The AI race has become one of the biggest technology battles of this decade. Governments, companies, and investors are all paying close attention. Both the United States and China have made it clear that they want to lead in this space, no matter the cost. Because of this, massive investments are flowing into data centers and AI-driven services, at the cost of consumer goods.

During a recent discussion with China-based publication Yicai Global, Mark Haefele, the chief investment officer at UBS Global Wealth Management, shared his view on how this AI race is playing out differently in China and the US. He pointed out that both governments openly want to win the AI race and are pushing hard to support companies that can benefit from that goal. From an investment point of view, this creates clear opportunities, but it also highlights how differently AI is being used in each region.

AI development in the US versus China

According to Haefele, China appears to be focusing much of its AI development on strengthening its manufacturing base. AI tools are being used to improve factory efficiency, increase output, reduce waste, and make large-scale production more competitive. This approach fits well with China’s long-standing strength in manufacturing and exports. By using AI to optimize supply chains, automate complex processes, and boost productivity, China is aiming to make its industrial capacity even larger and more efficient than before.

In contrast, Haefele remarked that a big portion of AI use in the US seems to be moving in a very different direction. Instead of being centered mainly on industrial output, a lot of AI capacity is going toward “teenagers having AI boyfriends and girlfriends.” We suppose he isn’t totally wrong, even if it feels a little tongue-in-cheek, given the recently-announced Project AVA companion AI from Razer, a company that is primarily based in the US and Singapore. Elon Musk’s xAI is also no stranger to introducing eye-catching AI companions.

At the same time, the AI boom is putting serious pressure on global hardware supply. Training and running AI models require massive amounts of memory, storage, and computing power. This has already led to a memory crisis, with prices for RAM, GPUs, and even SSDs rising sharply.

About the Author

Abdul Haddi

Abdul is a tech writer and Editor for PC Guide, specializing in all things tech, gaming, and hardware.