/Tech6h ago

Ford rehired 350 engineers after automated AI systems caused recalls, subsequently hitting a 20-year quality high

Automated systems struggled to resolve complex manufacturing edge cases.

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Rohan Paul@rohanpaul_ai#1257inTech

Ford’s AI push hit a hard limit: factories still need human failure memory.

They hiring back 350 specialists to catch failures machines missed.

Ford leaned on automated inspection to find defects faster, but car manufacturing is full of edge cases where tiny design, material, supplier, and assembly changes interact in ways rules-based systems and trained models can miss.

The missing ingredient was tacit engineering knowledge, the hard-earned pattern memory built from many product cycles, failed parts, supplier mistakes.

Ford’s rehired “gray beards” now review designs before parts reach the plant floor, while also helping improve the training data behind the AI systems.

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independent. co .uk/tech/ford-ai-automation-human-workers-b3003787.html

2:21 PM · Jun 27, 2026 · 4.2K Views

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Users criticized Ford for replacing engineers with an unreliable AI inspection system that missed defects, arguing CEOs misunderstand AI and such moves cause production failures.

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Gary Marcus@GaryMarcus

Another case of what I call The Klarna Effect.

Hedgie@HedgieMarkets

🦔Ford admitted it had to rehire engineers after replacing them with AI systems that couldn't do the job. The company's VP of hardware engineering said they mistakenly believed AI and adjusted design requirements would produce a high-quality product. Ford has cut over 5,000 workers since 2020 and recalled more cars than any other US automaker this year. The company rehired, newly hired, or promoted 350 experienced engineers to fix the damage. CEO Jim Farley has said AI will replace half of all white-collar workers in the US.

My Take Ford fired the engineers, the quality collapsed, and then Ford called the engineers back to fix what broke and train the AI that was supposed to replace them. The VP framed this as a lesson learned. I'd call it something else. Ford planned to use its own employees to build the system that would make them obsolete. The employees left before that could happen.

Ford now has the top spot in JD Power's quality ranking for the first time in nearly 20 years, but only after it brought the humans back. The company's response to the whole episode is to add 100,000 more AI-powered tests. Farley still says AI will replace half of white-collar workers. Ford just proved it can't replace 350 engineers without the product falling apart, and the CEO's position hasn't changed. That's the part I can't get past.

Hedgie🤗

3h13.8K17129

Gold Royalty@GoldRoyalty1

@GaryMarcus I call it the "Jim Farley doesn't know what the F*ck he's talking about" Effect. But he sure likes to hear his own voice or quotes of himself in national media.

3h5

Ali Khan@alikhan_biz

@rohanpaul_ai Tacit knowledge doesn't transfer to a model by accident. You have to deliberately capture it first. Ford learned that the expensive way.

5h13

Fabius Maximus (Ed.)@FabiusMaximus01

@GaryMarcus For those interested in “The Klarna Effect”, see this post by @GaryMarcus :

https://garymarcus.substack.com/p/ai-layoffs-productivity-and-the-klarna

3h12

Jack Huang@photonjaeger

@rohanpaul_ai @cherylwoooo

4h5

Gold Royalty@GoldRoyalty1

@GaryMarcus Never trust a CEO's view on AI.

NEVER.

They know nothing about normal functions and AI's ability to assist or replace them.

3h3

Ferbin@Ferbin08

@GaryMarcus replacing people who understand the system with APIs that don't. costs drop until something breaks in production.

3h3

Nathan Quantum@AI_WarriorNQ

@rohanpaul_ai the rehired specialists are also expected to improve the AI training data. capturing their own tacit knowledge so Ford can try automating them away next time.

6h1