US vs China AI Competition

Extracted Attributes

AI boom

An AI boom is a period of rapid growth in the field of artificial intelligence (AI). The current boom originally started gradually in the 2010s with the Deep Learning Phase, but saw increased acceleration in the 2020s. Examples of this include generative AI technologies, such as large language models and AI image generators developed by companies like OpenAI, as well as scientific advances, such as protein folding prediction led by Google DeepMind. This period is sometimes referred to as an AI spring, a term used to differentiate it from previous AI winters. As of 2025, ChatGPT has emerged as the 4th-most visited website globally, surpassed only by Google, YouTube, and Facebook.

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• U.S.-China Competition for Artificial Intelligence Markets - RAND

  The authors analyze global large language model (LLM) adoption patterns of U.S. and Chinese models and explore three key drivers of international LLM adoption: pricing strategies, multilingual capabilities, and government-led diplomacy initiatives. The authors analyze global large language model (LLM) adoption patterns, with a focus on the competitive dynamics between the United States and China. * U.S. models have maintained overwhelming market dominance and captured approximately 93 percent of global LLM site visits in August 2025. Wang, Austin Horng-En and Kyle Siler-Evans, *U.S.-China Competition for Artificial Intelligence Markets: Analyzing Global Use Patterns of Large Language Models,* RAND Corporation, RR-A4355-1, 2026. As of January 14, 2026: https://www.rand.org/pubs/research\_reports/RRA4355-1.html. Wang, Austin Horng-En and Kyle Siler-Evans, U.S.-China Competition for Artificial Intelligence Markets: Analyzing Global Use Patterns of Large Language Models. https://www.rand.org/pubs/research\_reports/RRA4355-1.html. This research was independently initiated and conducted by the Center on AI, Security, and Technology within RAND Global and Emerging Risks using income from operations and gifts and grants from philanthropic supporters. This publication is part of the RAND research report series.

• US-China AI Race in Focus at Davos - YouTube

  US-China AI Race in Focus at Davos Bloomberg Technology 714000 subscribers 5 likes 177 views 22 Jan 2026 Tech leaders at the World Economic Forum in Davos have been giving their views on the US-China AI race. Liza Tobin, managing director at Garnaut Global, says the US advantage lies in the scale of its compute capacity. Tobin joins Caroline Hyde and Ed Ludlow on "Bloomberg Tech." -------- Like this video? Subscribe to Bloomberg Technology on YouTube: https://www.youtube.com/channel/UCrM7B7SL_g1edFOnmj-SDKg   Watch the latest full episodes of "Bloomberg Technology" with Caroline Hyde and Ed Ludlow here: https://www.youtube.com/playlist?list=PLfAX25ZLrPGTygCwn55voYZ_LYyKjxokJ   Get the latest in tech from Silicon Valley and around the world here: https://www.bloomberg.com/technology Connect with us on... X: https://twitter.com/technology Facebook: https://www.facebook.com/BloombergTechnology Instagram: https://www.instagram.com/bloombergbusiness/   Follow Ed Ludlow on X here: https://twitter.com/EdLudlow Follow Caroline Hyde on X here: https://twitter.com/CarolineHydeTV   Listen to the daily Bloomberg Technology podcast here: https://www.bloomberg.com/podcasts/series/bloomberg-technology   More from Bloomberg Business Connect with us on... X: https://twitter.com/business Facebook: https://www.facebook.com/bloombergbusiness Instagram: https://www.instagram.com/bloombergbusiness/ LinkedIn: https://www.linkedin.com/company/bloomberg-news/ TikTok: https://www.tiktok.com/@bloombergbusiness

• China, the United States, and the AI Race

  # China, the United States, and the AI Race. China might have become the manufacturing floor for the global economy, but the West has taken some comfort from the assessment that the United States retains the lead when it comes to the quest for artificial intelligence (AI). The differences in AI strategy between the United States and China are also reflected in each country’s policy response, including their approach to export controls. Washington has spent years weaponizing the leading edge of the AI technology stack—restricting China’s access to the most advanced GPUs which could facilitate China’s competition in our race toward AGI—while Beijing has consolidated control over the inputs—including critical minerals—which could help the United States compete in their race toward industrial dominance. As my colleague Rush Doshi noted, “This is basically like the United States’ Foreign Direct Product Rule, but with Chinese characteristics.” If China enforces these controls, even selectively, it could send shockwaves through the global supply chain for advanced computing, electric vehicles, and renewable energy systems—industries that depend on the same materials portfolio.

• Hedged Bets on the U.S.-China AI Race | Charting Geoeconomics

  Jack Shanahan and Lawfare Senior Editor Kevin Frazier contend the United States ought to reorient its approach to more closely mirror China’s and instrumentalize America’s “formidable innovative spirit into practical applications and evidence-based impact.” Council on Foreign Relations President Mike Froman similarly questions if the United States is “racing toward the wrong finish line,” with Chinese initiatives strategically integrating AI as a “default layer of the industrial economy.”. Moreover, as a growing number of American companies rely on China’s open-weight AI models to meet business needs, direct comparisons of diffusion outcomes mischaracterize underlying diffusion capacity – attributing American diffusion success partly to adoption of Chinese models. To this end, the United States’ continued global AI leadership status is contingent on capital markets retaining their resiliency, growing American diffusion, and frontier model advantages. Without incorporating elements from the other's model, the United States and China will face significant shortcomings in capital, technology, and adoption as they attempt to vertically integrate AI.

• The Myth of the AI Race: Neither America Nor China Can Achieve ...

  The decision reflects a belief that allowing China access to “good enough” computing power can generate revenue for U.S. companies and reinforce American technological standards without risking the United States’ edge in AI innovation. But the danger of selling high-end U.S. chips to China is that it could lead to a more divided AI landscape—one in which U.S. firms maintain a lead in providing advanced AI-based services, but Chinese companies gain ground in disseminating their slightly less advanced but cheaper technology around the world and applying AI to machines, factories, and infrastructure. U.S. companies design the world’s most advanced AI chips, primarily through Nvidia, and the United States is far ahead of China in the scale of AI data centers. Access to computing power, then, remains the single most binding constraint on China’s global AI ambitions—a constraint that the Trump administration just eased with its decision to allow some Chinese firms to buy Nvidia’s H200 chips.