Is ai car manufacturing a trap?

"Always mentioning artificial intelligence," AI has now become the political correctness in various industries, including automobiles.

The wave of electrification and intelligence has swept through the automotive industry, and we have formed a keen pursuit of high automation. Whether it is the high automation in the production process—dark factories, or the high automation of vehicle functions—smart cabins and smart driving, they have become the focus of the industry today.

The application of AI in the automotive field can be divided into the consumer side and the production side. However, regardless of the side, AI faces real challenges, sparking controversy and doubts from various parties, and even presenting potential "traps."

On the consumer side, the debate about intelligent assisted driving no longer needs elaboration. While many pioneering consumers who advocate new technology strongly support it, there are still many experienced drivers who claim, "I absolutely do not trust machines and will not hand over the steering wheel."

On the production side, the involvement of artificial intelligence in high-precision processing and inspection is seen as "capable of improving automotive product quality and manufacturing speed." However, in practice, companies that were the first to deploy AI technology in factories have not been able to reduce the occurrence of failures and the number of automobile recalls.

The American market continues to pave the way globally with data experience, as Ford and Hyundai become the first two automotive companies in the United States to utilize AI in car manufacturing, with each AI factory costing billions of dollars. It can even be predicted that the entire industry might see investments related to AI manufacturing reach the scale of hundreds of billions of RMB.

This year has not yet ended, but Ford has already initiated hundreds of recalls in the United States due to product defects, involving tens of millions of vehicles. Therefore, assessing the true impact of artificial intelligence on the automotive manufacturing industry still requires more time and data accumulation.

01Spending tens of billions and recalling ten million vehicles

When automakers spend billions of dollars (equivalent to tens of billions of RMB) to create AI-driven "smart factories" and promise to improve quality and reduce recalls, the actual efficacy of this much-anticipated technology remains unclear.

If the automation of automobile manufacturing in the previous stage was still centered around mechanical concepts, then this stage is more combined with AI concepts, where software plays a greater role.

In the race to establish "dark factories," no country can compare with China. However, beyond robotic arms, "electronic eyes" and "AI brains" are still fields where overseas car factories can take the lead.

Ford and Hyundai are regarded as the leaders in the current AI manufacturing competition in the American automotive industry. They claim that AI systems can accurately detect defects before vehicles are delivered to customers.

Hyundai Motor's Metaplant factory in Georgia, built with an investment of $7.6 billion, has rolled out its first batch of Ioniq 5 electric vehicles in October 2024. Hyundai has introduced Boston Dynamics robots, automatic guided vehicles, and digital twin technology based on AI, and expanded its collaboration with NVIDIA to further enhance its "smart factory."

In December 2024, Ford launched the AiTriz visual system, which has been installed at 900 workstations in 35 factories across the United States.

This system can verify part installation in complex situations where the line of sight is obstructed, making it more advanced than the initial mobile vision system from the beginning of the year.

Ford regards AI as one of the key potential solutions for breaking through challenges. Jeff Tornabene, the technical manager of Ford's Manufacturing Technology and Development Center, stated: "Our goal is to design products that cannot be installed incorrectly and cannot incorrectly pass through the production process."

According to Ford's statement, quality improvements have been observed in areas where the AI vision system has been deployed, and its application is being expanded. However, they cautiously noted that "not all manufacturing processes are suitable for or require AI."

Meanwhile, Modern spokesperson Miles Johnson outlined his vision: "AI has enormous potential in enhancing quality control and early defect detection."

A stark reality has emerged: even with AI technology deployed in some factories, Ford Motor Company initiated 134 recalls in 2025, involving over 12.17 million vehicles.

For Ford, improving quality and reducing recalls are urgent matters. This veteran giant, headquartered in Dearborn, Michigan, has not only set a record for annual recalls in the U.S. market but is also likely to top the annual recall list for the fourth time in five years.

02The unstoppable flaws of AI

When car companies are loudly proclaiming that "AI helps improve car product quality," industry observers remain cautious. Analysts believe that it is too early to assess the returns on these massive investments.

Based on current performance, the impact of AI intervention in factories is not ideal. The most publicly available quality data—recall announcements—provide complex signals.

After Ford deployed AiTriz, the average scale of recalls involving components in the vehicles produced was significantly lower than the annual average. However, during the same period, Ford still initiated 22 recalls due to manufacturing defects, including improper bolt torque and poor windshield installation, which are precisely the defects that the AI vision and torque monitoring system aims to capture.

Ford did not specify whether the recalled vehicles were produced at AI workstations. Their spokesperson cleverly compared using recall data to evaluate AI to "asking the front door camera why it didn't detect an intruder at the back door."

Ultimately, Ford's record-breaking 134 recalls in 2025 affected over 12.17 million vehicles, with warranty expenses reaching as high as $450 million in just the third quarter of this year. Of course, Ford provided a rather "face-saving" explanation—this reflects a strategy of "extreme caution" and "quick detection and resolution of issues."

In contrast, Hyundai initiated 14 recalls this year, two of which involved the Ioniq 5 produced at the Georgia plant, with issues focused on headlight focus and harness installation.

From a theoretical perspective, neither Ford nor Hyundai has provided specific data directly proving that AI improves vehicle reliability. Both automakers have coincidentally positioned AI as a "long-term quality strategy" rather than an immediate solution.

First, the use of AI in production and manufacturing, and the factors affecting quality, exist in a "gray area."

"It has broad prospects, but it is by no means a panacea," pointed out AutoPacific analyst Robbie DeGraff. He believes that AI tools may help identify problems before large-scale recalls occur, but their analysis and identification capabilities are unlikely to ever achieve 100% accuracy.

As of the end of October, the National Highway Traffic Safety Administration recorded 817 recalls, which is lower than the 963 recalls in the same period last year, but the overall number remains large.

Secondly, AI is in the process of being deployed in car factories, but it is still in its early stages, facing challenges of evaluation difficulty and data mysteries.

Measuring the impact of AI on quality has become a complex project requiring precise data and time accumulation. Adam Bernard, a former senior executive at General Motors and industry analyst, pointed out: "'Artificial intelligence' is a broad concept, and the specifics of its application determine what kind of data is needed."

Even J.D. Power, which releases authoritative quality reports annually, stated that it currently does not track the application of AI in factories.

Therefore, we can conclude that AI indeed helps improve product quality in certain areas, but "believing entirely in books is worse than having no books at all; relying solely on AI to enhance quality can actually hinder it." While AI demonstrates "advancement," we must also be cautious to avoid "traps."

03Cars and car manufacturing both rely on people.

Automakers must ensure that beyond AI, they maintain a human-centered and solid post-production vehicle analysis and supervision system.

This is precisely the conclusion shared by experts such as AutoPacific analyst Robby DeGraff, which means that there is an undeniable "human factor" present in both the consumer side of automotive product usage (such as intelligent driver assistance) and the production side of automotive manufacturing.

Earlier this third quarter, I was invited by Lexus to visit the Lexus Miyata Plant in Miyawaka City, Fukuoka Prefecture, Kyushu, and the Tahara Plant and test site in Tahara Town, Atsumi District, Aichi Prefecture, Honshu. The features showcased were not characterized by a high level of automation where "humans are completely replaced." On the contrary, the collaboration between precise equipment and human labor, as well as the welfare and care of personnel, became the main focus.

In the second production line of Miyata Factory, robotic arms are everywhere and AGV carts operate efficiently, yet the presence of workers remains orderly.

In the previous windshield installation process, workers first cleaned the area where the adhesive was to be applied. Then, the robot applied the adhesive in the correct amount and at the correct location. After that, a team of two workers installed the car window glass onto the vehicle.

A Lexus factory's highest-level "Takumi" worker explained: "Applying the correct amount of adhesive in the right place" is a task that robots excel at. On the other hand, assembling window glass onto cars on the production line, a task that requires sensitivity and skill, is better suited for humans who possess emotional intelligence and flexibility.

"Even within the same work process, humans and machines can be highly integrated and complementary, which is the key to achieving high quality."

Moreover, the spraying process includes some areas that are complex in shape and have limited space, making it difficult for large robotic arms to achieve the level of manual spraying.

More importantly, the training of machines cannot be separated from human operation. If a machine makes an operational error, it also requires human intervention to correct it.

The final inspection process is also a fusion of manual and mechanical work. It is said that there are 1,800 points that need to be confirmed before leaving the factory.

Experts from the East and the West have reached an objective consensus here.

Paul Lavo, Vice President of Innovation and Applied Technology at the University of New Haven, cautions that while the industry is chasing technology, it faces severe talent challenges.

"The pace of advancement in manufacturing expertise may outstrip the speed of employee training," he stated, "This could even undermine the effectiveness of the most advanced AI systems. When implementing AI, the role of human leadership must never be overlooked. We must focus on enhancing employee skills to ensure the adoption of appropriate technology in the right way."

AI's journey in automobile manufacturing has just begun. Hundreds of billions of funds have been thrown in, yet the waves are still uncertain. Whether the promise of "zero defects" can truly be fulfilled, time and data will be the only touchstones.