What is AI Superpowers about?

AI Superpowers is Kai-Fu Lee's argument that the geopolitical competition to lead in artificial intelligence is primarily a two-country race between the United States and China, and that the outcome will reshape the global economy in ways most people haven't started to reckon with. Lee is unusually positioned to make this case: he ran Google China, founded a major Beijing venture capital firm, and trained under AI pioneer Geoffrey Hinton. The book draws on that dual vantage point rather than on secondhand analysis.

Lee's core claim is that the era of AI discovery—inventing new algorithms—is largely over. What matters now is implementation: applying existing AI to real problems at scale. On that dimension, China has structural advantages that the US AI community consistently underestimates. China has more data, a culture of execution and imitation that moves faster than American startups typically allow, and a government willing to treat AI as national strategy. Lee doesn't argue China will win outright, but he does argue that the default Silicon Valley assumption—that the US leads by default—is wrong.

The second half of the book shifts from geopolitics to labor economics. Lee estimates that AI will displace roughly 40 percent of global jobs within 15 years, with repetitive cognitive tasks most at risk: loan officers, radiologists reading standard images, customer service agents. The jobs least at risk are those requiring creativity, genuine human connection, or physical dexterity in unpredictable settings. He argues existing safety nets are nowhere near adequate for the transition.

The book ends on a personal note unusual for a technology executive. Lee was diagnosed with lymphoma while writing and describes the experience changing his framework. He argues that human compassion and care—the things AI demonstrably cannot replicate—should be the foundation of whatever we build next. The tone shifts from competitive analysis to something closer to an appeal. Readers looking for a clear-eyed account of AI's economic consequences will find it here, though the optimism in the final chapters reads somewhat against the weight of the preceding evidence.