Ford Calls Back Its 'Gray Beards' After Betting Too Much on AI

American automaker Ford is reportedly turning to former engineers once again as it works to lift product quality, after its reliance on artificial intelligence-based and automated quality systems did not deliver the expected results.

According to a Bloomberg report, over the past three years, the company has brought back around 350 experienced engineers, including ex-employees and specialists from supplier firms, to strengthen quality standards and help bring down costs.

Automation Overreach Concerns

Ford executives admitted that the company leaned too heavily on automated quality systems and undervalued decades of engineering expertise. This approach led to results that fell short of expectations.

Ford chief operating officer Kumar Galhotra told Bloomberg that growing dependence on automation had delivered disappointing outcomes. He said experienced engineers help identify potential failure points before components reach the production stage.

Galhotra added that these specialists now lead mandatory quality reviews, helping the company shift from fixing issues after they arise to preventing them during development.

AI Overestimation & Quality Gaps

According to Ford’s vice-president of vehicle hardware engineering Charles Poon, the company overestimated artificial intelligence capabilities. He added that while AI remains a useful tool, its effectiveness depends on the quality of data used to train it.

Poon noted that Ford had not preserved the knowledge of experienced engineers before many left, which limited AI systems’ ability to detect issues early in development.

To address this, Ford has rehired more than 350 veteran engineers, known internally as “gray beard” engineers. These specialists mentor younger employees, assist in retraining AI tools and identify quality problems before they reach production.

Meanwhile, Ford chief operating officer Kumar Galhotra said these veteran engineers are central to the company’s turnaround strategy. They lead mandatory quality reviews and help shift the focus from fixing problems after they occur to preventing them beforehand. He said, “We’re moving from that find-and-fix mentality to preventing issues before they occur.”

Ford’s improvements now extend beyond hardware to include software, manufacturing and supply-chain teams, which are working more closely to identify issues earlier. The company has also set up a 40-member software quality assurance team to improve software reliability before vehicles reach customers.

The automaker is not moving away from AI but is improving its effectiveness by using better data from experienced engineers. It has also added over 100,000 AI-powered validation tests to detect edge cases and stress-test vehicle software under different conditions.