Computer, Automated Teller, and Office Machine Repairers

Today’s repair techs already use smart tools for some tasks. For example, many ATMs and office machines have self-check software and sensors that can report errors to service teams ^[1]. Companies even use wireless sensors and AI-driven diagnostics so tech staff can spot wear early – one industry guide notes this can cut service costs by about 30% ^[2].

In practice, this means things like logging repairs on a computer or running remote software updates are often automated. However, most hands-on work remains human. O*NET notes this job is only “moderately automated” (about 42%) ^[3], meaning tasks like physically replacing gears, soldering circuits, or oiling parts still need skilled people.

In short, AI and software help with checks and data, but actual repair and troubleshooting often still rely on a person’s touch and experience.

Businesses weigh the costs and benefits of new AI tools. On one hand, there’s pressure to adopt helpful tech because many veteran technicians are retiring ^[4]. Firms are using AI-powered simulators and training apps to pass knowledge to younger workers ^[4].

Banks and companies also gain money by keeping machines running. For example, an analysis warns that fewer bank branches make working ATMs critical for revenue ^[1], so firms invest in “predictive maintenance” AI that can prevent breakdowns. If AI can catch a fault early, companies save on emergency repairs and downtime ^{[2] [2]}.

On the other hand, high-tech tools cost money and need data and rules to work, so small workshops may wait before buying them. And because dealing with cash machines or customers often requires a human touch and trust, many expect people – not robots – to handle critical fixes.