Ford Rehires Its Engineers After AI Falls Short on Vehicle Quality

Ford has rehired hundreds of experienced engineers after concluding that artificial intelligence alone could not deliver the level of quality required in vehicle production.

The automaker said it has brought back more than 300 veteran quality engineers in recent years after discovering that its AI-powered inspection systems lacked the practical knowledge needed to identify manufacturing defects as effectively as experienced employees. The decision follows several years of investment in artificial intelligence as Ford sought to improve manufacturing efficiency, reduce costs and strengthen quality control across its production facilities.

Charles Poon, Ford’s Vice President of Vehicle Hardware Engineering, said the company underestimated the value of institutional knowledge built over decades of vehicle development.

“Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it,” Poon told reporters.

He said Ford had not done enough to preserve the expertise of its most experienced engineers as many left the company.

“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.

AI Still Needs Human Expertise

Ford has been among the major manufacturers integrating artificial intelligence into production processes.

Last year, Chief Operating Officer Kumar Galhotra said the company had deployed AI across its manufacturing operations, including around 900 AI-powered cameras designed to identify quality issues early and reduce supply chain disruptions.

However, Poon said the technology did not produce the expected results when it relied only on engineering specifications and historical design data.

“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.

According to Poon, the systems lacked the practical judgement developed by engineers who had spent years working across multiple vehicle programmes. Ford has since brought many of those specialists back to help train its AI models while also mentoring younger engineers.

“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.

Quality Improvements Follow Workforce Changes

Ford’s comments came as the company regained the top position among mainstream vehicle manufacturers in the JD Power Initial Quality Study, an industry benchmark measuring vehicle quality during the first months of ownership. It is the first time Ford has topped the ranking since 2010.

In announcing the achievement, Ford said improving vehicle quality required significant organisational changes. Alongside appointing new leaders across engineering, manufacturing and supply chain operations, the company credited the return of hundreds of experienced engineers whose technical knowledge has helped strengthen both product development and quality assurance.