Ford rehires human engineers after AI fails to match quality checks

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Ford says it has hired back some human engineers after AI failed to match their skills and experience.

In a bid to reap the benefits of the tech, which developers claim can cut costs and boost productivity, the US carmaker adopted it across some parts of its operations including for quality checks.

But, according to Bloomberg , external , its executives said the firm has rehired more than 300 "veteran" quality inspectors in recent years to make up for the pitfalls of automated systems.

"Artificial intelligence is a fantastic tool, but it's only as good as the information you use to train it," Charles Poon, vice president of vehicle hardware engineering, told reporters.

"Over prior years, we didn't pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles," he said.

The US automaker is among many to have seized on the buzz around AI, particularly amid Wall Street fervour about the tech's potential to increase margins.

"AI will leave a lot of white collar people behind," Ford boss Jim Farley said in an interview with author Walter Isaacson last June.

In an October earnings call , external , chief operating officer Kumar Galhotra said the firm was "deploying AI across the entire industrial system".

This included rolling out 900 AI-powered cameras in its plants "to detect quality issues at the source and help us mitigate supply disruptions", Galhotra told investors.

But Poon told reporters on Wednesday the firm's AI-driven checks had failed to live up to expectations.

"Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product," he said.

Poon reportedly pointed to automated tools lacking the training and expertise of veteran technicians - many of whom he said had left the company before their knowledge could be used to improve its tech.

He said these human workers had since been reintroduced to train up its systems, as well as mentor younger workers.

"We recognised that for us to enhance some of our automation and machine learning and artificial intelligence tools we needed to ensure that they were trained by the most experienced individuals," he said, per Bloomberg.