AI-ding the technicians of tomorrow

5 June 2026  

The automotive aftermarket is one of the few sectors that doesn’t appear to be facing an imminent takeover brought about by the advent of artificial intelligence (AI). It’s hard to consider a future where AI is replacing brakes discs on a customer’s vehicle, performing an oil and filter service or replacing a timing belt. These are skills that require the experience, skills and careful handling of a qualified technician. But there are other uses for the technology that can positively impact an independent garage. Oscar Diaz, CEO of TOPDON Europe, introduces one.

The UK aftermarket has long relied on apprenticeships, structured training, and hands-on workshop experience to develop skilled automotive technicians. But workshops today are operating in a fundamentally different environment, one defined by tighter margins, rapidly evolving vehicle technologies, and diagnostic processes that demand engagement with ever-growing volumes of technical data.

The pressure is already showing. According to ManpowerGroup’s 2026 Talent Shortage Survey, 92% of UK automotive employers report being unable to find the skilled talent they need ­– nearly 20 percentage points above the national average. The IMI puts current motor trade vacancies at around 13,000, with just 24% of the existing technician workforce qualified to work on electric vehicles, and fewer than 3,000 trained in ADAS calibration against a projected industry need of 106,000 within seven years.

So where do you go for skills when they simply don’t exist? Increasingly, independent workshops are turning towards AI tools. Rather than waiting for a qualified technician to become available – or investing months in training that may not keep pace with the vehicles already on the ramp – workshops are exploring technology that can surface diagnostic guidance, interpret technical data, and support decision-making in real time. It’s a pragmatic response to a structural problem: not a replacement for expertise, but a way of extending the capability that already exists on the workshop floor.

Imagine life with an AI assistant

TopFix AI, an artificial intelligence assistant built into TOPDON’s diagnostic platform, is one example of how AI can support the technician role. Rather than requiring technicians to manually search through technical databases, it analyses vehicle type and detected fault data, cross-referencing official technical service bulletins (TSBs) from the relevant manufacturer to surface the most likely causes quickly. Trained on real diagnostic cases and OEM data, it guides technicians through fault resolution processes that would traditionally demand years of accumulated experience.

Crucially, TopFix AI doesn’t make diagnostic decisions. The technician remains in control throughout. Instead, the tool acts as an informed assistant, compressing the time it takes to reach the right information rather than bypassing the judgement needed to act on it.

For experienced technicians, the value of AI tools like this is straightforward: less time spent hunting through documentation means more time on the job itself. In a workshop running multiple bays simultaneously, that efficiency quickly adds up. But the more significant shift may be what TopFix AI represents for less experienced staff – the ability to access OEM-backed guidance in the middle of a live diagnostic situation, learning by doing rather than waiting for formal training to catch up with the vehicles already on their ramp.

The importance of retention

The industry talks a lot about a skills shortage, but this challenge is not uniform across the sector. Workshops aren’t simply short of technicians; they’re short of technicians with the right capabilities for the vehicles they’re increasingly being asked to service. An older, experienced hand may be deeply competent on internal combustion engines but hesitant around ADAS or hybrid systems. A newer recruit may have theoretical EV knowledge but limited diagnostic exposure. Tools that can bridge those specific gaps, in real time, address an immediate issue.

There is also a retention dimension worth considering. One of the less-discussed consequences of the skills shortage is the pressure it places on the technicians who do have the right capabilities. When complex jobs can only be handled by one or two people in a workshop, those individuals carry a disproportionate burden – and more often than not, eventually vote with their feet. Distributing diagnostic knowledge more evenly across a team doesn’t just improve throughput; it reduces the dependency that makes skilled technicians feel indispensable and overloaded in equal measure.

The broader trend here is one of integration rather than automation. The aftermarket has at times been wary of technology that appears to threaten the craft element of workshop work – and not without reason. Diagnostic tools that override technician judgement, or that generate plausible-sounding guidance without reliable sourcing, can introduce as many problems as they solve. The distinction with tools grounded in OEM technical data is meaningful: the information being presented is the same information a manufacturer would want a technician to consult, just delivered faster.

The pipeline problem

What AI doesn’t solve – and shouldn’t be expected to – is the pipeline problem. The aftermarket still needs more people entering the trade, more apprenticeships completing, and a more compelling story to tell young people about what a career in automotive actually looks like in 2026. Technology can extend the capability of the workforce that exists; it cannot manufacture one. Industry bodies, training providers, and workshops themselves all have a role to play in making that case more loudly.

TOPDON, like many businesses, is doing work here too. We’re partnered with several schools across Europe where we supply our technology to students looking to learn a technician craft. We hope to one day extend this across the UK and the rest of Europe.

Why? The baseline expectation of what a workshop should look like is evolving. A business that invested in good diagnostic equipment five years ago was considered well-equipped. Increasingly, the question is whether that equipment is intelligent; whether it can help the people using it work at the edge of their knowledge, not just within it. For independent workshops navigating a skills shortage they didn’t create and can’t quickly resolve, that may be the most practical definition of progress available to them right now.

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