{"id":691183,"date":"2026-06-08T07:09:25","date_gmt":"2026-06-08T07:09:25","guid":{"rendered":"https:\/\/www.newsbeep.com\/us\/691183\/"},"modified":"2026-06-08T07:09:25","modified_gmt":"2026-06-08T07:09:25","slug":"the-short-sellers-argument-nobody-on-the-coming-mega-ipo-roadshow-wants-you-to-make","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us\/691183\/","title":{"rendered":"The short seller\u2019s argument nobody on the coming mega IPO roadshow wants you to make"},"content":{"rendered":"

The race to be the first frontier AI lab to reach public markets is on. Anthropic just\u00a0confidentially filed<\/a>\u00a0for an initial public offering. OpenAI has reportedly been preparing its own draft. The valuations are eye-watering: Anthropic at\u00a0$965 billion<\/a>, OpenAI at $852 billion, each now looking to\u00a0raise $60 billion<\/a>. Add SpaceX\u2019s launch-and-AI vehicle,\u00a0pursuing a $1.75 trillion listing<\/a>, and these debuts are the most concentrated burst of capital formation since the dot-com peak. Expect investors to go nuts.<\/p>\n

But wait. Take a peek inside where the revenues for these AI darlings will come from. The labs racing each other are optimized for the top 15% of the global AI market, Anthropic\u00a0even more so<\/a>\u00a0than OpenAI: enterprises with fast networks, deep talent, generous compute budgets \u2014 for now \u2014 and CEOs and their employees being encouraged to play with the models and find productivity gains. That is where copilots and frontier models deliver their most impressive demos. It is not where most of the money is. Hours after Anthropic filed its pre-IPO paperwork, OpenAI CEO Sam Altman admitted that corporate concern over excessive AI costs was\u00a0\u201cfair criticism.\u201d<\/a>\u00a0Apart from the fact that corporate buyers are\u00a0struggling<\/a>\u00a0to find the ROI, the cheaper open-source alternatives do just as well. Buyers are not yet seeing the returns the AI frontier lab sellers are pricing in.<\/p>\n

Superintelligent agents in American companies may not be the killer app after all. The history of business tells us that the real money is where there\u2019s unmet need. And that need is in unglamorous settings that the frontier labs aren\u2019t pitching and most investors aren\u2019t watching.<\/p>\n

My Digital Planet team\u2019s\u00a02026 Digital Evolution Index<\/a>\u00a0scores 125 economies on 185 indicators. There is unmet need in both the rich and developing economies, where AI revenue actually scales.<\/p>\n

Entreprises in the highly digitally evolved economies, the U.S. and Europe can use AI for desperately needed modernization of banks, insurers, and ministries. Some\u00a043%<\/a>\u00a0of core banking systems and 95% of ATM transactions still run on COBOL, a program that predates the year the Beatles got together. In fact, when Anthropic argued Claude could automate that modernization and IBM<\/a>, whose mainframe franchise rests on the old code,\u00a0fell 13.2%<\/a>, its worst session since 2000.<\/p>\n

Fifty-one \u201cBreak Out\u201d economies, such as India, Brazil, Indonesia, Kenya, Vietnam, that aren\u2019t as digitally evolved but with digital momentum accelerating faster than almost anywhere in the developed world, have a clear killer app. Here, hundreds of millions of users have turned to mobile wallets and rich transaction histories yet cannot get formal credit. AI credit scoring trained on payment data, identity authentication and fraud detection can unlock a mountain of value. And these payment systems ride rails already clearing at huge scale. India\u2019s UPI\u00a0processed 22.6 billion transactions in March 2026 alone<\/a>; mobile money\u00a0moved more than $2 trillion worldwide in 2025<\/a>. This is not a niche waiting to graduate into the \u201creal\u201d economy. Here we have value that can be released by AI across vast populations with growing demand, already at scale, already monetizing. But these applications are absent from the daily chatter about AI\u2019s ROI and revenue potential.<\/p>\n

And then there are \u201cWatch Out\u201d economies mostly in Sub-Saharan Africa and South Asia. Our\u00a0research<\/a>\u00a0estimates that in just a single application, AI crop-disease detection across just seven African countries you could unlock $6.1 billion for 14 million smallholder farmers\u2014and those populations report, counterintuitively, the highest trust in AI of any cohort measured anywhere, higher than the Silicon Valley executives whose enthusiasm is priced into these IPOs.<\/p>\n

This has happened before<\/p>\n

Consider some lessons from history. At the dot-com peak, capital flooded into Pets.com and Webvan. The companies that captured the most durable internet revenue, however, were Cisco, which sold the routers; Akamai, which delivered the content; and eventually Amazon<\/a> Web Services. The mobile era ran a similar script: the long-run winners weren\u2019t the handset makers \u2014 with the exception of Apple<\/a> \u2014 but tower companies like American Tower<\/a> and Crown Castle<\/a>, which owned the infrastructure every carrier had to rent no matter which phone won. The more transformative the technology, the more durable value migrates to the layer everyone building on top must pay for, indefinitely.<\/p>\n

The strategic acquirers already know this. In a depressed 2025 deal market, the one hot corner was data infrastructure, the pipelines AI models run on: IBM\u00a0bought DataStax<\/a>, ServiceNow\u00a0acquired Data.world<\/a>, and Salesforce<\/a> paid\u00a0$8 billion for Informatica<\/a>. The acquirers aren\u2019t betting on which model wins. They\u2019re buying whatever every company building on AI will have to pay for, forever.<\/p>\n

The short thesis, stated plainly<\/p>\n

The arithmetic of the buildout is unforgiving. Bain & Company\u00a0warns<\/a>\u00a0AI will need $2 trillion in annual revenue by 2030 to justify its compute spending: an $800 billion shortfall. Oracle<\/a> just\u00a0disclosed<\/a>\u00a0$248 billion in data-center leases running 15 to 19 years, against customer contracts that often run five. Open-weight models are compressing inference prices an estimated 30% to 50% a year, capping the margins any model layer can defend.<\/p>\n

None of this means the mega-IPOs will be a bust. OpenAI may start hitting the revenue targets it has been missing thus far; Anthropic, racing to list first, may make its case to enough enterprises; SpaceX\u2019s launch economics may justify its price. But the race to be first to market is also a race to sell a story about AI diffusing frictionlessly across a global economy of augmented knowledge workers before the ROI numbers catch up with it. The data say that economy doesn\u2019t yet exist.<\/p>\n

The investors who made generational money in past cycles never bought the most exciting story at the IPO moment. They asked a simpler question: where is the need and what does every participant in this new economy have to pay for, over and over again? It pointed to Cisco\u2019s routers in 1999 and to cell towers in 2007. Today it points to COBOL modernization contracts in Stuttgart, fraud-detection rails in S\u00e3o Paulo, and crop-disease models in Addis Ababa. That\u2019s not the most thrilling roadshow pitch, but is an actual investment thesis.<\/p>\n

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of\u00a0Fortune.<\/p>\n","protected":false},"excerpt":{"rendered":"The race to be the first frontier AI lab to reach public markets is on. Anthropic just\u00a0confidentially filed\u00a0for…\n","protected":false},"author":2,"featured_media":691184,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[27],"tags":[184,28,4759,112,1283,1513],"class_list":["post-691183","post","type-post","status-publish","format-standard","has-post-thumbnail","category-business","tag-anthropic","tag-business","tag-ipos","tag-markets","tag-openai","tag-spacex"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/691183","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=691183"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/691183\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/691184"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=691183"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=691183"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=691183"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}