AI to Support Neurodivergent Learners in Vocational Education and Training

Young neurodivergent people – including those with Autism Spectrum Disorder (ASD), Attention-Deficit/Hyperactivity Disorder (ADHD), and learning disabilities, such as dyslexia, dyscalculia and dysgraphia – can struggle to complete compulsory education and to transition to further and higher education and training and eventually the labour market. Persistent gaps in educational and employment outcomes signal that neurodiverse talents are undervalued and underused, imposing costs to society in the form of lost productivity, higher welfare spending and worse health outcomes. More inclusive education, both general and vocational, and workplaces could help bridge these gaps.

Vocational Education and Training (VET) can be an important setting for neuroinclusive learning, given its diverse mix of learners with varied skills and work experience, and its focus on practical, job-specific and employability skills. Yet neurodivergent learners can face challenges in VET – as in general education – such as a lack of tailored instruction, insufficient support in learning and work environments, and stigma around neurodivergences.

AI (Artificial Intelligence) and other advanced technologies could help address some of these challenges and support neurodivergent learners in VET settings, including in work-based learning and apprenticeships, and the school-to-work transition. Drawing on insights from over 50 stakeholder interviews, this report highlights this potential but also identifies barriers and ethical, pedagogical and societal risks associated with these technologies.

AI and other advanced technologies have the potential to make VET more adaptive, accessible, and inclusive for neurodivergent learners:

• AI-enabled adaptivity allows instruction and feedback to be tailored to diverse needs, learning styles and abilities, helping bridge gaps in participation and performance. Some teachers already use generative AI to generate multiple versions of an exercise sheet for different learner profiles.

• Extended Reality (XR) technologies enable immersive, practice‑oriented learning in safe environments that facilitate repetition and rehearsal and can accommodate individual needs. Virtual Reality (VR) and Augmented Reality (AR) allow learners to rehearse task sequences or challenging interactions (such as job interviews), build confidence and manage anxiety before moving to real-life practice in the context of work-based learning.

• VET’s accessibility is enhanced through tools such as text-to-speech and speech-to-text. These “profoundly impactful” tools enable each learner to engage with the curriculum in ways that align with their strengths. These tools are not new but they have become more accurate and fluid due to recent improvements in LLMs and in cloud computing.

• Other tools seek to directly address difficulties that neurodivergent learners may face, such as with executive function. Neurodivergent VET learners already use simple technologies, such as digital to-do lists and video and written reminders, to assist with planning, time management, working memory and attention, while interviewees highlighted the possibility to leverage the latest advances in AR, wearables and AI’s ability to identify patterns (e.g. in behaviour or in stress responses), to personalise these tools to users and their learning and work environments.

• Transitions from VET to employment can become smoother if neurodivergent learners leverage new technologies such as generative AI to build independence, confidence and other employability skills, and to assist with the job application process (e.g. CVs and interview practice) and in the job itself. Additionally, the widespread use of generative AI at work could help remove some of the stigma associated with use of writing assistance tools.

However, a range of barriers prevent the full potential of these technologies from being realised. Learners, teachers (including trainers) and employers can be overwhelmed by the growing number of available tools, while VET teachers often lack the capacity and/or support to fully engage with new technologies. While desk- and computer-based work can easily accommodate new tools, the diversity of work and learning environments within VET presents practical and technical challenges. Affordability remains a significant barrier, limiting access and driving inequalities. At the same time, many promising technologies fail to reach the market, and those that do often do not align with the real needs of VET institutions, teachers and learners, and do not integrate well with existing systems.

The use of AI and other advanced technologies to support neurodivergent learners in VET also raises a range of ethical, pedagogical and societal risks, many of which also apply to general education system and to neurotypical learners.

• Data privacy risks could be amplified for neurodivergent VET learners due to the sensitivity and nature of data collected and uncertainties about who is responsible when data is shared between schools, training centres and employers. At the same time, an overly prescriptive approach to these risks could leave neurodivergent VET learners deprived of useful tools.

• Biases are replicated and perpetuated when AI systems are trained on historical data, which lack diversity and imbed assumptions about what counts as a “normal” body or mind. Discrimination against neurodivergent individuals is a serious harm that can result when biased systems make decisions that directly affect an individual’s livelihood and ability to transition to the labour market, for instance in AI-enabled recruitment tools.

• Overreliance on these technologies could hinder the development of fundamental skills, such as critical thinking, writing and communication skills. Interactions with generative AI chatbots could leave learners unprepared for real-life interactions with colleagues who provide nuanced, ambiguous or challenging answers.

• Concerns about AI-assisted cheating could put the legitimate use of assistive technologies (particularly writing assistance tools) at risk. The question of how to fairly assess students in light of the latest generative AI tools is as yet unresolved within VET and the wider education system.

• Socio‑emotional risks associated with generative AI chatbots and robots are not yet fully understood, not least for neurodivergent learners. One risk is that emotional attachments to robots or generative AI chatbots could expose learners to harmful content and interactions.

The following policy guidelines can help governments seize the potential of AI and other advanced technologies to support neurodivergent learners in VET:

• Apply existing frameworks governing accessibility, disability rights, AI, data privacy etc.

• Prepare and support VET teachers with skills and knowledge to use AI and other advanced technologies to support neurodivergent learners

• Help neurodivergent learners, VET institutions and employers to navigate the many AI and other advanced technologies available.

• Fund assistive technologies and support the assistive technology ecosystem.

• Encourage developers to improve the accessibility of AI and other advanced technologies and to better align them with the needs of neurodivergent learners.

• Use AI and other advanced technologies to help achieve more responsive, inclusive and innovative VET systems.