I was chatting to a friend recently, this friend is someone that has embraced AI from the beginning and has become a source of wisdom and information on how best to use it. Gustav Patrick describes himself as “More of an explorer than an expert”, but that’s because he has a lot of humility – in reality he is both. He works in the legal industry and likes figuring out AI use-cases for that space, but he applies that thinking everywhere else, too.
I was talking to him about my research, and how it was now much clearer to me why the education system doesn’t work very well for ADHD kids, and why so many of them end up in the school-to-prison pipeline. It has long been known that interest levels play a part in how well kids with ADHD can progress academically (Russell et al., 2023), but innate interest vs boredom is a far more significant factor than currently understood. In my as-yet-unpublished research, one of the core themes is ‘Interest Based Performance Extremes’. It discusses the binary nature of being interested by something or not. For kids with ADHD (and adults, too) interest allows the kids to engage, and therefore acquire, retain, and recall information around it. If they are not interested in it, they cannot force themselves to engage, so they become bored and seek other stimuli (including disruption).
Teachers, parents/guardians, and many experts are well aware of the interest vs boredom problem. There are institutions, policies, tailored curriculums, etc… which try to work around the problem. But to-date it’s been difficult because of the limitations around resource, time, and cost. In an ideal world, every child – neurodivergent or not – would have a dynamic tailored learning plan with real-time feedback based on their learning styles. But most school classes will have a teacher, a learning assistant, and perhaps another staff member for SEN in a class of around 30 kids. Even if they had the time to understand every child’s optimal learning style each year, trying to plan, implement, and measure with all of those differences is just not possible.
That is why the curriculum is the way that it is. It works somewhat for the majority. It might be just right for a considerable number of children, a few may get through with some help, and there will always be another few who really struggle with it. This does not just affect their academic futures, or their future careers. This affects their confidence with learning, which alters whether they feel they can learn, impacting their choices going forwards. Some will just decide they cannot learn like others do, and give up trying to progress on that standardised pathway, carving their own path instead. These pathways take longer routes in life, often filled with many extra and unnecessary obstacles. Some end up in success – but many do not. Many such pathways, unguided as they are, go via school expulsions and dropping out, to prisons, substance abuse, and wasted potential. These kids have their confidence damaged early on because they cannot do things in the same way as others, which breeds self-doubt in them. It doesn’t have to be this way though.
Gustav led me to learning about Intelligent Tutoring Systems (ITS), a dynamic AI-based, personalised curriculum. He explained some of the use-cases, how it was applicable to teaching kids in a general sense, but how he could see it being even more useful for teaching ADHD kids with interest levels being such an important factor. He was right. I have learning about it since, and it fills me with optimism – I believe it is genuinely a real, practical solution that can make a huge difference to the trajectories of so many with ADHD.
This isn’t just putting books on a screen. Major educational bodies are now exploring how AI can make learning more inclusive and accessible for every student (European University Association, n.d.). The goal is to build a lesson plan that fits the child, not the other way around.
Getting the ADHD Brain Engaged
One of the biggest challenges for a student with ADHD is staying engaged. A smart tutoring system tackles this by not just demanding focus, but earning it. For the ADHD brain, interest is the on-switch. It’s the key that unlocks their focus, and their ability to hyperfocus.
ITS uses Interest-Based Learning. The AI can take any school subject and wrap it in a topic the child already loves. This approach is central to empowering students with ADHD, as it directly addresses their need for engaging content.
- Is a student obsessed with space? A boring fractions lesson becomes a vital mission to calculate fuel for a rocket ship.
- Does a child love animals? Reading practice turns into an exciting virtual safari, with facts and stories about their favourite creatures.
This is often paired with ‘Smart Gamification’. This isn’t just about points and badges. The AI learns what actually motivates your child by adjusting the challenge to keep them in that sweet spot of feeling successful. Reviews of the research confirm that using gamification can have a positive effect on learning for students with ADHD (Wang & Tahir, 2020). The learning goal stays the same, but the journey there is suddenly exciting and meaningful.
Education That Learns You
The real magic of this technology is that it learns how your child learns. And the evidence shows it works. One major study found that AI tutoring was more effective than some traditional in-class activities (Klink et al., 2024). This is why a new wave of companies are launching AI tutors with the goal of closing learning gaps (Staufenberg, 2023).
The system is constantly gathering information to understand your child’s unique thinking style, a process known as adaptive learning. Scoping reviews on this topic have found that these adaptive systems are a promising avenue for students with ADHD (Khenissi et al., 2022). The system notices things like:
- The types of mistakes they make.
- How long it takes them to answer.
- How they use hints.
Based on this, the system is always learning and adapting. This is not just a theory; systematic reviews of the research have confirmed that these AI-driven systems are effective in K-12 education (Zou et al., 2024).
This technology is not meant to replace teachers. Even reviews of popular tools like ChatGPT show that while they are helpful, they don’t take the place of a human expert (Sexton, 2024). It is a tool for teachers. An AI tutor can act as a tireless co-pilot for every single student, handling the detailed work of personalising lessons.
This frees up the teacher to do the things only a human can do: mentor, inspire, and provide emotional support.
The real impact goes far beyond the classroom. By giving a child an environment where they can feel successful on their own terms, we do more than teach them school subjects… we help them build a core belief in their own ability to succeed.
I am not suggesting this is a panacea, I know more is needed in other areas. But I genuinely believe this has huge potential when it comes to addressing the challenges neurodivergent people face throughout their entire life journeys. I intend to learn more in this space, and do whatever I can to increase adoption rates in schools – I suppose I had better learn how to become a lobbyist, in that case.
References
Birnbaum, M. L. (2025, February 2). ADHD, executive functions, and AI: A new era in treatment. Psychology Today. https://www.psychologytoday.com/gb/blog/screen-play/202502/adhd-executive-functions-and-ai-a-new-era-in-treatment
European University Association. (n.d.). Using AI to serve inclusive education. Retrieved September 26, 2025, from https://eua.eu/our-work/expert-voices/using-ai-to-serve-inclusive-education.html
Kaplan. (n.d.). Five ways AI can support neurodivergent learners. Retrieved September 26, 2025, from https://kaplan.co.uk/blog/learning/five-ways-ai-can-help-neurodivergent-learners
Khenissi, M. A., Essalmi, F., & Jemni, M. (2022). A Scoping Review of Adaptive Learning for Students with ADHD. Education and Information Technologies, 27(4), 5121–5143. https://doi.org/10.1007/s10639-021-10811-3
Klink, K., Veldkamp, C. L. S., Schyr, J., de Vente, W., & Hu, Y. (2024). AI tutoring outperforms in-class active learning: An RCT introducing a novel research-based design in an authentic educational setting. Scientific Reports, 14(1), 7027. https://doi.org/10.1038/s41598-024-57652-6
Russell, A. E., Benham‐Clarke, S., Ford, T., Eke, H., Price, A., Mitchell, S., Newlove‐Delgado, T., Moore, D., & Janssens, A. (2023). Educational experiences of young people with ADHD in the UK: Secondary analysis of qualitative data from the CATCh‐uS mixed‐methods study. British Journal of Educational Psychology, 93(4), 941–959. https://doi.org/10.1111/bjep.12613
Sexton, J. (2024, May 14). What it’s actually like studying with ChatGPT’s AI tutor. Mashable. https://mashable.com/article/chat-gpt-study-mode-review
Staufenberg, J. (2023, November 24). The companies launching AI tutors to transform the attainment gap. SchoolsWeek. https://schoolsweek.co.uk/the-companies-launching-ai-tutors-to-transform-the-attainment-gap/
Wang, Y., & Tahir, R. (2020). The effect of using gamification for students with ADHD: A literature review. Technology, Pedagogy and Education, 29(5), 613-627. https://doi.org/10.1080/1475939X.2020.1812328
Zou, D., Wang, Y., Zhang, R., & Xie, H. (2024). A systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education. Education and Information Technologies, 29(6), 7635–7660. https://doi.org/10.1007/s10639-024-12507-2