Ford has rehired several experienced engineers after its artificial intelligence (AI) systems fell short of replacing the expertise and institutional knowledge of senior staff. According to reporting by the BBC and Bloomberg, the company rehired more than 300 experienced quality inspectors in recent years to offset gaps in its automated systems.
What happened
Ford attempted to deploy AI across multiple areas of its industrial operations, including in‑line quality control during manufacturing. The company installed about 900 AI‑equipped cameras in its plants to detect quality issues during production and help prevent supply‑chain disruptions. Despite those efforts, executives acknowledged the AI systems did not meet expectations.
Charles Poon, Ford’s vice president for automotive hardware engineering, told reporters: “Artificial intelligence is a fantastic tool, but it’s only as good as the quality of the data you train it with.” He added that the company had not paid sufficient attention to the knowledge of its most experienced engineers, who had worked through many product‑development cycles.
Poon said Ford had mistakenly assumed that simply introducing AI and loading it with existing design requirements would be enough to produce high‑quality products. The automated systems lacked the tacit expertise and know‑how that technicians with decades of experience possess. Many such experts left the company before their knowledge could be incorporated into AI‑driven system development.
Response: rehiring and mentoring
In response, Ford rehired those workers. The more than 300 veteran quality engineers are now helping to train Ford’s AI systems and to mentor younger employees. Poon said the company recognized that advancing its automation, machine learning, and AI tools requires those systems be trained by the most experienced professionals.
Ford’s CEO Jim Farley has previously said AI will leave many knowledge workers behind, and COO Kumar Galhotra has stated the company intends to apply AI across its entire industrial operations.
Results and organizational changes
At the same time Ford acknowledged AI’s limitations, it announced that it finished first among mainstream automakers in the United States in the J. D. Power Initial Quality Study. Ford said achieving that quality level required substantial professional renewal: the company replaced several senior executives and hired nearly 300 experienced engineers.
In short, Ford’s experience shows that deploying AI alone does not guarantee quality improvements; the company has brought back veteran engineers to improve AI training and to transfer institutional knowledge to younger staff.
