Ford Rehires ‘Gray Beard’ Engineers After AI Falls Short in Quality Push

Ford Motor Company has rehired and reintroduced around 350 veteran engineers over the past three years after its artificial intelligence and automated quality systems failed to deliver expected improvements in vehicle quality, according to multiple international reports, including Bloomberg-based coverage.

The engineers, internally referred to as “gray beard” specialists , include former Ford employees and experts from supplier firms. The automaker had initially relied heavily on AI-driven inspection and automated quality tools to improve design and manufacturing outcomes, but executives later admitted that the systems lacked the institutional engineering knowledge required to detect complex, real-world failures.

Ford vice-president of vehicle hardware engineering Charles Poon acknowledged that the company overestimated AI’s standalone capabilities, stating that it mistakenly believed that feeding design requirements into AI would automatically produce high-quality products. He also noted that AI remains effective only when trained with strong, experience-based engineering data .

Chief operating officer Kumar Galhotra said the company had been increasingly dependent on automation without achieving desired results, prompting a structural shift toward prevention-based quality management . The returning engineers are now mentoring younger staff, leading mandatory quality reviews, and helping retrain AI systems to better identify defects before production.

Recent industry reports indicate that this hybrid strategy has contributed to Ford’s improvement in JD Power Initial Quality Survey rankings , where it recently emerged as a leading mainstream brand after years of weaker performance. However, the company still faces challenges, including a high recall rate linked largely to older models , highlighting ongoing systemic issues in its product lifecycle management.

Alongside human reintegration, Ford is expanding its AI infrastructure with more than 100,000 validation tests aimed at detecting edge cases in software and manufacturing processes. The company is also strengthening cross-functional coordination between engineering, software, and supply-chain teams, along with a dedicated software quality assurance unit .