German automaker Audi has launched a flexible workforce program allowing employees to voluntarily transfer to aerospace and defense companies such as Airbus, with Audi reporting strong employee interest. The move reflects how automotive talent is breaking through industry boundaries and echoes Taiwan's supply chain transformation from computers, communications, and consumer electronics (3C) to automotive applications and now AI data centers.
Reuters reported that Audi is allowing project managers, technical development staff, and quality assurance personnel to voluntarily transfer to companies including Airbus, MBDA, Diehl Defence, and KNDS for up to 24 months. During that period, the employees will remain employed by Audi, retain their existing collectively agreed wages, and receive additional allowances before returning to Audi at the end of the assignment.
The program involves temporary assignments rather than layoffs, offering a flexible way to deploy talent during a period of transformation. Audi said employee interest in the initiative was strong, while the union has endorsed the initiative as a meaningful measure to protect jobs.
Taiwan's own cross-sector talent journey
The case also reflects the cross-sector expansion of Taiwan's talent over recent decades.
Before 2000, Taiwanese companies moved from 3C and information and communications technology into automotive electronics. They initially assumed electrification would rapidly rewrite the rules of the auto industry, but many struggled with the automotive standards required by leading European, US, Japanese, and South Korean automakers.
The challenge at the time was that cross-sector talent brought the rapid-iteration mindset of consumer electronics into the automotive industry, where reliability, stringent certification, and long development cycles are critical. In recent years, Taiwanese companies have gradually aligned themselves with leading automakers in Europe, the US, Japan, and South Korea.
China was another potential growth direction during that period. Its market initially appeared to offer Taiwanese companies the easiest path into the automotive sector, but China's self-sufficiency policies ultimately limited the room for Taiwanese businesses to operate more than was expected.
Now the situation has reversed. With the automotive market under pressure in recent years, AI has emerged as a new driver of the business cycle, prompting Asian suppliers to rapidly and extensively expand into industrial-grade applications and AI data centers.
This time, talent accustomed to automotive standards must break through rigid thinking. Their established processes emphasize getting things right the first time and prioritizing stability over speed. Faced with AI data centers' rapid evolution and customers operating on different timelines, they can easily struggle to adapt.
Industry sources said entering the AI data center market presents a challenge for professionals with only an automotive standards mindset, making the initial expansion less efficient than expected. As the AI industry has rapidly taken off, some companies have established independent divisions and dedicated teams to focus fully on AI data centers and industrial control, concerned that business opportunities could quickly pass them by.
However, this view is limited to a small number of companies. Taiwan's six leading semiconductor and electronics companies play critical roles in the global AI ecosystem. Because these businesses have experience in both 3C electronics and automotive standards, most have been able to quickly allocate resources toward AI.
In practice, the technical barriers to entering AI data centers are relatively limited for companies that have undergone the rigors of automotive standards. Some have even applied technologies developed for the automotive sector to AI, including 800V systems, power semiconductors, power management, and thermal management.
Of course, AI data centers have their own product characteristics and requirements. Suppliers must continue advancing their technologies and still face certification periods, although these currently do not appear to be as lengthy as the automotive certification processes required by leading automakers.
Article translated by Lily Hess and edited by Ysi Chen
