So from June 1-8, AIC chapters are hosting 100+ events across 100+ cities on six continents — mixers, talks, and gatherings built around one question: what does it mean to be human in the AI era? Alongside the events, we're building a global time capsule: a record of what people around the world fear, hope, and believe about AI in this moment, captured for all of humanity to look back on.

There is a phenomenon happening in offices, remote setups, and co- spaces all over the world that has gone largely undiscussed: neurodivergent workers, those with ADHD, autism, dyslexia, dyscalculia, and related profiles are adopting AI tools at a disproportionately high rate. Eight in 10 (79%) of neurodivergent professionals already use AI at work and they are 55% more likely to use AI than neurotypical peers, according to the 2025 EY Neuroinclusion at Work Study.

Neurodivergent workers aren't adopting AI because their companies told them to. They're doing it because, for many of them, it's the first time a workplace tool has worked the way their brain does. This carries significant implications for how we think about AI, the future of work, and the 15–20% of the global population that is neurodivergent.

Mentra’s latest research identified a high level of ease with AI tools among neurodivergent professionals. More than half of the survey respondents (51%) feel very or somewhat comfortable with AI tools. The comfort Mentra detected isn't surprising when you consider the stakes: for many neurodivergent professionals, AI tools aren't a convenience, they're a genuine equalizer.

Before we can understand why neurodivergent workers are gravitating toward AI, we need to understand what the workplace has cost them up to this point. Masking, the practice of suppressing or camouflaging neurodivergent traits to conform to neurotypical norms, is not a choice. Masking is a survival strategy. It consumes enormous cognitive resources: the mental bandwidth spent making eye contact, modulating tone, structuring communication, managing sensory input, and performing neurotypicality is bandwidth that cannot be spent on actual work.

A growing body of research shows that masking creates a significant cognitive and emotional load, contributing to disproportionately high rates of burnout, anxiety, and depression among neurodivergent individuals. This pressure to appear neurotypical results in a “hidden” tax that extracts energy and focus, and harms wellbeing, yet remains largely invisible in how organizations measure productivity or support their workforce.

AI is more than a productivity tool. It’s becoming a cognitive scaffold for neurodivergent workers. For many, AI tools are doing something no workplace accommodation ever quite managed: they're absorbing the masking labor by offloading the mental labor of constant self-translation, something traditional accommodations rarely fully address.

Tools like ChatGPT or Claude act as real-time bridges between thought and output: turning stream-of-consciousness ideas into structured emails, tracking the thread of long documents, and removing the pressure to produce perfectly polished responses on demand, a challenge that disproportionately affects people with ADHD or dyslexia.

For autistic professionals, AI reduces social ambiguity: no tone decoding, no hidden subtext, no constant calibration. Interaction becomes simpler, less draining, and more predictable. There is no subtext to parse, no facial expression to read, no fear of saying the wrong thing in the wrong tone. The cognitive load of human interaction, often cited as a primary driver of autistic burnout, drops substantially. In short, AI is a workplace tool that adapts to how people think, rather than forcing them to adapt to it.

Figma's recent research on shifting roles found that 72% of workers cite AI tools as the top factor reshaping how they work and respondents now spend nearly 19% of their time co-creating with AI, a figure expected to reach 27% by mid-2026. But who, within that population, is driving the most enthusiastic adoption and why?

When a tool lowers the cognitive burden of masking rather than adding to it, neurodivergent employees don’t just adopt it; they integrate it into their work as essential infrastructure. Neurodivergent job seekers and employees are not passive users of AI tools. They are power users, integrating AI into communication, task management, interview preparation, and professional writing at rates that suggest something more than casual adoption. They become dependent on it in the best possible sense. It becomes infrastructure.

The broader implication is significant. If neurodivergent workers are among AI's earliest and most enthusiastic adopters, they are also the population most likely to develop genuine fluency with these tools. Companies that have historically underestimated or overlooked this talent pool may find themselves sitting on an AI-readiness advantage they didn't know they had.

There is a blind spot, however.

Most employer conversations about AI adoption are focused on training, change management, and productivity measurement. They are not asking which employees are already ahead of the curve or why. The result is that neurodivergent workers who have quietly built sophisticated AI workflows are often not recognized as the early adopters and internal experts they are. Their fluency is invisible, in part because they learned it outside the formal structures their employers recognize.

This is not new. Neurodivergent workers have long developed compensatory systems such as elaborate note-taking architectures, time-blocking rituals, and environmental hacks that remain invisible to managers because they don't look like the conventional signals of competence. AI is simply the latest version of this pattern. The accommodation is happening, yet the recognition is not.

The reason AI is effective for neurodivergent users is that, unlike most workplace systems, it meets the user where they are. It doesn't require a specific communication style. It doesn't penalize a non-linear thought process. It doesn't demand that the user perform a particular version of professionalism before it will engage with them. In this way, AI has done something that decades of workplace accommodation policy never quite achieved: it has defaulted to flexibility rather than conformity.

The lesson for the next generation of workplace AI tools is clear. If the goal is genuine inclusion (not just DEI optics) then tools must be designed with neurodivergent users as a primary use case. This means interfaces that reduce sensory overload. Communication tools that don't penalize non-standard phrasing. Task systems that support non-linear workflows. Performance systems that measure output, not work performance.

The economic case is straightforward. Neurodivergent workers represent 15–20% of the workforce. Many have been systematically underemployed relative to their capability. This is not because of skill gaps, but because the systems around them were built for someone else. AI, designed intentionally, is the first technology capable of closing that gap at scale. The companies that understand this will have access to a talent pool that their competitors are still filtering out.

The quiet power users of AI have already shown us what the future of work can look like. It’s one where tools adapt to people, not the other way around. Neurodivergent professionals aren’t simply getting a head start with new technology; they’re pioneering a model of work built on accessibility, authenticity, and cognitive inclusion.

As organizations race to operationalize AI, many are overlooking the very employees who’ve already mastered how to work alongside it. The companies that win won’t be the ones with the most AI licenses, but the ones that support the people who have been quietly building the blueprint for how to use it best. Employers that recognize and retain this talent aren’t just supporting inclusion. They’re gaining an unexpected edge in AI fluency, positioning themselves ahead of the curve in the future of work.

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