Making Work, Work
Why Structural Design Matters for Inclusive Employment
The UK is entering a period of rising economic inactivity and mounting welfare expenditure. With unemployment at 5.1% and the welfare bill forecast to rise significantly over the coming decade, much of the public debate has focused on participation rates and labour supply. Yet a more fundamental question remains underexamined: is work itself designed to be accessible and sustainable for everyone?
This is not simply a question of numbers. It concerns capable people, particularly older adults and neurodivergent workers, who encounter structural and cultural barriers that prevent them from accessing or sustaining employment, even when they have the skills and motivation to contribute.
Recent reports, including the government’s Keep Britain Working agenda and work from the Age Diversity Forum, recognise elements of this challenge. However, discussions often centre on health, skills and participation metrics, while overlooking deeper structural issues in how opportunities are surfaced, assessed and sustained.
We do not only need to increase employment rates. We need to examine whether the architecture of work itself is fit for a more diverse and ageing workforce.
The Fragmentation Problem
The UK’s job market operates across dozens of platforms, from the Department for Work and Pensions’ Find a Job service to private sites such as Indeed and Reed. There is no single coordinated system ensuring that every vacancy is visible and accessible. Roles may appear briefly, behind paywalls, or only on niche platforms. Smaller employers and social enterprises may not advertise widely. Search algorithms and paid listings influence visibility. National data on inclusion and progression remains inconsistent.
For neurodivergent individuals and many older adults, this fragmentation creates tangible barriers. Opportunities can be difficult to locate and short-lived once advertised. For those who process information differently or require additional time to evaluate fit, this structure disadvantages them before any assessment of capability occurs.
At a time when economic inactivity is rising, avoidable structural barriers should be a policy concern.
Structural Reforms Worth Considering
Three interconnected reforms could address these systemic challenges.
1. A National Vacancy Register
This would not be another job board, but a structural reform requiring all employers, public and private, to list vacancies within a single transparent system. Such a register would:
· Present opportunities equitably, without distortion by advertising budgets or algorithmic ranking
· Connect to regional support networks, training programmes and mentoring schemes
· Generate national data on inclusion, progression and retention
The principle is straightforward: equal visibility should precede equal opportunity.
2. The “NeuroAgent” Model
Visibility alone does not guarantee inclusion. Many neurodivergent and older individuals benefit from contextualised support.
A NeuroAgent would act as an intermediary between candidate and employer, helping to:
· Match individuals to roles aligned with their skills, preferences and sensory needs
· Support disclosure and reasonable adjustments
· Advise employers on inclusive recruitment and retention
Rather than viewing inclusion as an individual burden, this model treats it as a shared process supported by informed mediation.
3. Paid Work Trials
Many pathways into employment rely on unpaid work experience or voluntary placements. While well-intentioned, these models exclude individuals who cannot afford extended periods without income.
Paid work trials would allow candidates to demonstrate competence within real working environments, reduce interview bias, and provide employers with practical evidence of fit. Most importantly, they would maintain dignity by valuing contribution from the outset.
The Role of Artificial Intelligence
As employment services increasingly integrate AI to improve administrative efficiency, careful design becomes essential.
Emerging evidence from the United States and Europe suggests that AI hiring systems can disadvantage older workers and neurodivergent candidates when trained on historical data reflecting past exclusion. For example, research from the University of Washington (2024) demonstrated bias in AI-generated resume rankings involving autism-related indicators. Regulatory responses, including aspects of the EU AI Act, signal growing recognition of these risks.
AI can improve access and matching at scale. However, it cannot reliably assess contextual factors such as non-linear career progression, sensory fit, or resilience demonstrated through atypical pathways. Without human oversight, efficiency gains may unintentionally replicate existing structural inequalities.
This is where intermediary models such as the NeuroAgent become relevant. Human judgment can interpret context, recognise atypical strengths, and prevent algorithmic outputs from becoming definitive gatekeepers.
The aim is not to resist technological innovation, but to embed human accountability within it.
Cultural and Institutional Change
Infrastructure alone is insufficient. Broader changes in recruitment and retention practice are also required:
· Diversifying assessment methods beyond conventional interviews
· Designing flexible roles focused on outcomes rather than rigid career narratives
· Involving neurodivergent individuals directly in policy and recruitment design
· Ensuring ongoing support rather than treating inclusion as a one-off adjustment
Inclusion is not achieved at the point of hire. It is sustained through design.
Why This Matters
The UK faces significant demographic and economic transitions. As the population ages and technological change accelerates, workforce sustainability depends on retaining and enabling diverse talent.
Expanding participation is necessary, but participation alone is not sufficient. Structural visibility, contextual support, fair assessment mechanisms and responsible technological integration are equally important.
The capability to contribute exists. The institutional tools to support it are emerging. The challenge is whether policy design will align systems with that capability, before inefficiencies become further embedded.
Making work, work requires deliberate architecture, not aspiration alone.