Let me tell you a story. The entire global economy has accidentally tied itself to a company that loses billions of dollars a year, has never turned a profit, and just committed to spending $1.4 trillion it doesn’t have.

This isn’t hyperbole. This isn’t alarmist clickbait. No, I’m talking about OpenAI, a company that started as a nonprofit to “ensure artificial general intelligence benefits all of humanity,” and since then has morphed into a financial black hole so massive that its collapse would trigger a cascade more devastating than Lehman Brothers. And unlike the 2008 crisis, where at least we could pretend nobody saw it coming, this time we’re watching the house of cards assemble itself in real-time while everyone pretends it’s a cathedral.¹²³

The phrase “too big to fail” used to mean something. It described institutions so woven into the financial system that their collapse would trigger catastrophic contagion. Banks. Insurance giants. Now it describes a chatbot company that burns $15 billion a quarter and has convinced half the Fortune 500 that the future of mankind depends on its survival.⁴³⁵

How did we get here? And more importantly, what happens when this bubble pops? Not if, but when.

The Circular Economy of Artificial Demand

Let me break down the most brazenly circular deal in modern capitalism. In September 2025, Nvidia agreed to invest up to $100 billion in OpenAI. Sounds impressive, right? Except OpenAI is using that exact money to buy… Nvidia’s chips. Nvidia is literally funding its own sales. They write OpenAI a check, OpenAI writes a purchase order, and both companies report “revenue growth” to investors who apparently can’t do basic arithmetic.^67891011

But wait, there’s more! OpenAI also committed $300 billion to Oracle for data center capacity. Oracle, in turn, needs to spend roughly $40 billion buying, you guessed it, Nvidia chips to build those data centers. Meanwhile, Nvidia has invested $100 billion in OpenAI, which… do you see the problem yet?^7129134

The AI boom isn’t being driven by customers. It’s being driven by the AI companies investing in each other. Think of it as a financial Ouroboros eating its own tail while claiming it’s experiencing exponential growth.¹⁴⁶⁷

AMD got in on the action too, inking a deal to supply tens of billions worth of GPUs to OpenAI in exchange for OpenAI receiving warrants to become one of AMD’s largest shareholders, potentially a 10% equity stake. So OpenAI isn’t just a customer; it’s becoming an owner of its suppliers, who are also its investors, who are also its customers. If you tried to diagram this on a whiteboard, it would look like a conspiracy theorist’s fever dream.^8129107

Morgan Stanley published a report literally titled “AI: Mapping Circularity” that details how “suppliers are now financing their own customers, blurring traditional market boundaries and creating a highly interconnected ecosystem”. The report warns that “AI-related cash flows surge” while “transparency has not kept pace,” with complex off-balance-sheet partnerships making it “difficult for investors to gauge the true scale of interconnected risks”.⁶

Translation: Nobody has a fucking clue where the money is anymore. It’s just sloshing around in circles, inflating valuations with every lap.

The Economics Don’t Math

Let’s talk numbers now, because they’re utterly deranged.

OpenAI generated $5.5 billion in revenue in 2024. Sounds decent! Except it also lost $5 billion the same year. That’s a nice, round 100% loss ratio. By mid-2025, OpenAI was reportedly burning through $8 billion annually, with projections showing that could hit $45 billion by 2028. And remember that $1.4 trillion infrastructure commitment over eight years? That works out to $175 billion per year.⁵¹⁵¹⁶¹

Do the math. OpenAI’s current revenue run rate is around $13-20 billion annually (depending on who you ask, because Sam Altman keeps changing the number). To justify its current $500 billion valuation and service its infrastructure commitments, the company would need to grow revenue to somewhere between $100-577 billion by 2030.^31718195

For context, that’s more than the entire GDP of Finland. For a company that makes a chatbot.

Here’s the really fun part: Microsoft gets 20% of OpenAI’s revenue as part of their partnership deal. So OpenAI isn’t even keeping all the money it does make. And it won’t until some independent panel declares they’ve achieved “Artificial General Intelligence,” at which point (and I’m not making this up) the revenue-sharing stops but Microsoft can still use OpenAI’s IP to build their own AGI, subject to “compute thresholds”.^20212223

Are you fucking kidding me?

This is the financial equivalent of a perpetual motion machine, except instead of free energy, it produces quarterly earnings reports that make increasingly less sense.

When the Music Stops

The comparisons to previous bubbles are everywhere, but they’re all wrong. This is worse.

Yes, it looks like the dot-com bubble: absurd valuations, circular vendor financing, companies spending customer money they don’t have yet. Yes, it echoes the housing crisis: interconnected failures, too-big-to-fail dynamics, exotic financial instruments hiding risk. Yes, it mirrors crypto: hype-driven speculation, reality-disconnected valuations, retail investors buying into a narrative.

But here’s the difference: the dot-com bubble was mostly confined to tech stocks. The housing crisis started in mortgages. Crypto was, let’s be honest, monopoly money for tech bros. The AI bubble has metastasized into everything.

AI-related stocks now represent roughly 75-80% of S&P 500 gains since late 2022. The top five tech companies, all heavily invested in AI, control nearly 30% of the entire index’s value, the highest concentration in 50 years. Microsoft, Amazon, Google, and Meta are collectively spending over $300 billion this year on AI infrastructure, primarily to subsidize OpenAI, Anthropic, and a handful of other model makers.^{24252627282930}

When one of these dominos falls, they all fall.

Julien Garran, a UK analyst, calculated that the AI bubble is 17 times larger than the dot-com frenzy and four times bigger than the subprime mortgage crisis. MacroStrategy Partnership estimates current AI investment already exceeds those historical bubbles combined. And unlike previous bubbles where investors at least had the excuse of genuine ignorance, this time everyone from the Bank of England to the IMF to Goldman Sachs CEO David Solomon is openly saying “yeah, this is a bubble”.^{31322633273435}

Even Sam Altman, the poster boy of AI, admits it. At a press conference, he literally said “there are parts of AI that feel bubbly right now” while simultaneously announcing trillion-dollar spending plans. That’s like the captain of the Titanic pointing at the iceberg and saying, fuck it, let’s push on for more steam.²³⁶⁵

The Counterargument: This Time It’s Different

To be fair, the AI bulls aren’t idiots.

Marc Andreessen, the venture capitalist who never met a hype cycle he couldn’t rationalize, argues this is “Computer Industry V2,” a fundamental reinvention of computing that will create an era of radical abundance. Jensen Huang, Nvidia’s CEO (who, it must be said, has every financial incentive to keep this party going), claims we’re experiencing “three compounding exponentials” of AI demand that justify the spending.³⁷³⁸³⁹

Their argument goes like this: Yes, it’s a massive investment. Yes, many companies will fail. But unlike the dot-com era, where profitless startups burned VC money building pet food websites, today’s AI infrastructure is being bankrolled by the most profitable companies in human history. Microsoft, Google, Amazon, and Meta generate hundreds of billions in annual free cash flow. They can afford to experiment.^4041423537

Jeff Bezos, notably, called AI an “industrial bubble” but insisted the technology is “real” and will “pay off” long-term, comparing it to the biotech boom where many companies collapsed but lasting medical advances emerged. The optimists point out that AI is already producing measurable productivity gains. GitHub Copilot really does help programmers code faster, enterprises really are saving costs on customer service with chatbots, and the technology hasn’t even reached enterprise-wide deployment yet.^252743443537

And they’re right that this isn’t 1999. The companies building AI infrastructure have actual revenue, actual products, and actual users. ChatGPT has 700 million weekly active users. Claude is growing at unprecedented rates. These aren’t vaporware promises; they’re functioning products.

But here’s where the bull case falls apart: none of it is profitable. And more importantly, none of it is sustainably profitable.

The Subsidization Trap

The dirty secret of AI pricing is that nobody’s paying full freight.

Every major AI service is being offered below cost. OpenAI, Anthropic, Google, Microsoft. They’re all subsidizing usage to build market share, with the implicit promise that once everyone’s dependent on AI, they’ll gradually raise prices. It’s the Uber playbook: lose billions to kill competition, then jack up rates once you’ve created dependency.^42452843

The problem? There’s no evidence it’ll work.

MIT’s State of AI in Business 2025 report found that 95% of organizations investing in generative AI see no return. IBM reports enterprise AI ROI at just 5.9% against a 10% cost of capital, meaning companies are actively destroying value. Between 82-93% of AI projects fail, primarily due to poor strategy alignment and unrealistic expectations.^464744484943

This isn’t a technology problem: it’s an economics problem. The compute costs are astronomical, the electricity demand is unsustainable, and customers aren’t willing to pay enough to cover the infrastructure.^50515224

A brutal analysis circulating in financial circles calculated that AI datacenters built in 2025 will suffer $40 billion in annual depreciation while generating only $15-20 billion in revenue. The depreciation is literally double the revenue. That’s not a business model; that’s performance art.⁵¹⁵²

The Energy Apocalypse Nobody’s Pricing In

Let’s talk about the constraint everyone’s ignoring: physics.

AI training and inference require staggering amounts of electricity. We’re talking about U.S. electricity demand increasing by nearly 40% after two decades of flat consumption. Nvidia’s 2027 server racks will require 30 times the energy of existing racks as of 2025. Nuclear plants take 10-15 years from planning to operation. Natural gas facilities need 3-5 years minimum.^535224506

OpenAI’s infrastructure plans alone require enough electricity to power a major city. Where, exactly, is that coming from? The grid can’t handle it. Renewable energy can’t scale fast enough. And every community that hosts these datacenters is already seeing skyrocketing electricity prices.^549111624

This is the part where the AI bulls just… wave their hands and assume somebody else will solve it. “Oh, we’ll build small modular reactors!” Sure, with what regulatory approval timeline? “Fusion is coming!” Buddy, fusion has been 10 years away for the last 50 years.²⁴⁵³

The energy bottleneck isn’t hypothetical. It’s happening now. And it’s the ultimate constraint on the entire AI buildout.^52255024

The “Too Big to Fail” Trap

So what happens when this unravels? Not if, but when.

The nightmare scenario plays out like this: OpenAI, burning cash at an unsustainable rate, needs another funding round. But investors are getting nervous about the circular financing, the lack of profitability, and the growing realization that ChatGPT might not become the next operating system. The funding doesn’t materialize, or comes with brutal terms.⁴³⁵⁵

OpenAI begins cutting costs, scaling back infrastructure plans, potentially missing commitments to Oracle, AMD, Nvidia. Those companies, having booked OpenAI’s future spending as confirmed revenue in their projections, suddenly face massive write-downs. Their stock prices crater.¹²¹³⁴⁷

Because Microsoft holds 27% of OpenAI and depends on its models for Azure’s AI offerings, Microsoft’s valuation tanks. Nvidia, whose market cap ballooned to $5 trillion on the promise of AI demand, sees that thesis evaporate. Oracle, having issued $18 billion in bonds specifically to build OpenAI infrastructure, faces questions about debt serviceability.^{5657212858134206}

Now multiply that across the entire ecosystem. Amazon is deeply tied to Anthropic ($8 billion invested). Google has $3-4 billion in Anthropic and is offering “tens of billions” in compute credits. Every major cloud provider has made massive CapEx commitments predicated on sustained AI demand.^{59606162636465662524}

When the music stops, there aren’t enough chairs.

The Bank of England warned that AI valuations could trigger a “sharp market correction” similar to the dot-com crash. The IMF’s managing director said market expectations around AI could “turn abruptly,” with particularly severe impacts on developing economies. Goldman Sachs CEO David Solomon predicted a 10-20% drawdown in markets within the next year or two.^2633276734

And here’s the kicker: governments might actually have to bail them out. Yes, you read that right.

The Innovation Paradox

The really insidious part? This bubble is already killing innovation.

The AI market is consolidating at breakneck speed. In 2025, there were 427 AI startup acquisitions, most by Big Tech, with many well-funded startups positioning themselves for acquisition rather than independence because they can’t compete with subsidized services. Small AI companies can’t afford the infrastructure to train frontier models, can’t match the compute subsidies offered by hyperscalers, and can’t access the distribution channels controlled by platform companies.^6869704571

We’re watching the entire AI ecosystem concentrate into maybe five companies, all of which are unprofitable and depend on continued cheap capital. That’s not a recipe for innovation; that’s a recipe for stagnation.^69704572

Meanwhile, public trust in AI is cratering. The combination of overhype, underdelivery, and growing awareness of the financial engineering behind the boom is creating exactly the kind of skepticism that will slow adoption even if the technology improves. Robodebt in Australia, algorithmic bias scandals, and high-profile AI failures are all contributing to a “trust deficit” that could take years to rebuild.^73747576

The tragedy is that AI probably will be transformative long-term. But by tying it to an unsustainable financial structure, we’re ensuring that when the crash comes, it’ll set the entire field back a decade.^35554650

What Happens Next

Over the next 3-5 years, watch for these inflection points.

The Profitability Reckoning (2026-2027): AI companies will be forced to raise prices or admit their business models don’t work. Enterprises will face the choice between accepting massive cost increases or walking away from implementations that haven’t delivered ROI. This is where we’ll discover whether AI demand is real or subsidized.^45444843

The Infrastructure Overhang (2027-2028): As billions in CapEx comes online, we’ll see whether actual usage justifies the build-out. My bet? We’ll discover we’ve built 10-15 years ahead of demand, just like the telecom bubble. Utilization rates will be abysmal, depreciation will crush margins, and hyperscalers will be stuck with stranded assets.^774237515224

The Consolidation Wave (2026-2029): Most AI startups will be acquired, fail, or pivot to niche applications. The companies that survive will be those with genuine unit economics, likely enterprise-focused tools with clear ROI, not consumer chatbots burning cash to acquire users.^70716945

The Regulatory Crackdown (ongoing): As the systemic risks become undeniable, regulators will step in. The FTC is already investigating the Microsoft-OpenAI and Amazon-Anthropic partnerships. Expect antitrust action, potentially forced divestitures, and new rules around vendor financing and circular investment structures.^7872795569

The Trust Collapse (ongoing): Every failed AI implementation, every hallucination that causes real harm, every dollar wasted on pilots that don’t scale. They all accumulate into a credibility crisis that will make the next AI wave much harder.^7475768073

Here’s what won’t happen: OpenAI will not go bankrupt in any traditional sense. They’re too interconnected. If they stumble, Microsoft will absorb them, or the government will structure some sort of “public-private partnership” that’s bailout-by-another-name. The losses will be socialized, the gains will remain privatized, and we’ll all pretend this was inevitable. Business as usual.

The Lesson We Won’t Learn

The AI bubble is a perfect case study in how late-stage capitalism has broken our collective ability to distinguish investment from speculation, innovation from hype, and strategic necessity from collective delusion.

Everyone involved knows it’s a bubble. Sam Altman knows. Jensen Huang knows. Every VC writing checks knows. The Bank of England published a report literally saying “this is a bubble”. And yet the money keeps flowing, because the incentives are so misaligned that rationality has become optional.^413327145526

VCs invest because they’re terrified of missing the next Google. Corporations invest because their competitors are investing. Cloud providers invest because they can book the spending as revenue. Chip makers invest because they can inflate sales. Executives approve budgets because they’ll be at a different company when it all collapses. Nobody has an incentive to be the adult in the room.

This is the fundamental sickness at the heart of modern tech. We’ve built an entire ecosystem that rewards short-term value extraction over long-term value creation. We’ve created markets where financial engineering matters more than actual products. We’ve normalized valuations so disconnected from cash flows that CFOs sound like astrologers explaining their projections.

And the worst part? When it crashes, we’ll bail out the people who caused it, shrug, and do it all over again with whatever the next hype cycle is.

OpenAI isn’t too big to fail. It’s too interconnected to fail. And that’s worse. Because it means we’ve accidentally built a financial weapon of mass destruction and handed the detonator to a company whose business model is “burn money now, figure out profits later”.

The AI bubble will pop. The only questions are when, how badly, and whether we’ll be smart enough to learn anything from it.

Spoiler: we won’t.

^{81828384858687888990919293949596979899}

Footnotes

1. https://www.morningbrew.com/stories/2025/11/08/is-openai-putting-the-ai-in-too-big-to-fail ↩ ↩² ↩³

2. https://www.bbc.com/news/articles/cz69qy760weo ↩ ↩²

3. https://www.thealgorithmicbridge.com/p/you-have-no-idea-how-screwed-openai ↩ ↩² ↩³ ↩⁴

4. https://www.rte.ie/news/business/2025/1108/1542794-ai-bubble-tech/ ↩ ↩² ↩³ ↩⁴

5. https://observer.com/2025/11/openai-revenue-model/ ↩ ↩² ↩³ ↩⁴

6. https://clfi.co.uk/insights/ai-economy-circular-investment-energy-demand/ ↩ ↩² ↩³ ↩⁴ ↩⁵

7. https://www.ainvest.com/news/billion-dollar-ai-loop-big-tech-creating-fueling-bubble-2511/ ↩ ↩² ↩³ ↩⁴ ↩⁵

8. https://www.purposeinvest.com/thoughtful/ai-capex-boom-roundtrip-roadshow-or-virtuous-cycle ↩ ↩²

9. https://www.theregister.com/2025/11/04/the_circular_economy_of_ai/ ↩ ↩² ↩³ ↩⁴

10. https://www.bloomberg.com/news/features/2025-10-07/openai-s-nvidia-amd-deals-boost-1-trillion-ai-boom-with-circular-deals ↩ ↩²

11. https://openai.com/index/openai-nvidia-systems-partnership/ ↩ ↩²

12. https://www.nbcnews.com/business/economy/openai-nvidia-amd-deals-risks-rcna234806 ↩ ↩² ↩³

13. https://www.cnbc.com/2025/10/15/a-guide-to-1-trillion-worth-of-ai-deals-between-openai-nvidia.html ↩ ↩²

14. https://finance.yahoo.com/news/very-troubling-ais-self-investment-spree-sets-off-bubble-alarms-on-wall-street-160524518.html ↩ ↩²

15. https://www.aiprm.com/openai-statistics/ ↩

16. https://truthout.org/articles/with-big-tech-talking-government-backing-has-openai-become-too-big-to-fail/ ↩ ↩²

17. https://www.reuters.com/business/openai-hits-12-billion-annualized-revenue-information-reports-2025-07-31/ ↩

18. https://www.wheresyoured.at/where-is-openais-money-going/ ↩

19. https://www.youtube.com/watch?v=lWc3mM9sHXQ ↩

20. https://www.bloomberg.com/news/articles/2025-10-28/microsoft-to-get-27-of-openai-access-to-ai-models-until-2032 ↩ ↩²

21. https://www.cnbc.com/2025/10/28/open-ai-for-profit-microsoft.html ↩ ↩²

22. https://blogs.microsoft.com/blog/2025/10/28/the-next-chapter-of-the-microsoft-openai-partnership/ ↩

23. https://www.reuters.com/business/microsoft-openai-reach-new-deal-allow-openai-restructure-2025-10-28/ ↩

24. https://siliconangle.com/2025/11/09/ai-factories-face-long-payback-period-trillions-upside/ ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶ ↩⁷ ↩⁸

25. https://www.economist.com/leaders/2025/09/11/what-if-the-3trn-ai-investment-boom-goes-wrong ↩ ↩² ↩³ ↩⁴

26. https://finance.yahoo.com/news/bank-england-imf-warn-ai-115111105.html ↩ ↩² ↩³ ↩⁴

27. https://economictimes.com/markets/stocks/news/is-the-becoming-a-bubble-why-goldman-jpmorgan-imf-are-sounding-the-alarm/articleshow/124443190.cms ↩ ↩² ↩³ ↩⁴ ↩⁵

28. https://www.linkedin.com/posts/deepak-lathi-1136262_the-ai-market-is-driven-by-a-vendor-financing-activity-7381326787177422848-xFVd ↩ ↩² ↩³

29. https://www.ft.com/content/f8cd239e-287c-4e3c-bfae-8c4acec7ac34 ↩

30. https://www.linkedin.com/posts/krismcgee_the-500-billion-question-what-if-ai-doesnt-activity-7383889271662788609-W2Vx ↩

31. https://www.reddit.com/r/technology/comments/1o4t6o2/the_ai_bubble_is_17_times_the_size_of_the_dotcom/ ↩

32. https://www.cnn.com/2025/10/18/business/ai-bubble-analyst-nightcap ↩

33. https://www.cnbc.com/2025/10/09/imf-and-bank-of-england-join-growing-chorus-warning-of-an-ai-bubble.html ↩ ↩² ↩³

34. https://discoveryalert.com.au/ai-bubble-experts-concerned-2025/ ↩ ↩² ↩³

35. https://nationalcioreview.com/articles-insights/extra-bytes/bezos-defends-ai-growth-as-analysts-warn-of-unsustainable-surge/ ↩ ↩² ↩³ ↩⁴

36. https://www.cnbc.com/2025/08/18/openai-sam-altman-warns-ai-market-is-in-a-bubble.html ↩

37. https://www.theneuron.ai/explainer-articles/the-bull-and-bear-case-for-the-ai-bubble-explained ↩ ↩² ↩³ ↩⁴

38. https://www.youtube.com/watch?v=Y7dwbJ0AtUA ↩

39. https://fortune.com/2025/10/08/billionaire-investor-marc-andreesssen-ai-jobs-personal-finance-careers-costs-plummet-healthcare-law/ ↩

40. https://www.janushenderson.com/en-dk/investor/article/ai-versus-the-dotcom-bubble-8-reasons-the-ai-wave-is-different/ ↩

41. https://hbr.org/2025/10/is-ai-a-boom-or-a-bubble ↩ ↩²

42. https://edelweisscapital.substack.com/p/dot-com-bubble-vs-the-ai-boom ↩ ↩² ↩³

43. https://www.consultancy-me.com/news/11386/the-ai-investment-paradox-when-revolutionary-rhetoric-meets-economic-reality ↩ ↩² ↩³ ↩⁴

44. https://www.okoone.com/spark/strategy-transformation/why-ai-projects-keep-burning-cash-and-how-to-fix-it/ ↩ ↩² ↩³

45. https://www.nofriction.io/intel/aimarket.html ↩ ↩² ↩³ ↩⁴ ↩⁵

46. https://www.wired.com/story/ai-bubble-will-burst/ ↩ ↩²

47. https://themoralalgorithm.com/record-profits-mass-layoffs-the-ai-lie-fueling-our-next-systemic-collapse/ ↩

48. https://www.deloitte.com/dk/en/issues/generative-ai/ai-roi-the-paradox-of-rising-investment-and-elusive-returns.html ↩ ↩²

49. https://thedataexperts.us/insights/ai-investment-roi-analysis-2025 ↩

50. https://www.latimes.com/business/story/2025-08-20/say-farewell-to-the-ai-bubble-and-get-ready-for-the-crash ↩ ↩² ↩³ ↩⁴

51. https://www.firstlinks.com.au/simple-maths-says-the-ai-investment-boom-is-doomed ↩ ↩² ↩³

52. https://research.contrary.com/deep-dive/the-economics-of-ai-build-out ↩ ↩² ↩³ ↩⁴ ↩⁵

53. https://businessengineer.ai/p/ai-technology-bubble-analysis ↩ ↩²

54. https://www.lumenova.ai/blog/ai-systemic-risks-existential-risks/ ↩

55. https://insights.som.yale.edu/insights/this-is-how-the-ai-bubble-bursts ↩ ↩² ↩³ ↩⁴

56. https://finance.yahoo.com/news/microsoft-and-openais-new-for-profit-deal-gives-windows-maker-27-stake-142521255.html ↩

57. https://huntnewsnu.com/89655/editorial/column-will-the-ai-bubble-be-too-big-to-fail/ ↩

58. https://www.bbc.com/news/articles/cvgv38py7ewo ↩

59. https://www.bloomberg.com/news/articles/2025-10-21/anthropic-google-in-talks-on-cloud-deal-worth-tens-of-billions ↩

60. https://www.emarketer.com/content/google—anthropic-partner-aws-faces-reliability-doubts ↩

61. https://www.anthropic.com/news/anthropic-amazon-trainium ↩

62. https://www.reuters.com/business/retail-consumer/anthropic-google-talks-cloud-deal-worth-tens-billions-bloomberg-news-reports-2025-10-21/ ↩

63. https://www.aboutamazon.com/news/aws/amazon-invests-additional-4-billion-anthropic-ai ↩

64. https://www.economist.com/business/2025/07/31/who-will-pay-for-the-trillion-dollar-ai-boom ↩

65. https://www.economist.com/finance-and-economics/2025/08/18/how-americas-ai-boom-is-squeezing-the-rest-of-the-economy ↩

66. https://www.cnbc.com/2025/10/23/anthropic-google-cloud-deal-tpu.html ↩

67. https://fortune.com/2025/10/09/as-ai-bubble-warnings-mount-a-23-year-olds-1-5-billion-hedge-fund-shows-how-prophecy-turns-into-profits/ ↩

68. https://cloudwars.com/ai/in-startup-ecosystem-ais-impact-ranges-from-investment-analysis-to-product-development/ ↩

69. https://www.lowtouch.ai/ai-startup-ma-heats-up-what-427-acquisitions-in-2025-mean-for-enterprises/ ↩ ↩² ↩³ ↩⁴

70. https://www.forbes.com/sites/elainepofeldt/2025/06/15/ai-reshapes-startup-ecosystems-around-the-world-despite-the-funding-winter/ ↩ ↩² ↩³

71. https://microventures.com/startup-consolidation-the-rise-of-m-and-a-in-2025 ↩ ↩²

72. https://frontierai.substack.com/p/untangling-concerns-about-consolidation ↩ ↩²

73. https://www.pmc.gov.au/resources/long-term-insights-briefings/how-might-ai-affect-trust-public-service-delivery/landscape ↩ ↩²

74. https://institute.global/insights/tech-and-digitalisation/what-the-uk-thinks-about-ai-building-public-trust-to-accelerate-adoption ↩ ↩²

75. https://arxiv.org/pdf/2102.04221.pdf ↩ ↩²

76. https://www.brookings.edu/articles/what-the-public-thinks-about-ai-and-the-implications-for-governance/ ↩ ↩²

77. https://www.economist.com/business/2025/09/30/the-murky-economics-of-the-data-centre-investment-boom ↩

78. https://law.stanford.edu/2025/03/21/ai-partnerships-beyond-control-lessons-from-the-openai-microsoft-saga/ ↩

79. https://www.ftc.gov/news-events/news/press-releases/2024/01/ftc-launches-inquiry-generative-ai-investments-partnerships ↩

80. https://mbs.edu/news/global-study-reveals-trust-of-ai-remains-a-critical-challenge ↩

81. https://aimagazine.com/news/behind-microsoft-openais-redefined-partnership-in-ai ↩

82. https://www.anthropic.com/news/expanding-our-use-of-google-cloud-tpus-and-services ↩

83. https://www.nytimes.com/2025/10/07/business/dealbook/openai-nvidia-amd-investments-circular.html ↩

84. https://e27.co/circular-capital-inside-the-closed-loop-ecosystem-propelling-and-distorting-the-ai-boom-20250925/ ↩

85. https://www.reuters.com/legal/transactional/ai-startup-valuations-raise-bubble-fears-funding-surges-2025-10-03/ ↩

86. https://www.tbsnews.net/tech/ai-bubble-about-burst-1280901 ↩

87. https://www.linkedin.com/posts/laurencemussio_what-if-the-3trn-ai-investment-boom-goes-activity-7372049539802992640-J0OF ↩

88. https://www.wheresyoured.at/openai-is-a-systemic-risk-to-the-tech-industry-2/ ↩

89. https://www.cnbc.com/2025/11/07/ai-valuation-fears-grip-investors-as-tech-bubble-concerns-heighten.html ↩

90. https://arxiv.org/html/2412.07780v1 ↩

91. https://logisticsviewpoints.com/2025/11/03/33669/ ↩

92. https://cloudsummit.eu/blog/microsoft-openai-agreement-dawn-multi-vendor-enterprise-ai ↩

93. https://mtsoln.com/blog/ai-news-727/ai-bubble-dont-throw-the-baby-out-with-the-bathwater-4382 ↩

94. https://www.wsj.com/tech/ai/is-openai-becoming-too-big-to-fail-400bac2c ↩

95. https://blogs.microsoft.com/blog/2025/01/21/microsoft-and-openai-evolve-partnership-to-drive-the-next-phase-of-ai/ ↩

96. https://www.dw.com/en/ai-bubble-about-to-pop-as-returns-on-investment-fall-short-chatgpt-microsoft-nvidia-grok-elon-musk/a-74636881 ↩

97. https://www.telegraph.co.uk/business/2025/11/10/ai-cant-be-allowed-to-become-too-big-to-fail/ ↩

98. https://openai.com/index/next-chapter-of-microsoft-openai-partnership/ ↩

99. https://www.reuters.com/business/finance/opinions-split-over-ai-bubble-after-billions-invested-2025-10-16/ ↩