The AI boom is creating a new kind of supply-chain problem for the automotive industry: data centers are consuming components that cars also need. According to The Next Web, Chinese automakers are reporting global shortages of around 20%–30% for printed circuit boards and multilayer ceramic capacitors (MLCCs), while prices for some of these components have more than tripled over the past year. Automotive memory prices have also risen sharply, with reports of roughly 180% increases in just three months.
MLCCs are small, inexpensive components, but modern vehicles use them in enormous numbers across electronic control units, infotainment systems, sensors and other systems. AI data centers also require huge quantities of electronic components for servers, networking equipment and power-management systems. As hyperscalers continue buying infrastructure at extraordinary scale, suppliers are prioritizing the most lucrative AI-related orders, leaving other industries—including automotive manufacturers—competing for remaining capacity.
The problem is particularly significant for Chinese electric-vehicle makers, because their products are becoming increasingly software- and electronics-intensive. Modern EVs depend on advanced driver-assistance systems, centralized computing, sensors and connectivity, meaning a shortage of seemingly minor components can eventually become a production constraint. The pressure is already visible elsewhere in consumer electronics: Xiaomi recently reported that substantially higher memory and component costs were weighing on its margins, illustrating how AI-driven demand is spreading through the wider electronics supply chain.
The broader lesson is that the AI infrastructure boom is no longer affecting only GPUs and advanced semiconductors. Its enormous appetite is reaching memory, capacitors, circuit boards and other relatively ordinary components used throughout the global economy. That creates a new challenge for manufacturers: even if they can secure the sophisticated chips needed for their products, they may still face shortages of cheaper components that are just as essential. AI's supply-chain impact is therefore becoming increasingly broad—and potentially a source of higher costs and production delays well beyond the technology sector.
