Patterns of Leadership Blog

Tag: neurodivergent

  • Shared workplace needs of neurodivergent and Gen Z employees

    More and more HR and business leaders are focusing on how to keep their growing Gen Z workforce motivated and connected. When I listen to the conversations about supporting Gen Z colleagues, now roughly aged 12 to 27, I keep hearing themes that also come up when we talk about neurodivergent needs at work.

    As a neurodiversity advocate, that feels genuinely encouraging. In many cases, the same changes organisations make to help Gen Z thrive also make the workplace easier to navigate for neurodivergent people. In a fast-changing world of work, taking time to understand different employee experiences is one of the best routes to inclusion and stronger performance.

    To show why this can be a win for everyone, here are a few of the overlaps I see when engaging Gen Z and neurodivergent (ND) employees.

    Flexibility and work life balance

    Gen Z: Many Gen Z employees have never known a world without the internet and mobile tech, so flexibility feels normal rather than a perk. They often prefer outcomes over hours, and they respond well to options like hybrid working, remote roles, and working patterns that allow them to protect time for life outside work.

    ND: Flexibility can be just as important for neurodivergent colleagues, although the details may vary by person. Some autistic people may prefer predictable routines while needing adjustments to the workspace, noise levels, lighting, or how meetings are run. People with ADHD may find flexible hours helpful because it lets them work when their concentration is strongest, with breaks planned in a way that supports focus.

    Mental health and wellbeing

    Gen Z: Gen Z tend to be more direct and open about mental health than many previous generations. They often look for employers who take wellbeing seriously in day-to-day practice, not just in policy. Support such as employee assistance programmes, access to counselling, wellbeing resources, and the ability to take time to reset can all matter.

    ND: For neurodivergent people, wellbeing support can be the difference between coping and thriving. Clear signposting to mental health resources, a culture that reduces stigma, and practical adjustments that lower day-to-day stress all help. Reasonable accommodations can also prevent small barriers from turning into burnout.

    Technology and smarter ways of working

    Gen Z: As digital natives, Gen Z typically expect work to be enabled by modern tools. They are comfortable learning new platforms quickly and often enjoy teams that experiment, automate, and improve how work gets done. Up-to-date tech can support productivity, collaboration, and engagement.

    ND: Technology can also remove barriers for neurodivergent employees. Tools such as speech to text, captioning, task management apps, noise reduction options, and structured templates can make work more accessible. The right tech can also reduce friction in communication by making expectations, decisions, and next steps easier to track.

    Inclusion, belonging, and diversity

    Gen Z: For many Gen Z employees, diversity and inclusion are baseline expectations. They want workplaces where people are respected, where different perspectives are welcomed, and where it is safe to speak up. This often includes a broader view of diversity, including lived experience and ways of thinking.

    ND: A strong sense of belonging is especially important for neurodivergent colleagues. People do best when they are understood, when their strengths are recognised, and when they are not penalised for differences in communication or working style. Inclusive practices and fair progression routes help ensure neurodivergent talent is not overlooked.

    Clear communication and useful feedback

    Gen Z: Gen Z often value clarity about priorities, success measures, and what good looks like. Regular, specific feedback helps them learn quickly and feel anchored in their role. When communication is open and consistent, it builds trust and strengthens engagement.

    ND: Many neurodivergent employees benefit from direct, unambiguous communication, especially around expectations and timelines. Written follow-ups, clear agendas, and constructive feedback can reduce uncertainty and make it easier to plan and deliver. Small shifts in how teams communicate can have a big impact on confidence and performance.

    When employers design work around these shared needs, everyone benefits. Flexibility, wellbeing support, practical tech, a culture of inclusion, and clear communication are not niche requests. They are foundations for better work, particularly for Gen Z and neurodivergent people.

    If we keep leaning into these principles, we move towards workplaces that are calmer, more human, and more effective. That is good for individuals, teams, and ultimately the future of work.

    Photo by Anna Shvets on Pexels.com

  • Designing AI for neurodivergent users: inclusion by default

    AI is everywhere right now, and the hype can make it hard to separate what’s genuinely useful from what’s just shiny. I’m excited by the possibilities, but I’m also cautious about the real issues that sit underneath: relevance, ethics, and the energy and data costs of building and running these systems.

    One area that deserves much more attention is talent. AI is already shaping how people apply for roles, how they’re assessed, and how work is tracked and supported once they’re in post. If we get it right, AI could remove friction and widen access. If we get it wrong, it will quietly scale exclusion.

    That’s why I keep coming back to neurodiversity. Neurodivergent people, such as autistic people, and people with ADHD or dyslexia, often process information, communicate, and manage attention differently. Those differences can translate into real workplace strengths (pattern recognition, deep focus, creative problem-solving), but only when the environment is designed to let them show up well.

    The risk: automating yesterday’s definition of “great”

    A lot of AI in hiring works by learning patterns from historic data: who was hired, who was promoted, who performed “well” according to existing measures. That sounds neutral, but it can lock in a narrow idea of competence, especially when the past wasn’t built for different thinking styles. The output may look objective while simply repeating old preferences at speed.

    But AI can also be used to widen the lens. For instance: screening that focuses on demonstrable skills instead of polished CVs; application routes that offer written, audio, or asynchronous options rather than forcing everyone into a single “performative” format; and workplace tools that support planning, prioritisation, and clarity without turning every day into a surveillance exercise.

    When inclusion is designed in from the start, AI becomes a lever: it can reduce avoidable bias, uncover overlooked talent, and make work easier to navigate. The goal isn’t to build a “special” track for neurodivergent people. It’s to build systems that work well for a wider range of humans.

    AI should lower barriers, not turn them into code.

    The opportunity: build with, not for

    The most reliable way to make AI tools neuroinclusive is simple: involve neurodivergent people in shaping them. Not as a late-stage “accessibility review”, but in discovery, prototyping, testing, and measurement. If the system will be used to judge humans, it needs humans with varied cognitive styles at the table.

    In my experience, many neurodivergent people are early adopters of tools that bring structure: clear prompts, predictable workflows, and asynchronous communication. Those features aren’t niche. Most of us benefit from less ambiguity. Designing for neurodivergent users often produces cleaner, more usable products for everyone.

    Doing this early also helps you catch unintended consequences, like assessment formats that punish slower processing speed, or interfaces that create cognitive overload, before they become “just the way the platform works.”

    • Multiple ways to participate (for example: written responses, live conversation, work samples, or asynchronous options)
    • Control over the experience (customisable layouts, captions/transcripts, quiet modes, the ability to pause and return)
    • Measures that prioritise outcomes (quality and impact over performative “activity” signals)
    • Regular bias and accessibility checks (audit inputs, outputs, and who is being screened out, then fix what you find)
    • Transparency people can understand (plain-language explanations of how a decision was reached and how to challenge it)

    These aren’t add-ons. They’re the building blocks of tools that are safer, more human-centred, and more likely to produce decisions you can defend.

    I’m starting to see encouraging signs: some employers offer alternatives to one-way video screening; some teams are experimenting with skills-based assessments and structured interviews that reduce guesswork; and some platforms are investing in personalisation and accessibility features as core product requirements rather than optional extras.

    Vendors matter here too. Tools that allow configuration, provide clear explanations, and make auditing practical will increasingly stand out, not only because it’s ethically important, but because organisations are under growing pressure to prove that their processes are fair.

    So, what now?

    Neurodiversity is not a “problem to solve”. It’s a source of insight and innovation. When AI is designed with a wider range of minds in view, organisations don’t just do the right thing; they make better decisions and access a deeper pool of talent.

    AI isn’t magically unbiased. It reflects the choices we make: what we measure, what we optimise for, and which trade-offs we accept. “Inclusive by default” means you don’t wait for someone to struggle before you redesign the process. You build the process so more people can succeed from day one.

    As AI becomes more embedded in recruitment and everyday work, we have a choice: optimise purely for efficiency, or optimise for humans. If you care about performance and fairness, those two shouldn’t be in conflict.

    To me, this is less about lowering any bar and more about asking whether the bar is measuring the right things. Neurodivergent people are often filtered out by noisy processes, such as unstructured interviews, ambiguous tasks, “culture fit” guesswork, or assessments that reward performance under pressure rather than capability. AI can either reinforce those filters or help dismantle them.

    What “neuroinclusive AI” can look like in practice

    If you’re building or buying AI for hiring or talent management, my challenge is this: ask who it works well for, who it disadvantages, and how you know. Bring neurodivergent voices into the design. Audit what happens in the real world. And treat clarity, choice, and transparency as non-negotiables.

    When we design AI with cognitive diversity in mind, we don’t just support neurodivergent people. We build smarter, more trustworthy systems for everyone.

    Photo by Pavel Danilyuk on Pexels.com