As the September 24 meeting between U.S. President Donald Trump and Chinese President Xi Jinping in Washington approaches, discussions around mitigating risks posed by cutting-edge frontier artificial intelligence models and resolving long-running intellectual property disputes have emerged as the core items on the bilateral agenda.
This planned first official U.S.-China AI dialogue under the Trump administration, first disclosed by Reuters on July 21, will be led on the American side by Treasury Secretary Scott Bessent. Trump later confirmed the report on July 23, noting that the two leaders first broached the topic of AI collaboration and competition during his May visit to Beijing, where the pair met on May 14, 2026.
Chinese state observers and media outlets point out that the Trump administration’s push for the summit stems from growing anxiety over China’s rapid progress in the global AI race. This concern intensified after China secured new AI development partnerships with 28 countries, mostly from the Global South, at the 2026 World Artificial Intelligence Conference held in Shanghai this past July. Within Chinese policy and tech circles, there is a widespread consensus that further U.S. export restrictions and regulatory curbs on China’s AI sector will only accelerate domestic efforts to achieve technological self-sufficiency and build an independent, sustainable AI ecosystem.
The upcoming talks will center on regulating high-capacity AI models that carry far-reaching implications for global security and economics: these systems could rebalance global military power, enable devastating cyberattacks on critical national infrastructure, and cause widespread disruption to global labor markets. Trump has repeatedly framed AI as one of the most transformative technologies in human history, warning that the nation that leads the global AI race will hold unmatched strategic and economic advantage. “Whoever wins that race is probably going to win,” he stated in his confirmation of the September talks.
Washington’s push for dialogue comes against a backdrop of dramatic breakthroughs by Chinese AI developers over the past 12 months. Leading domestic firms including DeepSeek, Zhipu AI and Moonshot AI have launched a wave of low-cost, high-performance frontier models that match or even outperform U.S. industry leaders OpenAI’s ChatGPT and Anthropic’s Claude on key industry benchmarks.
A key strategy that has allowed Chinese firms to deliver strong results at a fraction of the cost of Western competitors is knowledge distillation, a process where new models learn pattern recognition and reasoning by studying outputs from existing Western AI systems, rather than building foundational capabilities from scratch. This approach eliminates the need for massive purchases of expensive cutting-edge AI chips. Chinese developers have also paired distillation with two efficiency-focused architectural innovations: mixture of experts (MoE), which routes individual queries only to the most relevant subset of the model’s parameters rather than activating the entire system, and sparse attention, which lets models focus only on the most contextually relevant sections of input text. Both techniques drastically cut computing requirements without sacrificing output accuracy.
In a July 26 commentary, the Global Times, a publication under China’s People’s Daily, noted that China’s open-source AI ecosystem has expanded dramatically in power and influence over the past two years, enough to trigger alarm among leading U.S. AI research labs. “Two years ago, names like Zhipu AI and Moonshot AI barely registered in the American tech press. Now their models are going toe-to-toe with those from Anthropic and OpenAI,” the commentary read. “The United States’ panic makes sense.”
The publication added that Washington has adjusted its strategy in the AI contest with China: rather than seeking to rapidly displace China from the global AI market, the U.S. is now focused on extending its current lead for as long as possible. “The failure to eliminate China doesn’t mean the contest is over. On the contrary, as knocking China out becomes less feasible, the AI race between the US and China simply shifts to more specific and hard-fought fronts,” the commentary said. “As long as China stays true to a development path suited to its own realities, it will earn the standing it deserves in shaping AI’s norms, rules and standards of access.”
That reference to “China’s realities” speaks to the long-running impact of U.S. export controls that have constrained China’s access to advanced chip manufacturing technology and high-end AI hardware, a topic rarely addressed directly by Chinese state media until recently. The U.S. first blocked Dutch chip equipment giant ASML from selling extreme ultraviolet (EUV) lithography machines to China in 2019, extended restrictions to cover cutting-edge deep ultraviolet (DUV) lithography systems in October 2023, and banned exports of high-end Nvidia AI graphics processing units (GPUs) to China starting in October 2022.
In response to these restrictions, Chinese firms initially adapted by sourcing second-hand mid-tier DUV machines for domestic AI chip production, routing imports of Nvidia chips through smuggling networks and shell companies, and training large models at overseas data centers in Southeast Asia. As controls tightened further, however, firms pivoted to the cost-effective distillation strategy that has now enabled their competitive breakthroughs.
For its part, the Trump administration has raised formal concerns over intellectual property practices in China’s AI sector. Speaking on July 21, Treasury Secretary Bessent said the administration has gathered evidence indicating that leading Chinese AI models draw heavily on foundational development work from U.S. systems, emphasizing that Washington does not tolerate what it frames as intellectual property theft.
Chinese analysts and policymakers have framed their country’s AI strategy as fundamentally different from the U.S. approach. Zhu Min, former deputy governor of the People’s Bank of China, outlined China’s priorities during a June World Economic Forum panel, noting that Beijing’s top goal is to integrate AI across China’s massive industrial economy, with a particular focus on manufacturing applications.
“China’s greatest advantage was never about building the largest model. It lies in having more use cases, more factories, more diverse industries and cost-conscious business owners,” Zhu explained. “The real winners will not be the AI model makers but those doing deployment, integration and process restructuring. The vendors installing factory systems, connecting data pipelines, retraining workers and collecting annual fees will pocket more than anyone.”
Zhu emphasized that manufacturing offers the clearest return on AI investment in China: every small improvement in production yield directly boosts profits, every avoided unplanned outage cuts avoidable losses, and every shortened delivery cycle increases business turnover. By contrast, he noted, U.S. investment capital overwhelmingly focuses on backing a small number of top-tier foundational model developers, betting that a handful of firms will capture the bulk of the global AI market. Chinese investment, meanwhile, flows disproportionately to application layers and industrial integration, targeting returns from the vast network of domestic factories, niche use cases and commercial orders.
Not all observers expect major breakthroughs from the September talks. Shandong-based political commentator Chen Xia argues that the U.S. is unlikely to make meaningful concessions on core issues China cares about, including easing export controls and expanding access to advanced technology. “The most likely outcome is a handful of toothless risk management clauses. On the issues China truly cares about, including access to technology and the easing of export controls, the US will not compromise on any of them,” Chen said. “The US only wants to walk away with maximum political gain at minimum cost.”
Chen also frames Trump’s outreach for AI talks as a tactical political move ahead of U.S. midterm elections in early November, where Trump’s Republican Party is fighting to defend its narrow majorities in both the U.S. Senate and House of Representatives. After the election, Chen argues, Washington’s underlying strategy of containing China’s AI development will become more explicit. He added that the U.S. is using the dialogue process to push for global AI governance rules that advance its own strategic interests and lock other nations into a disadvantaged position, while China seeks to secure a more equitable voice in shaping global AI rules.