Ford rehires former engineers to fix automated system errors

Ford is pulling back the curtain on its quality struggles, and the story involves a surprising twist: the automaker is bringing back veteran engineers to fix problems caused by its own automated systems. After claiming the top spot in JD Power’s initial quality ranking among mainstream automakers, Ford has revealed that its reliance on AI-driven production and design was not as foolproof as once believed.

The company acknowledges that artificial intelligence is powerful but deeply dependent on the quality of data used to train it. Ford also underestimated the value of institutional knowledge held by experienced engineers who had navigated multiple vehicle-development cycles. The result was a noticeable dip in vehicle quality. “Mistakenly, we thought that by just introducing artificial intelligence and adjusting the design requirements that we had, that that would produce a high-quality product,” said Charles Poon, Ford’s VP of vehicle hardware engineering, during a media briefing.

According to Poon, many of Ford’s most seasoned employees departed before their expertise could be fully captured by the company’s automated systems. That forced Ford to rehire some of those engineers to retrain the systems and mentor younger staff struggling to maintain quality standards. In total, Ford has hired, promoted, or brought back more than 350 experienced engineers to rebuild that critical layer of expertise. Their mission includes improving data collection and AI training while guiding the next generation of engineers.

“That’s where some of our most experienced engineers have had experience solving and identifying those problems before they creep into the system,” Poon said.

Ford currently leads the industry in recalls, and its quality ratings have declined over the past several years. Challenges were compounded by difficulties during the launches of the Explorer and Aviator, supply-chain disruptions during the pandemic, and a rising number of vehicle recalls. COO Kumar Galhotra explained that the company eventually recognized its quality approach had become too fragmented. Different departments operated in silos, and Ford relied heavily on a “find and fix” mentality that addressed defects only after they appeared.

“We’re moving from that find-and-fix mentality to preventing issues before they occur,” Galhotra said. “We’re focused on enablers and early indicators versus outputs. Stop admiring the problem and start solving it.”

The shift extends beyond hardware. Ford’s software and digital teams now collaborate more closely with vehicle engineering, manufacturing, and supply-chain groups. The automaker is trying to merge the speed and flexibility of software development with the rigorous validation required for automotive-grade engineering. In the past, Ford often discovered software bugs late in the process because it wasn’t fully using rapid iteration cycles. However, Poon noted that Ford could not push updates as quickly as consumer electronics companies, because vehicles operate in safety-critical environments where software must work correctly from delivery.

To address this, Ford created a dedicated 40-person software quality assurance team focused solely on preventing problems before they occur. At the same time, the automaker has dramatically expanded its automated testing capabilities, adding more than 100,000 new AI-powered tests designed to identify edge cases and stress software under a wide range of conditions. Because the testing framework is highly automated, software changes can be rapidly revalidated even late in development.

“Because these tests are highly automated, even if we have a late change in the software, we can rapidly run back through the entire validation process to guarantee it works perfectly well before it reaches the customer,” Poon said. “We’ve established software reliability as its own rigorous discipline with strict metrics.”