Or consider the growing national security-AI industrial complex. The U.S. government is becoming a major customer of leading AI companies<\/a>, deepening entanglements with the Defense Department, CIA, National Security Agency, and others. An odd alliance that includes U.S. President Donald Trump, socialist independent Sen. Bernie Sanders, and OpenAI CEO Sam Altman is seeking ways for the U.S. government to become a major stakeholder of these companies.<\/p>\n As David Sacks, who recently stepped down from his position as the Trump administration\u2019s AI czar, pointed out<\/a> in late July, the United States\u2019 champions\u2014OpenAI and Anthropic\u2014are now resorting to a \u201cregulatory capture strategy\u201d focused on persuading the U.S. government to adopt regulations and laws that will handicap their competition, both foreign and domestic.<\/p>\n Three powerful forces are fueling this race for the brightest shiny object that current observers have ever seen.<\/p>\n First, AI companies are chasing what they believe will be the biggest-ever pot of gold at the end of the rainbow. For the first time in history, companies and individuals are talking not in billions but trillions. Their leaders stand to gain not only heretofore unimagined fortunes but also fame and influence. Note, for example, the June G-7 meeting in France, at which AI CEOs took seats around the same table as leaders of the world\u2019s advanced economies to discuss the road ahead. Is there anything they would not say or do to win?<\/p>\n Second, U.S. Treasury Secretary Scott Bessent and other economic policymakers are acutely aware of the huge systemic risk posed by the nation\u2019s unsustainable annual fiscal deficits (now at nearly 6 percent<\/a> of GDP) and government debt (the annual interest payments on which now exceed the defense budget). An AI miracle that produces unprecedented increases in productivity and growth offers their best hope for avoiding an economic catastrophe.<\/p>\n Finally, the national security strategist community has declared that AI is existential, in that whoever wins the AI race will rule the world. They have accepted the technology titans\u2019 proposition that whichever nation is first to build a super-intelligent \u201cAGI,\u201d artificial general intelligence, will have a decisive, irreversible advantage\u2014since an agent smarter than all the Nobel laureates in the world will then begin teaching itself. In former U.S. Secretary of State Condoleezza Rice\u2019s summary: This is a race that \u201cwe absolutely have to win.\u201d<\/p>\n Confronting this blizzard of claims and counterclaims about a bedazzling technology, four questions demand our attention.<\/p>\n First, is the course that the United States has chosen prudent? Another way to think about this is, would a financial investor with fiduciary responsibility place this large a bet on a single sector? Second, what could go wrong? Could the eye-popping increases in investment and stock prices be another bubble\u2014analogous to the financial wizardry that created the real-estate bubble that burst in the Great Recession of 2008 or the dot-com bubble in 2000? Third, why is the only other AI superpower\u2014China\u2014making such a radically different bet?<\/p>\n And finally, if the miracle is delayed or never happens, what will the likely consequences be\u2014not just for the U.S. economy but also for national security?<\/p>\n A group of men in dark business suits standing together outdoors on concrete stairs, with several looking forward and one checking his phone.<\/p>\n Tesla CEO Elon Musk checks his phone next to Apple CEO Tim Cook, Blackstone CEO Stephen A. Schwarzman, and Nvidia CEO Jensen Huang, as U.S. Treasury Secretary Scott Bessent, Secretary of State Marco Rubio, and Ambassador to China David Perdue stand prior to a welcome ceremony for U.S. President Donald Trump during his visit to China on May 14. Alex Wong\/Getty Images <\/p>\n However attractive a stock such as Elon Musk\u2019s SpaceX or a sector such as AI, successful investment firms know better than to place most of their eggs in one basket. As Bridgewater founder Ray Dalio put it, piling into \u201cone new sector that is highly volatile and risky\u201d is \u201cunsophisticated.\u201d<\/p>\n Nonetheless, in the first half of 2026, more than 80 percent<\/a> of global venture capital funding has flowed into AI start-ups. Google, Microsoft, Meta, and Amazon have announced plans to cumulatively spend more than $1 trillion on AI in 2025 and 2026\u2014relying on debt markets to finance their ambitions. Moreover, in the drive for more computing power, or compute, a growing number of circular transactions have frontier AI companies contracting with chipmakers that invest the funds from their purchases back into their customers, further inflating share prices.<\/p>\n How could this go wrong? Ask your AI assistant, and it will provide a list of a dozen ways. In his last article published before he died in 2023, Henry Kissinger and I warned<\/a> about the possibility of an AI Chernobyl or AI 9\/11, in which a powerful AI assists a malign actor in producing a bioweapon or similar device that could kill hundreds of thousands of people, disrupt the financial markets, or shut down the electricity grid.<\/p>\n In an open letter<\/a> published in June, all the AI titans\u2014Altman, Anthropic\u2019s Dario Amodei, Google DeepMind\u2019s Demis Hassabis, Microsoft\u2019s Mustafa Suleyman, and Meta\u2019s Alexandr Wang\u2014highlighted the risk of an AI-enabled killer pathogen and called for serious safeguards. Beyond that, Amodei has offered his view that there is a \u201c25 percent chance that AI could lead to catastrophe for the human race.\u201d<\/p>\n The more immediate risk is a collapse of what increasingly looks to many analysts like a classic bubble. In its monthly global fund manager survey for July, Bank of America ranked a bursting of the AI bubble as the key risk to financial markets. Financial institutions such as the Bank for International Settlements are now warning that valuations for AI companies exceed earnings by an amount not seen since 1929.<\/p>\n Drawing lessons from his reading of the history, Michael Burry, one of the investors portrayed in The Big Short, has cautioned<\/a>: \u201cWe are getting into that rare air, so extreme that the consequences will be unavoidable, no matter where one hides.\u201d<\/p>\n Recent market corrections reflect concern that the hyperscalers are building more compute than they require. For example, Meta, SpaceX, and others are actively exploring renting capacity to other companies. As Forbes concluded<\/a> from a recent analysis by Bain and Company, \u201ctech companies will need to find $2 trillion in new AI revenue to make a profit on the cost of deployment.\u201d Last week, DeepSeek released a powerful upgrade to its V4 model that can complete complex coding tasks at a level comparable to Anthropic\u2019s top-tier Claude Opus 4.8. But as Axios notes<\/a>: \u201cDeepSeek charges about 28 cents for the same amount of output that costs $25 on Opus 4.8\u2014a 99% discount.\u201d Coming on top of OpenAI\u2019s announcement that it was cutting the price of its fastest model for high volume tasks by 80 percent only three weeks after its launch, the release is igniting debate about whether AI products are in effect becoming \u201ccommoditized\u201d\u2014eroding the frontier labs\u2019 pricing power.<\/p>\n At the same time, the companies are facing a rising tide of resistance to their deployment plans. The governor of New York state has imposed a one-year ban on new AI data centers. Polls now show<\/a> that 7 in 10 Americans oppose the construction of data centers in their neighborhoods. And 80 percent<\/a> of Americans are concerned about AI. Their fears<\/a> include the possibility that AI will take their jobs, harm their children\u2019s education, and make truth inseparable from fiction online.<\/p>\n A person stands inside a dark, immersive room featuring large-scale digital projector displays of glowing red and pink gridlines, numbers, and data code across the walls and floor.<\/p>\n A visitor tours Dataland, the \u201cworld\u2019s first museum of AI arts,\u201d during a press preview in Los Angeles on June 16. Mario Tama\/Getty Images<\/p>\n The fact that the United States\u2019s only credible competitor in AI\u2014China\u2014is taking such a strikingly different path should make Americans pause and think. Beijing shares with Washington the view that AI is of critical national importance. On the day in 2016 when DeepMind\u2019s AI beat the world\u2019s Go champion, President Xi Jinping declared<\/a> that this was a technology in which China could and should achieve global supremacy.<\/p>\n But in contrast to the frenzy in Silicon Valley to install evermore compute in pursuit of a world-changing AGI, Beijing has been more relaxed. Why is a good question. Money is certainly not the obstacle\u2014since China has a sovereign wealth fund of $3.6 trillion<\/a> and recorded a trade surplus of $1.2 trillion last year. U.S. constraints have limited Chinese access to the most advanced semiconductors and the equipment to produce them\u2014though Chinese companies have demonstrated remarkable skill at finding holes in these fences and other work arounds.<\/p>\n While one can never know what one doesn\u2019t know, there is no evidence of a hidden, state-directed Manhattan Project for AI in China. China\u2019s latest five-year plan<\/a> identifies AI as a top priority. But its \u201cAI Plus\u201d program focuses primarily on strengthening the integration of AI across society to increase productivity, multiply scientific breakthroughs, streamline governance, and improve everyday life.<\/p>\n Indeed, China\u2019s strategy for becoming the world leader in AI reflects its basic strategy for achieving dominance in the production of everything. In essence, as we have seen in its domination of solar panels, fast trains, 5G, consumer electronics, and now increasingly electric cars, China begins by offering a product almost as good as the alternative but at a far more affordable price<\/a>.<\/p>\n Unlike their U.S. counterparts, China\u2019s large corporate champions in the AI race\u2014Baidu, Alibaba, and Tencent\u2014are not aggressively building massive data centers. In 2025, the three Chinese champions spent roughly one-tenth<\/a> of what the U.S. hyperscalers spent on AI. Yet they are releasing models that rival the performance of those produced by the United States\u2019 AI leaders.<\/p>\n \u00a0\n<\/p>\n Moreover, an array of small start-ups is producing startling results. This month\u2019s launch of Kimi K3 by Moonshot<\/a> produced what some in Silicon Valley called a \u201cmoon quake\u201d\u2014upending the frequently stated conviction that the United States leads China by at least six to 12 months. Kimi\u2019s results on AI benchmark tests are comparable to those of Anthropic\u2019s and OpenAI\u2019s most advanced models.<\/p>\n Rather than offering hundred-million-dollar signing bonuses to attract \u201csuperintelligent\u201d AI stars, DeepSeek demonstrated that with just 200 engineers earning around $150,000 a year, it could produce a model that could perform almost as well as U.S. competitors\u2014and one that it offers to users around the world for free. Moonshot, Zhipu, and China\u2019s other \u201cAI tigers\u201d are following a similar playbook. Nvidia CEO Jensen Huang has estimated that half of all the AI super talent in the world is in China. So, as one Chinese AI leader put it, in the rivalry between brain cells and GPUs, China is betting on the former.<\/p>\n The United States\u2019 frontier labs keep their model weights and training data proprietary in order to sell their services for revenue. China\u2019s AI companies have instead chosen to open-source their models, making them available to anyone in the world essentially for free. China\u2019s approach is analogous to Google\u2019s in its competition with Apple to develop the leading smartphone operating system. While Apple\u2019s iOS is a premium product available only to those who buy iPhones, Android can be installed on many devices free of charge, encouraging adoption and enabling app development within the ecosystem. Today, Android is used in 70 percent of smartphones in the world and offers twice as many apps as Apple\u2019s iOS.<\/p>\n Similarly, users around the world are increasingly selecting Chinese AI models over U.S. models. Chinese models now handle almost two-thirds of the world\u2019s AI use, measured in tokens. On the leaderboard<\/a> of AI models that process the most tokens, the five most popular are Chinese. U.S. companies such as Airbnb that employ Chinese models rather than American ones report<\/a> that their AI costs are roughly one-tenth that of the U.S. alternative.<\/p>\n Trump addresses an audience while standing behind a wooden podium bearing the seal of the president of the United States, framed by signs reading “Winning The AI Race” on a blue backdrop. The light in front of him is harsh, projecting two shadows of Trump on the wall behind him on either side.<\/p>\n Trump speaks during the \u201cWinning the AI Race\u201d summit hosted in Washington on July 23, 2025.Chip Somodevilla\/Getty Images<\/p>\n In the year ahead, if the United States\u2019s AI miracle fails to materialize, the economic consequences are likely to exceed those of the real-estate bubble of 2008 and the dot-com bubble of 2000. Indeed, we could see another 1929. After the 2008 crash, U.S. GDP fell by 4.3 percent<\/a>. During the Great Depression, it dropped nearly 30 percent<\/a>. The downturn that began in 2000 erased $5 trillion<\/a> of Americans\u2019 wealth as the Nasdaq lost almost 80 percent of its value\u2014and it took 15 years to recover to pre-recession levels.<\/p>\n Beyond economics, the national security consequences of a U.S. AI bubble that bursts are even more disturbing to contemplate. The collapse of wealth, fall in government revenues, and spike in demand for social programs would upend all plans for national security and defense investments.<\/p>\n The impact of this event\u2014the visible failure of the world\u2019s technology leader in what it had declared was the most consequential technology race of all time\u2014on confidence in the United States both at home and abroad would be even graver. Remember the crash of 1929. It led to the Great Depression of the 1930s and created the conditions in which fascists took power in Germany and Italy. It ended in World War II.<\/p>\n In 2008, the failure of mortgage-backed securities created by Wall Street financial engineers caused the global Great Recession, which was on the precipice of becoming another Great Depression. As Hank Paulson, who served at that time as secretary of the U.S. Treasury and the designated lead for averting another depression, has explained<\/a>, catastrophe was avoided only by a coordinated stimulus in which the U.S. and Chinese governments acted together. But as Paulson also noted, this became, for Xi and his colleagues, a decisive learning moment. Previously, they had assumed that Wall Street\u2019s supposed masters of the universe knew what they were doing and could be relied on to manage the global financial system prudently. After seeing their reckless risk-taking fail, Xi and his team chose a different course.<\/p>\n How would China respond to the chaos in the United States and the world that would accompany an AI collapse?<\/p>\n","protected":false},"excerpt":{"rendered":"The United States is betting the house on winning the artificial intelligence race with China. Consider the U.S.…\n","protected":false},"author":2,"featured_media":129814,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[6744,24,3013,387,1984,1897,44476,3772,58471,2018,214],"class_list":["post-129813","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agi","tag-agi","tag-ai","tag-artificial-general-intelligence","tag-china","tag-economics","tag-geopolitics","tag-great-power-politics","tag-homepage_regional_americas","tag-paywall-free","tag-science-and-technology","tag-united-states"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/129813","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=129813"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/129813\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/129814"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=129813"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=129813"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=129813"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"A](\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/08\/2-ai-gamble-us-GettyImages-2276124586.jpg\")
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