Ford Motor Company has brought back approximately 350 experienced engineers and quality specialists over the past three years after its increased reliance on artificial intelligence and automated systems failed to deliver the expected results in vehicle quality control.
The move, which included rehiring some former employees and hiring or promoting others from supplier companies, has contributed to Ford achieving the top ranking among mainstream automakers in the 2026 J.D. Power U.S. Initial Quality Study, the company’s first time leading that category since 2010.
The Limits of Automation in Complex Manufacturing
Ford had leaned more heavily on automated quality systems and AI tools, including deployments such as AI-powered cameras in plants, in an effort to improve efficiency and reduce costs. Executives later acknowledged that these systems could not fully replicate the nuanced judgment and deep product-cycle knowledge of veteran engineers.
Charles Poon, Ford’s vice president of vehicle hardware engineering, stated: “Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product.”
He added: “Over prior years, we didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles.”
Poon also noted: “Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it.”
Chief Operating Officer Kumar Galhotra described the decision to bring back technical specialists who could “hunt for failure points before a part ever reaches the plant floor.”
The returning engineers, sometimes referred to internally as “gray beard” experts, are now mentoring younger staff, leading troubleshooting efforts, and helping refine the company’s AI and machine-learning tools with better training data drawn from decades of hands-on experience.
Quality Turnaround and Business Impact
The renewed emphasis on combining human expertise with technology has produced measurable gains. Ford climbed from the mid-teens in mainstream brand rankings in recent years to No. 1 in the 2026 J.D. Power Initial Quality Study, with a score of 152 problems per 100 vehicles.
Company leadership has linked the quality improvements to reduced warranty and recall costs, describing the financial benefit as a tailwind worth hundreds of millions of dollars.
Ford has made clear it is not abandoning AI. Instead, executives say the company is taking a more integrated approach in which experienced engineers strengthen the data and processes that power automated systems.
Relevance to Ohio’s Manufacturing Economy
The story carries direct interest for readers across south and south central Ohio, where automotive manufacturing and its supply chain remain vital to local economies. Ford operates the Ohio Assembly Plant in Avon Lake, and numerous suppliers and related employers support the broader industry throughout the region.
Developments that affect quality standards, production efficiency, and workforce strategies at a major automaker like Ford can influence supplier contracts, job stability, and the overall health of Ohio’s industrial base. The recognition that veteran human expertise remains essential alongside advancing technology offers a practical lesson for manufacturers navigating similar transitions.
Ford’s experience underscores a broader point emerging in manufacturing: AI and automation deliver significant value when guided by deep domain knowledge, but they have not yet reached the point of fully replacing seasoned engineers in complex, high-stakes production environments.
The company’s quality recovery, achieved through what it described as a “significant talent refresh,” demonstrates that pairing experienced professionals with improved digital tools can yield strong results, both on the factory floor and in customer satisfaction metrics.
