Older equipment does not fail politely. It drifts, then it breaks, and unplanned downtime costs money and orders. That is why so many plants now want people who can spot trouble in the data before a machine stops. The pressure is real: six in ten (59%) manufacturers cited automation and half (50%) cited wider digitalisation as trends changing jobs and skills needs in Make UK's 2030 Skills report.
The skills gap behind this shift is wide. There were 55,000 unfilled long-term vacancies in UK manufacturing in 2025, costing the economy £6bn in lost output every year according to Make UK's Industrial Strategy Skills Commission Report 2025. When ageing kit needs constant attention and the people who understand it are hard to find, small teams get stretched thin.
It also holds back the very technology that makes predictive maintenance possible. Over 50% of manufacturers cite skills shortages as the main barrier to AI adoption, and only 2% say AI is widely embedded across their operations reports The Manufacturer, drawing on Make UK research. The tools exist. The people to run them are the constraint.
Predictive maintenance is a blend of hands-on engineering and data literacy. Think maintenance technicians who read vibration and thermal data, reliability engineers who set condition monitoring thresholds, and controls specialists who keep sensors and older PLCs talking to newer systems. The demand for these cognitive skills is climbing: 74% of manufacturers expect demand for cognitive and meta-cognitive skills to increase by 2030 in Make UK's 2030 Skills report.
These are exactly the roles employers find hardest to fill. 76% of engineering employers struggle to recruit for key roles, with technical and specialist skills topping the list the Institution of Engineering and Technology found in 2025. And it is not just recruitment: manufacturers name skills shortages (75%), recruitment (36%) and talent retention (32%) as their top barriers to growth Barclays Corporate reported in 2024.
Many firms are also building these skills from within. 40% of manufacturers are looking to upskill their existing workforce, specifically for redeployment as a result of automation and digitalisation, a figure that rises for firms with more than 1,000 employees according to the Make UK Executive Survey 2026. Hiring and upskilling work best together: bring in the specialist knowledge, then spread it across the team.
Start with the machines you actually run. Someone who has kept 30-year-old presses or legacy conveyors alive is often worth more than someone who only knows brand-new lines. Write the job around your real estate: the kit, the sensors, the control systems and the failure modes you see most.
Then hire for the mix. You want engineering instinct and comfort with data. Ask people to talk through a real fault they caught early, what the data showed and what they did next. That tells you more than a certificate. With 76% of engineering employers struggling to recruit for key roles per the IET's 2025 figures, move quickly once you find the right person, because good ones do not stay on the market long.
Finally, plan for retention. Since talent retention is a top-three barrier for 32% of manufacturers as Barclays Corporate reported in 2024, set out a clear path: training on your systems, room to grow into reliability engineering, and a say in which technology you adopt next.
When your line depends on ageing kit, you cannot wait weeks for a shortlist. We search 15 million candidates to find people with the maintenance and condition-monitoring skills you need, then handle the process end to end. Our recruitment agent manages recruitment end to end for 8% on a successful hire, with no monthly fee and no upfront cost. Tell Reed.ai what your plant runs and what good looks like, and we will start today.
