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Neurodivergent people can contribute valuable perspectives and skills to AI-related work, but no diagnosis guarantees a particular ability or job performance. Whether those skills can be used depends in part on the work environment: accessible tools, thoughtful task design and appropriate support can help people contribute, while exclusion and poorly chosen technology can create new barriers.
What neurodiversity means for AI work
Neurodiversity describes variation in how people think, learn and process information. It includes people with autism, ADHD and learning disabilities such as dyslexia, dyscalculia and dysgraphia. People within each group differ widely in their strengths, preferences and support needs; a label is not a reliable predictor of how someone will perform a specific task.
That matters in AI work, which spans many activities: developing or evaluating systems, working with data, supporting users, managing projects and using AI tools in other jobs. There is no single neurodivergent profile that maps neatly to this range of work. The practical question is whether the person, task, tools and workplace fit together.
Why workplace inclusion affects whether skills are used
Skills are not always visible in environments built around one way of communicating, learning or organizing work. The OECD’s 2026 report describes persistent gaps in education and employment and stakeholder accounts of neurodivergent talent being undervalued or underused. Its findings point to the importance of context and support, rather than an assumption that ability alone determines outcomes.
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The report draws on more than 50 stakeholder interviews and a workshop, with a focus on vocational education and the transition into work. It is a qualitative synthesis, not a representative study showing that a particular accommodation causes better job performance. Participants were recruited purposively, current vocational education and training learners were not interviewed, and the report notes possible positive-selection bias. Its findings should not be generalized to every AI occupation or workplace.
How AI and related tools may help with specific tasks
AI-enabled and other digital tools can reduce some task barriers when they suit the individual and the work. The OECD describes examples across vocational learning, work-based learning, the transition to employment and desk-based jobs:
- Reading and writing: Text-to-speech can make written material available as audio; speech-to-text can help turn spoken ideas into text. Writing assistants may help with editing, while summarization tools can condense documents or meeting notes.
- Planning and attention: Digital to-do lists and reminders can support planning, time management, working memory and attention.
- Learning and practice: Adaptive learning materials may be adjusted for different needs. Extended- or virtual-reality tools may let someone rehearse a task sequence or job interview.
- Applications and interviews: Generative AI can be used to practice interview questions or prepare application materials. These are practice aids, not guarantees of a successful application or interview.
These examples are not suitable for everyone or every role. A tool that helps with one task may not help with another, and some examples in the OECD report describe potential uses rather than established results across workplaces. The person using a tool should have meaningful choice and control over whether and how it is used.
What reported figures do—and do not—show
Available survey figures offer a view of respondents’ experiences and expectations, not proof that AI tools cause better performance or that neurodivergent employees share the same experience.
| Finding | What it measures | How to interpret it |
|---|---|---|
| 87% felt more productive at work when using an AI assistant; 85% said AI helps them perform better in their roles. | Respondents’ perceptions in the EY Global Neuroinclusion at Work Study, 2025. | These are self-reported perceptions, not independently measured productivity or causal effects. |
| 31% higher reported cybersecurity proficiency, 20% higher AI and big data skills, and 10% higher resilience, flexibility and agility in inclusive environments. | EY figures from 2025, as cited by the OECD in 2026. | These are survey-reported differences relayed by the OECD, not universal effects of inclusion or a guarantee for an individual worker. |
| 57% said they would be more likely to disclose their neurodivergence if their employer provided specialized AI tools as a standard accommodation. | A hypothetical disclosure response in an Understood.org online U.S. survey conducted by The Harris Poll, March 19–23, 2026. The survey included 2,073 U.S. adults, including 614 neurodivergent respondents; reported full-sample precision was ±2.5 percentage points at 95% confidence. | This measures stated likelihood, not observed disclosure behavior or a causal effect of providing tools. |
Risks to consider before relying on AI tools
AI assistance can remove friction, but it can also introduce risks. The OECD identifies privacy concerns around sensitive data, affordability barriers, poor fit or integration, and the possibility that overreliance may impede development of writing, communication or critical-thinking skills.
Recruitment systems deserve particular care. If an AI system is trained on historical data that reflects past exclusion, it can carry those patterns into screening or assessment. The OECD warns that such systems can reproduce assumptions about what counts as a “normal” body or mind. Employers should not treat an automated score as a neutral or complete account of a candidate’s capability.
How to choose and introduce a workplace tool
There is no validated scorecard for selecting tools in the OECD findings, but its identified concerns suggest useful questions for a practical trial:
- Task fit: Which specific task or barrier should the tool address, and how will the user know whether it helps?
- Customization and control: Can the person adjust the tool, choose when to use it and decline it without penalty?
- Accessibility: Does the interface work with the person’s preferred ways of reading, writing, listening or organizing?
- Privacy: What information is collected, stored or shared, especially if it may reveal sensitive personal or workplace details?
- Cost and access: Is the tool affordable and available to the people who need it, rather than only to some teams or employees?
- Workflow and human support: Does it integrate with existing work, and is someone available to help when it fails or produces an unsuitable result?
Employees should not have to disclose a diagnosis simply to be considered for AI-related work. Where an accommodation is requested, the conversation should focus on the task, the barrier and the support that would help, while protecting personal information. An AI tool can be one option; it should not replace human judgment, accessible work practices or needed support.
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What employers and teams can do
Organizations can make skills easier to use by designing work around clear outcomes and allowing reasonable flexibility in how people reach them. Useful practices include offering accessible communication formats, making expectations explicit, providing suitable assistive tools, and giving workers a way to request adjustments without stigma. For AI-assisted tasks, teams should set expectations for checking outputs and protect people from being judged solely by automated assessments.
The OECD’s evidence supports a conditional conclusion: AI and related technology may help some neurodivergent learners and workers with particular tasks, but successful use depends on individual fit, safeguards, access and workplace support. Neurodiversity is not itself a job qualification or a promise of special AI aptitude; inclusive conditions help people show what they can do.
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