One in seven in the UK are neurodiverse, with many more experiencing unrecognised cognitive differences that affect how they learn and work. Yet despite growing awareness of neurodiversity, traditional education systems still largely operate on a one-size-fits-all model.
Learning needs often go unidentified until learners fall behind, leading to frustration, low self-esteem, and in many cases, disengagement.
Emerging technologies, particularly those powered by AI, are offering new ways to reverse this trend, providing earlier identification, personalised support, and pathways to greater success for all learners.
Understanding the learner before problems arise
AI-enabled cognitive assessments represent a major step forward in identifying how individuals think, learn, and process information. Rather than focusing solely on visible academic performance, we can explore domains such as memory, attention, reasoning, and processing speed.
By understanding a learner’s cognitive profile early, providers can adjust teaching methods, communication styles, and support strategies to better align with individual strengths. Providers like Educationwise Academy and Hawk Training are embedding these approaches at the start of the learner journey, helping ensure that support is proactive rather than reactive.
From risk of dropout to higher completion rates
Early identification and support have a direct impact on learner success. At Educationwise Academy, cognitive assessments allow tutors to create highly personalised learning plans that anticipate potential challenges. As a result, apprentices feel more supported from day one, leading to better engagement and higher retention rates.
Similarly, Hawk Training uses cognitive insights to build stronger relationships between tutors and learners, allowing early support to become a natural part of the learning process rather than a response to problems.
Personalisation without the cost barrier
Historically, personalising education at scale has been prohibitively expensive. Specialist support often requires one-to-one teaching or individualised intervention plans, both of which can strain resources.
AI-driven platforms now enable education providers to deliver personalised learning strategies across large cohorts without significant cost increases. At Hawk Training, cognitive profiling
allows tutors to adapt learning delivery methods quickly and consistently, reducing administrative burden and ensuring that learners get the right support when they need it.
A new model for inclusive education
The success seen at Hawk Training is mirrored at Lincoln College, where cognitive assessments are embedded throughout the learner journey. The college uses data from these assessments to make timely referrals, personalise teaching approaches, and track the impact of interventions across programmes. Staff at Lincoln College say the technology helps “join the dots” between identifying needs, delivering support, and evidencing outcomes: something increasingly important under Ofsted’s Education Inspection Framework.
This proactive model of inclusion is helping Lincoln College build a more supportive, responsive learning environment for all learners, not just those with diagnosed differences.
Building independent learners through AI
Beyond supporting tutors, AI is also being used to empower learners directly. Real-time digital coaching, based on individual cognitive profiles, offers learners tailored advice to help them manage their studies independently. This includes nudges to stay focused, strategies to manage workload, and practical techniques to break complex tasks into manageable steps. At Realise Learning and Employment, early adoption of AI-driven coaching tools has helped apprentices balance the demands of study and work more effectively, improving outcomes across a wide range of programmes.
Human support enhanced, not replaced
A common concern around AI in education is whether technology might replace the human relationships that are so critical to learning. In reality, AI tools are being used to supplement and enhance human support, not replace it.
At Educationwise, cognitive insights allow tutors to better understand each learner’s needs, leading to more meaningful and productive tutor-learner interactions. Similarly, at Realise, learners use AI-based tools to reinforce strategies taught by tutors, creating a continuous support system that bridges formal learning sessions.
The future: AI-driven empathy at scale
The real promise of AI in education lies in empathy at scale. By recognising the diversity of how people think and learn, AI tools enable providers to treat learners as individuals without adding unsustainable resource pressures.
Institutions like Lincoln College, Hawk Training, Realise, and Educationwise are demonstrating that when cognitive diversity is acknowledged and supported early, educational outcomes
improve significantly. They all show that inclusive, personalised support can be the norm, not the exception.
Why early adopters matter
Their experiences offer important lessons for the wider education sector. By adopting AI-powered cognitive assessments and learner support tools early, these providers are setting new standards for inclusive, personalised education. They are also demonstrating how technology can drive measurable improvements in retention, attainment, and learner wellbeing.
Their examples show that technology’s role is not to replace educators, but to empower them – and to ensure that no learner is left behind because their brain works differently.
A more inclusive future is within reach
Cognitive diversity is not a niche issue; it affects a significant proportion of all learners. Building education systems that recognise and respond to this diversity is no longer optional: it’s essential.
AI-driven cognitive technologies offer a practical, scalable solution to the challenge of personalisation, providing earlier support and greater empowerment for learners. As more education providers embrace these tools, the vision of truly inclusive, equitable education moves closer to reality.
