Ford Motor Company has taken the unusual step of rehiring hundreds of former engineers to correct errors introduced by its automated production and design systems. The move comes as Ford celebrates its new No. 1 ranking in JD Power's initial quality survey among mainstream automakers, but executives acknowledge that the path to that achievement required a hard look at the limitations of artificial intelligence.
Automated Systems Fall Short
Ford’s reliance on automated systems in manufacturing and design proved less robust than expected. According to Charles Poon, Ford’s vice president of vehicle hardware engineering, the company mistakenly believed that introducing AI and adjusting design requirements would automatically yield high-quality vehicles. “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,” Poon said in a briefing with reporters.
The automaker underestimated the value of institutional knowledge held by veteran engineers who had worked through multiple vehicle-development cycles. Many of these experienced personnel left before their expertise could be fully transferred into automated systems. To address the resulting quality decline, Ford hired, promoted, or brought back over 350 experienced engineers to rebuild that layer of expertise.
Rehiring and Retraining
These seasoned engineers are tasked with retraining automated systems and mentoring younger engineers struggling to maintain vehicle quality. They also work on improving data collection and AI training processes. “That’s where some of our most experienced engineers have had experience solving and identifying those problems before they creep into the system,” Poon explained.
Ford currently leads the industry in the number of recalls, and its quality ratings have slipped over the past several years. Challenges were exacerbated by difficulties launching the Ford Explorer and Lincoln Aviator, supply-chain disruptions during the COVID-19 pandemic, and a growing number of recalls.
From Find-and-Fix to Prevention
Ford’s chief operating officer, Kumar Galhotra, said the company concluded that its quality approach had become too fragmented. Departments operated in silos, relying on a “find and fix” philosophy that addressed defects after they appeared but did not prevent them. “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 transformation extends beyond hardware. Software and digital teams now work closely with vehicle engineering, manufacturing, and supply-chain teams. Ford aims to combine the speed of software development with the rigor of automotive-grade engineering. Historically, software bugs were discovered late in the process because Ford did not fully leverage rapid iteration cycles, Poon noted. However, vehicles cannot be updated with the same speed as consumer electronics due to safety-critical requirements.
New Quality Assurance Measures
To improve software reliability, Ford created a dedicated 40-person software quality assurance team focused on preventing problems before they occur. The automaker has also expanded automated testing capabilities, adding more than 100,000 new AI-powered tests designed to identify edge cases and stress software systems under various conditions. “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 disciplines with strict metrics.”
Despite these challenges, Ford remains committed to integrating AI into more processes, but with a renewed emphasis on human expertise and data quality.
