In the pursuit of automation, automakers increasingly rely on artificial intelligence. However, recent experience at Ford Motor Co. clearly demonstrated that technology cannot fully replace human experience accumulated over years. Admitting strategic mistakes in quality control, the company brought back hundreds of experienced specialists, which has already yielded impressive results.
The automation mistake
Several years ago, Ford, aiming to optimize costs and speed up development processes, laid off thousands of employees. Management expected that AI-based systems would take over quality control and engineering checks. However, specialists left before they could fully 'transfer' their knowledge and intuition to algorithms.
As a result, automated systems began to miss defects that an experienced professional would have noticed instantly. This led to serious reliability problems, an increase in recall campaigns, and billion-dollar losses for the company.
Admitting the mistake
Ford's management openly acknowledged the miscalculation in its strategy. 'Artificial intelligence is a fantastic tool, but it is only as good as the data it is trained on,' said Charles Poon, Ford's vice president of vehicle hardware. 'We mistakenly believed that simply implementing AI and loading it with our design requirements would yield a quality product. In previous years, we did not pay enough attention to the experience of our most knowledgeable engineers, who have been through many development cycles.'
The return of 'gray-beard' veterans
To rectify the situation, Ford took an unusual but highly effective step. Over the past three years, the company has rehired 350 engineering veterans, informally called 'gray-beard engineers' in corporate culture. Many of them are former Ford employees or specialists from key suppliers.
Their main tasks in the new role:
- Mandatory design reviews: conducting rigorous meetings to thoroughly analyze projects at early stages.
- Proactive vulnerability search: identifying potential failure points before a part or assembly reaches the production line.
- Retraining AI: correcting and fine-tuning machine learning algorithms based on real, not theoretical, experience.
Synergy, not replacement
Importantly, Ford has not abandoned technology entirely. The company continues to invest in automation and has added more than 100 000 automated tests to its production processes. But now the paradigm has shifted: AI works not instead of people, but in tandem with them, enhancing the capabilities of experienced engineers rather than replacing them.
Triumph in the rankings
The results of the new policy were not long in coming. In the J.D. Power U.S. Initial Quality Study (IQS) for 2026, which measures the number of problems per 100 vehicles in the first three months of ownership, Ford made an impressive leap.
Rising from 15th place in 2023, the brand took 1th place among all mainstream automakers in 2026, ahead of such recognized quality leaders as Toyota and Honda. In the overall standings, Ford yielded only to premium brands Porsche and Genesis. In addition, three of the company's models — the F-150 pickup, Super Duty truck, and Mustang sports car — took first place in their respective categories.
Conclusion
Ford's story has become a textbook example for the entire global industry. It proves that blind faith in AI's ability to fully replace human intuition and experience can cost a company billions. Technology delivers the greatest effect not when it replaces people, but when experienced specialists use it as a powerful tool to prevent errors at the earliest stages.
Sources: Transport Topics, Bloomberg, official data from the J.D. Power Initial Quality Study 2026.
