Tech
The grey door: Solving the UK’s self-inflicted skills shortage | Computer Weekly
The UK’s technology sector has had, and continues to have, a significant demographic challenge. As the nation grapples with an ageing population, the UK government has responded with fiscal policies designed to extend the working lives of its citizens, predominantly through the incremental raising of the state pension age.
Simultaneously, the IT sector, the vanguard of the modern British economy, continues to operate within a cultural and structural framework that systematically marginalises older professionals.
The premise of the current UK economic strategy is built on the assumption of “fuller working lives”. With the state pension age having risen to 66 and legislated to reach 67 between 2026 and 2028, the expectation is that workers will remain economically productive well into their late 60s.
For many sectors, this transition, while challenging, is operationally feasible. However, in the technology sector, a “grey door” appears to descend significantly earlier, often as early as age 50, creating a demographic anomaly where the industry most vital to the UK’s future is the least representative of its present population demographic.
The most definitive metric of ageism is the representation gap – the difference between the proportion of older workers in the general economy versus their proportion in the IT sector. According to the BCS diversity report 2024: “There were 446,000 IT specialists in the UK aged 50 and above during 2023, and at 22%, the level of representation for this group was much lower than that recorded amongst the wider workforce (i.e. 30%).”
The report adds: “If the level of representation for older workers in IT specialist positions was equal to that amongst the working-age population as a whole, there would have been 594,000 older IT specialists in the UK during 2023, i.e. approximately 148,000 more than the number recorded.”
This shortfall represents a significant loss of experience, leadership and technical capability, which is particularly ironic in a sector chronically complaining of skills shortages. Beyond the operational strain of the skills shortage, the structural exclusion of 148,000 experienced professionals represents a critical public policy failure, stripping the UK economy of an estimated £1.6bn in lost tax revenue and directly undermining the government’s fiscal agenda for “fuller working lives”.
According to a survey conducted by CW Jobs, “Over a third (41%) of IT and tech sector workers said they have encountered age discrimination in the workplace, whereas only 27% across other UK industries had experienced old ageism.”
The Stop the bias report 2024 from Tribepad shows similar trends.
The presented trend lines offer little comfort. Despite broader societal trends towards longer careers, the level of representation for older workers in IT roles has remained stagnant over the past five years. While the general employment rate for the “50 to 64” demographic has historically trended upward, the IT sector appears resistant to this shift, maintaining a younger demographic profile as the pool of available young talent shrinks relative to the ageing population.
To resolve the conflict between an ageing demographic and a youth-centric technology sector, stakeholders must move beyond passive acknowledgement of the “grey door” to enact structural reform. When artificial intelligence (AI) tools inadvertently assert human bias, such as ageism, it threatens to turn the government’s “fuller working lives” policy into a driver of inequality.
To prevent the IT sector from becoming a closed shop to the over-50s, the following three recommendations are essential.
1. Mandate algorithmic auditing and glass box transparency
Organisations must treat AI recruitment tools as high-risk systems requiring rigorous safety checks. Companies should implement regular algorithmic audits using counterfactual testing, running identical CVs with different age markers to detect bias.
Furthermore, employers should demand transparency from software vendors regarding how their models handle proxy variables such as formatting and vocabulary, ensuring that years of experience are considered an asset rather than a liability.
2. Institutionalise and scale returnerships
While government initiatives like “returnerships” and “skills bootcamps” provide a framework, the industry must lead the execution. Tech companies should formalise corporate returner programmes as a standard recruitment channel, distinct from entry-level intakes.
These programmes should be designed to bridge the confidence and technical gaps for experienced professionals returning from career breaks, validating their transferable skills rather than forcing them to compete directly with graduates for junior roles.
3. Shift from culture fit to skills-based
The nebulous concept of “culture fit” often serves as a smokescreen for affinity bias, allowing hiring managers to reject older workers who don’t match the prevailing demographic.
Recruitment strategies must pivot to a skills-first taxonomy, where candidates are evaluated strictly on their competencies and potential contribution, rather than social similarity. This requires training human recruiters to recognise and override automation bias, ensuring they do not simply rubber-stamp the rejection of older candidates suggested by flawed AI models.
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Fouch knew automated sensors could help by, for example, identifying the environmental culprits of the hole-punching issues, but with so many potential options to try he didn’t know where to start. “The worst thing you can do, in a smaller business especially, is muddle through pilot purgatory, hoping to find a viable product,” he says. “When someone else has done it before, they know the viable path, and they can save you the time and the expense.”
That’s just what three directors and managers from Apple’s engineering and operations teams offered when Fouch and Quinn Shanahan, who oversees Polygon’s medical device production and special products, visited the manufacturing academy in October and November, respectively. Over what Fouch estimates was five hours, the Apple employees evaluated Polygon’s challenges and applied the industrial engineering equation of Little’s Law—which can identify capacity bottlenecks—to devise solutions.
The result was a detailed strategy mapping out sensors and software that could affordably track production and alert about anomalies. Polygon can now count the number of passes the tube makes through the grinder, and it will soon be able to understand whether an overheated motor or other factors could explain the botched hole punching, Shanahan says.
If all goes as planned, Polygon will have implemented a working system to address its most significant bottlenecks for no more than $50,000 compared to the $500,000 that an automation consultancy may have charged, according to Fouch. The Apple team is working on visiting Polygon to talk through other upgrades. “They have walked these paths before,” Fouch says. “Without their help, it’s going to take us much longer.”
Apple’s Herrera says giving small manufacturers a sense of the benefits of automation and other technologies could eventually lead them to work with consultants and invest in more expensive systems.
Two other academy participants tell WIRED that they have not received extensive assistance from Apple—Herrera says it comes down to which companies have prepared a “problem statement” that Apple can help with—but they are working to bring what they learned to their factories. Jack Kosloski, a project engineer at Blue Lake, a plastic-free packaging startup, says it was eye-opening for him to hear about the depth of Apple’s product testing.
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