Ford rehires 350 engineers as AI quality efforts fall short

Ford has hired 350 veteran engineers to address vehicle quality issues, representing a strategic shift after the automaker acknowledged that artificial intelligence and automated systems failed to deliver the desired quality level. The hiring decision follows a period where the company attempted to automate much of its quality control. Some of these newly hired engineers are former Ford employees, while others had been working at various suppliers. According to Kumar Galhotra, Ford’s chief operating officer, the company had been relying more and more on automated quality systems, but the results did not meet expectations. In response, the automaker brought back these technical specialists to identify and resolve engineering issues early in the production cycle.

Charles Poon, Ford’s vice president of vehicle hardware engineering, openly acknowledged the company’s over-reliance on automation. Poon stated, “Mistakenly we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that that would produce a high-quality product.”

Despite the setback, Ford is not abandoning its AI plans entirely. Instead, the company is deploying these rehired employees—colloquially referred to as gray beard engineers, a term used to describe highly experienced, veteran engineers—to train younger staff and reprogram automated tools. These specialists are tasked with hunting for failure points before any vehicle part ever reaches the plant floor, ensuring that automated systems are better calibrated to detect defects. By combining human expertise with automated systems, the company hopes to build a more robust quality control framework.

This strategic adjustment is already yielding significant financial and operational benefits. Ford CEO Jim Farley noted that the initiative is reducing warranty and recall costs, contributing to literally hundreds and hundreds of millions of dollars of a tailwind for the company on cost. In financial terms, a tailwind refers to a factor that helps improve performance or reduce costs. Alongside these savings, the automaker secured the top spot among mainstream brands in the JD Power Initial Quality Survey released this week, an industry benchmark used to measure vehicle quality.

Why it matters

This move highlights a critical correction in the automotive industry: the realization that AI cannot fully replace human expertise in complex manufacturing, signaling a shift toward a hybrid approach to quality control.