their own pace, or have highly individualised homework set within seconds.

This approach could be a game-changer for students who struggle with maths anxiety. Imagine a learner who freezes at the sight of a word problem. Instead of waiting until the next lesson to get feedback, AI can offer a gentle prompt immediately: “Try drawing a bar model.” This instant support can prevent small hurdles from turning into overwhelming barriers.

However, personalisation has its risks. If students only ever interact with AI-driven pathways, they may miss out on the richness of mathematical dialogue – explaining their thinking, debating methods, and learning from peers. As Holmes and Tuomi (2022) point out, AI can be useful for practising mathematical procedures, but if students lean on it too heavily, there’s a danger they end up just copying the steps a machine gives them instead of really thinking mathematically.

And there’s another challenge: confidence. AI can help improve test scores and speed up procedural work, but it doesn’t automatically strengthen students’ ability to explain their reasoning or build mathematical resilience. In short, better performance on paper doesn’t always mean deeper understanding. That’s why human interaction, such as peer collaboration, probing teacher questioning, and real-world problem solving, remains essential. These practices help students make sense of maths, explain their thinking, and persist when problems get hard.

AI and the Curriculum

Perhaps the biggest long-term impact of AI will be on the mathematics curriculum itself. If machines can handle calculations instantly and accurately, what skills should we prioritise for future generations? Should fluency in long division still take centre stage, or should more space be given to modelling, critical thinking, and data literacy?

Curriculum reformers are beginning to tackle these questions. The OECD (2023) highlights that mathematics education should increasingly prioritise competencies such as reasoning, problem-solving, and the responsible use of knowledge, rather than focusing only on procedural skills that AI can easily replicate. As the recent OECD research warns, “AI capabilities are quickly catching up with those of students,” this serves as a reminder that the human elements of creativity, judgment, and ethical reasoning are more important than ever. This doesn’t mean abandoning fundamentals, but it does mean rebalancing priorities.

We might see, for example, greater emphasis on statistical reasoning and data science, since these are central to understanding the world AI is shaping. Students could be asked to evaluate the outputs of an AI model: does the prediction make sense? What assumptions sit behind the calculation? In this way, maths education prepares learners not just to use AI, but to critically question it.

But there’s also the issue of equity. Access to AI is not equal across schools. According to the Sutton Trust (2023), teachers in less affluent schools are far less likely to receive training in AI. In fact, only 18% of teachers in the least advantaged schools had formal training, compared with 26% in the most advantaged. This gap risks widening inequalities if some students benefit from AI while others are left behind.

Looking Ahead

The arrival of AI in mathematics education is not just about efficiency; it’s about rethinking what it means to learn, teach, and apply mathematics in the 21st century. Teachers will still be the heart of the classroom, but their role will increasingly be about guidance, creativity, and care. Students will gain more personalised learning journeys, but they will also need opportunities for dialogue, exploration, and genuine mathematical play. And curricula must evolve, ensuring we prepare learners for a world where machines can already 'do the maths,' but only humans can interpret, question, and apply it meaningfully.

At Mindful Maths, we believe AI has the potential to relieve pressure on teachers and open new doors for learners , but only if we keep people at the centre. Maths is more than correct answers; it’s about curiosity, confidence, and connection. If AI can help us reclaim time and space for those human aspects, then its role in mathematics education will be not just disruptive, but transformative. And when technology strengthens, not replaces, the human side of learning, we can begin to change the way maths feels.

Together, let’s change the way maths feels - for good.

- Mindful Maths