Neurodivergent people can contribute valuable skills to AI-related work, but no diagnosis guarantees a particular strength or performance. People have different abilities and support needs; whether they can use their skills depends in part on accessible tools, suitable work design and an inclusive workplace. AI can help with specific tasks, but it can also create privacy, bias and access problems.
What neurodiversity means for AI work
Neurodiversity is not a single work style or skill set. It includes people with varied experiences and support needs, including autism, ADHD and learning disabilities such as dyslexia, dyscalculia and dysgraphia. A person’s diagnosis alone does not tell an employer what tasks they will excel at or what accommodations will help.
The OECD’s 2026 report focuses on vocational education and the transition from learning into work, rather than every AI occupation. It synthesizes more than 50 stakeholder interviews and a workshop. Participants were recruited purposively, current vocational education and training learners were not interviewed, and the report notes possible positive-selection bias. The findings offer useful perspectives, not a representative or causal test of whether neurodivergent people perform better in AI roles.
Why skills can be underused
Skills are only useful when people have a fair chance to develop and demonstrate them. The OECD describes persistent education and employment gaps and stakeholder accounts that neurodivergent talent is undervalued or underused. Work processes built around one communication style, pace or sensory environment can make it harder for some people to participate, regardless of their actual ability to do the job.
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That makes inclusion a practical work-design issue, not just a matter of recruitment. Clear expectations, accessible communication, appropriate accommodations and support can help workers contribute. What works should be agreed with the individual rather than inferred from a label.
How AI and related tools may help with particular tasks
AI-enabled tools are not useful to everyone in the same way, and examples from education or desk-based work do not automatically apply to every occupation. The OECD describes current and emerging uses across vocational learning, work-based learning and employment transitions, including:
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- Ideal for Gifting
- Ideal for a bookworm
- Compact for travelling
- Reading and writing: text-to-speech, speech-to-text, and tools that help edit or summarize documents.
- Planning and attention: digital to-do lists and reminders that can support time management, working memory and attention.
- Learning and practice: adaptive learning materials, virtual or extended-reality rehearsal of task sequences, and generative AI practice for job applications or interviews.
- Meetings: tools that summarize discussions, where their use is appropriate and participants’ privacy is protected.
Some of these are established examples of use; others are potential applications. In either case, the relevant question is whether a tool reduces a barrier for a particular person doing a particular task—not whether it is marketed as “neurodivergent-friendly.”
What reported figures do—and do not—show
Available survey figures describe respondents’ views, not independently measured gains or proof that AI caused better performance. Their dates, populations and limitations matter:
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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →| Reported finding | What it measures |
|---|---|
| 87% felt more productive at work when using an AI assistant; 85% said AI helps them perform better in their roles. | Respondents’ perceptions in EY’s 2025 Global Neuroinclusion at Work Study, not measured productivity or job-performance outcomes. EY study. |
| 31% higher reported cybersecurity proficiency, 20% higher AI and big data skills, and 10% higher resilience, flexibility and agility in inclusive environments. | Survey-reported proficiency differences attributed to EY (2025) and relayed by the OECD in 2026. They are not universal effects of an accommodation or treatment. OECD report. |
| 57% said they would be more likely to disclose their neurodivergence if their employer provided specialized AI tools as a standard accommodation. | Hypothetical stated likelihood, not observed disclosure behavior. Understood.org reported the result from an online U.S. survey conducted by The Harris Poll on March 19–23, 2026, among 2,073 U.S. adults, including 614 neurodivergent respondents. The full-sample precision was reported as ±2.5 percentage points at 95% confidence; that figure does not make the disclosure response a causal finding. Understood.org survey announcement. |
The numbers should not be read as evidence that all neurodivergent employees want AI tools, that disclosure will rise in practice, or that AI itself produced the reported skill differences.
Risks and trade-offs to consider
Tools can introduce barriers as well as reduce them. The OECD identifies several concerns that matter when employers or training providers choose AI systems:
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- Privacy: tools may process sensitive personal, workplace or disability-related information. Users should understand what is collected, how it is stored and who can access it.
- Bias in hiring: systems trained on historical data can reproduce discrimination or assumptions about what a “normal” body or mind looks like. Automated screening should not be treated as neutral simply because it is automated.
- Cost and access: affordability can determine who benefits, particularly where an accommodation depends on a paid tool or suitable device.
- Poor fit or integration: a tool that does not work with existing systems, tasks or a person’s preferences may add friction instead of removing it.
- Overreliance: depending on automated writing or communication support without judgment may impede the development of writing, communication or critical-thinking skills.
AI support should complement, not replace, accessible work practices, human assistance and a person’s own judgment. The OECD cautions that biases can be replicated when systems rely on historical data that lack diversity. Its report frames AI as both a potential support and a source of risk.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to assess a workplace tool or accommodation
There is no one-size-fits-all tool or validated scoring system in the OECD findings. A practical discussion between the worker and employer can use these questions:
Best Value
- It can be a gift option
- Comes with secure packaging
- Helpful in various ways
- Task fit: What specific barrier or job task is the tool meant to address?
- Choice and control: Can the worker customize it, decide when to use it and opt out?
- Accessibility: Does it work with the worker’s preferred way of reading, writing, communicating or organizing tasks?
- Privacy: What data does it process, and are sensitive information and workplace conversations protected?
- Affordability: Can the worker access it reliably without bearing an unreasonable cost?
- Workflow and support: Does it integrate with the tools already used, and is a person available to help troubleshoot?
A short, voluntary trial on a defined task can clarify whether a tool helps, provided the worker has a say in the trial and understands how their data will be handled. A poor result with one tool is not evidence that the person cannot do the work; it may indicate that the tool or work process is a poor fit.
What employers and workers should take from the evidence
The strongest conclusion is conditional: neurodivergent people may bring useful capabilities to AI-related work, but those capabilities are varied and can be overlooked when workplaces are inaccessible. AI may help with concrete tasks such as reading, planning, writing or practice, but it is not a substitute for individualized support, fair hiring and privacy safeguards. Employers should evaluate tools by how well they serve a person and task, not by assumptions about a diagnosis.
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