OpenAI Faces $207 Billion Funding Gap Despite Massive Cloud Computing Commitments

HSBC spies $207B crater in OpenAI's expansion goals

Gap threatens Oracle, Microsoft, and Amazon despite optimistic forecasts of 3 billion ChatGPT users by 2030 OpenAI needs to secure $207 billion in new financing by 2030 to fulfill its expansion plans, according to HSBC Global Investment Research - a challenge that could ripple across Big Tech. The funding shortfall emerged after OpenAI committed $300 billion to Oracle, $250 billion to Microsoft, and $38 billion to AWS for cloud computing services. Even with HSBC's updated revenue projections, which increased 4 percent from earlier estimates, the gap remains substantial. In a research paper HSBC shared with The Register, it warns OpenAI "would need $207 billion of new financing by 2030. One unknown parameter is the flexibility that OpenAI may have to adjust its commitment vs effective demand or financial capacity. Capital injections, debt issuance, or higher revenue than in our model would help closing the funding gap." HSBC predicts that OpenAI's ChatGPT consumer products will attract 3 billion regular users by 2030, up from 800 million last month, and equivalent to 44 percent of the world's population over 15 years old. The bank also forecasts higher subscription rates (10 percent versus 8 percent) and increased corporate demand for APIs and licensing, plus a larger share of digital advertising revenue for AI companies. Still, these assumptions leave OpenAI with a significant funding gap. The company could bridge that through additional user growth. Another half a billion users would generate a $36 billion boost in revenue, for example. It could improve compute efficiency, raise more capital from its shareholders (hello Microsoft and SoftBank), or increase external debt. Failure to close the funding gap would hit OpenAI's nearest and dearest tech alliances the hardest. "The most exposed partners to OpenAI success or failure under our coverage are Oracle, Microsoft, Amazon, Nvidia, and AMD, and so is SoftBank, given its 11 percent stake in OpenAI," HSBC said. The report rates those first four tech giants as "buy." However, Oracle has already experienced volatility since signing its $300 billion deal with OpenAI. After announcing the deal in September, part of $455 billion in cloud contracts won - much related to AI compute - Big Red's share price surged 30 percent, briefly making co-founder Larry Ellison the world's richest person. Investment analysts were enthused. Oracle has since lost all the value it gained in that period, and Ellison has had to hand back his crown. He now ranks third after Google/Alphabet's Larry Page and Elon Musk. Oracle and the other tech giants OpenAI have made promises to will be hoping the funding gap closes sooner rather than later. ®

OpenAI needs to raise at least $207bn by 2030 so it can continue to lose money, HSBC estimates

OpenAI is a money pit with a website on top. That much we know already, but since OpenAI is a private company, there's a lot of guesswork required when estimating the depth of the pit. HSBC's US software and services team has today updated its OpenAI model to include the company's $250bn rental of cloud compute from Microsoft, announced late in October, and its $38bn rental of cloud compute from Amazon announced less than a week later. The latest two deals add an extra four gigawatts of compute power to OpenAI's requirements, bringing the contracted amount to 36 gigawatts. Based on a total cumulative deal value of up to $1.8tn, OpenAI is heading for a data centre rental bill of about $620bn a year -- though only a third of the contracted power is expected to be online by the end of this decade. To check OpenAI ability to pay, HSBC's team first had to build a model to forecast revenues. Its starting point is to put user numbers on an S-curve that by 2030 reaches 3bn, "equivalent to 44 per cent of the world's adult population" ex China. That's versus an estimated total user base last month of approximately 800mn: Advertising, agentic AI and possibly even Jony Ive's thing can contribute to revenue by the end of the decade, For now, the business is mostly cajoling this user base to sign up for subscriptions. LLM subscriptions will become "as ubiquitous and useful as Microsoft 365", HSBC says. It models that by 2030, 10 per cent of OpenAI users will be paying customers, versus an estimated 5 per cent currently. The team also assumes LLM companies will capture 2 per cent of the digital advertising market in revenue, from slightly more than zero currently. What results is gangbusters revenue growth: ... but with a parallel rise in costs, meaning OpenAI is expected to still be subsidising its users well into next decade: ... meaning each new OpenAI fundraise will be for shovelling cash to data centre owners: For what it's worth, we can summarise a few of the assumptions HSBC is making for the estimates above: The bottom line is that, for OpenAI, it's nowhere close to enough. HSBC's model assumes that OpenAI's rental costs will be a cumulative $792bn between the current year and 2030, rising to $1.4tn by 2033. The projection matches OpenAI's eight-year guidance that CEO Sam Altman is exasperated at being asked to discuss. OpenAI's cumulative free cash flow to 2030 may be about $282bn, it forecasts, while Nvidia's promised cash injections and the disposal of AMD shares can bring in another $26bn. The broker also includes OpenAI's $24bn of undrawn debt and equity facilities and, at the 2025 mid-year point, its $17.5bn of available liquidity. Squaring the first total off against the second leaves a $207bn funding hole, to which HSBC adds a $10bn cash buffer for safety's sake. These estimates might prove overly cautious, though guessing how is a finger-in-the-air exercise. Each extra 500mn users OpenAI can grab will add about $36bn to cumulative revenue between now and 2030, while converting 20 per cent of the customers to paid subscriptions might bring in an additional $194bn over the same period, HSBC says. Assumptions for LLM spend and computing costs are flexed in similar ways, though the possibility of OpenAI chancing on Artificial General Intelligence is not put through the model. If revenue growth doesn't exceed expectations and prospective investors turn cautious, OpenAI would need to make some hard decisions. Oracle has spooked debt markets, Microsoft's support for OpenAI has been a bit flip-flop lately, and the next-biggest shareholder is SoftBank. The best worst option might be to call in some favours and walk away from data centre commitments, either before or at the usual contracted period of four to five years. HSBC says: Given the interlaced relationships between AI LLM, cloud, and chips companies, we see a case for some degree of flexibility at least from the larger players (less so for the neo clouds): less capacity would always be better than a liquidity crisis. What might not be clear from the above is that the HSBC software team is very, very bullish on AI as a concept. Here's an entirely representative section of the note: We expect AI to penetrate every production process and every vertical, with a great potential for productivity gains at a global level. [ . . . ] Some AI assets may be overvalued, some may be undervalued too. But eventually, a few incremental basis points of economic growth (productivity-driven) on a USD110trn+ world GDP could dwarf what is often seen as unreasonable capex spending at present. And when it's put like that, is $207bn to tide things over really such a big ask?

OpenAI Is Just $200 Billion Away From Still Losing Money, HSBC Says

OpenAI has committed more than $1.4 trillion that it will spend on building out its data center infrastructure to power the development and deployment of its AI models over the next eight years. Notably, OpenAI does not have $1.4 trillion. Also notable is the fact that the company doesn't make that much money. That means it'll remain reliant primarily on fundraising rounds to pay the bills as they come due. According to a report from the Financial Times, all OpenAI has to do is raise $207 billion by 2030 in order to keep operating at a deep loss. Easy peasy! The report cites a recent analysis of OpenAI's finances from HSBC, the British multinational financial services giant, which has taken into account the AI startup's planned spending on infrastructure, compute, and energy costs, as well as its projected revenue to offset all those costs. The bank estimates that OpenAI will run up a bill of $620 billion per year on data center costs, with a caveat that it has signed contracts for more computing power than is actually available at the moment. Then it created an estimate for the company's customer reach, which is currently reported to be 800 million by OpenAI's count and will reach three billion by 2030 under HSBC's model. The bank generously estimates that OpenAI will convert 10% of that reach into paying customers, double its current rate of 5%. Those estimates are more generous than OpenAI's reported internal ones, which have the company reaching 2.6 billion and converting 8.5% of them to paying subscribers by the end of the decade. HSBC also tosses OpenAI some advertising revenue under the assumption that LLM firms will take about 2% of the total digital ad market in the coming years. With all that, HSBC projects that OpenAI will hit about $215 billion in annual revenue by 2030. That, once again, tops OpenAI's own projections, which reportedly put it at about $200 billion annually by the end of the decade. Both models are calling for what is basically unprecedented growth, but let's roll with it. Taking into account OpenAI's current cash flow plus its projected expectation-busting growth projections would still leave the company with a funding deficit of $207 billion. Per HSBC, the company will need to raise that much just to continue operating in the red. OpenAI has options to shrink that funding gap, though none of them are all that appealing. The company could back out of some of its data center commitments to shrink its expenditures, though it might not provide much comfort to investors who are counting on something closer to infinite growth. It could also blow past even the generous revenue projections made by HSBC, which seems unlikely and not really something it can just manufacture. If generating revenue were easy, the company would be doing it. Then there's the other option that OpenAI execs started floating before immediately getting push back: get a government bailout. Contingency plans usually aren't a bad idea, but it probably doesn't instill a whole lot of confidence that you're planning on the possibility of failing so hard that you might drag the entire economy down with you.

'It's not just the hyperscalers' free cash flow anymore.' Debt related to OpenAI's computing needs is moving credit markets. | Fortune

Companies supplying data centers, chips, and "compute" processing power to OpenAI have taken on about $96 billion in debt to fund their operations, according to an analysis by the Financial Times. The news highlights the AI sector's increasing reliance on debt and its growing dependence on loss-making AI startup OpenAI in particular. Currently, the revenues being generated by AI companies and many of the data center operators that are rapidly expanding in order to serve them, are nowhere near big enough to cover their build-out costs. OpenAI has made $1.4 trillion in commitments to procure the energy and computing power it needs to fuel its operations in the future. But it has previously disclosed that it expects to make only $20 billion in revenues this year. And a recent analysis by HSBC concluded that even if the company is making more than $200 billion by 2030, it will still need to find a further $207 billion in funding to stay in business. Here's the FT's breakdown of the debt that OpenAI's partners have taken on: The increased use of debt to fund AI is a relatively new development -- prior to this year most AI build-out was funded by cash straight from the balance sheets of big tech companies, such as Microsoft, Alphabet, Amazon, and Meta. How CoreWeave services its debt will be of particular interest to investors. The company reported $3.7 billion in current debt, $10.3 billion in non-current debt, and $39.1 billion in future lease agreements for data centers, in its Q3 earnings report. The company said it expected to make only $5 billion in revenue this year. All that extra investment-grade (IG) corporate debt is having a material effect on the credit markets, a recent research note from BofA analysts Yuri Seliger and Sohyun Marie Lee said. "This week (the week prior to Thanksgiving) is typically the last week of the year with heavy IG supply. And 2025 supply is ending the year with a bang. We are tracking about $50bn for this week and about $220bn over the prior four weeks - about 70% higher than the typical volume for this time of year," they said. "This year ... hyperscalers added another $63bn. This suggests the entire increase in supply this year is explained by [debt-funded M&A deals] and hyperscaler activity." The increased supply of debt from tech companies is moving "spreads" -- the extra interest yield demanded by buyers of debt above the notional risk-free rate -- in the credit default swap (CDS) market, according to Deutsche Bank. CDS act as a kind of insurance policy on corporate debt, paying the holders in the event the creditor defaults. If the yields on CDS increase, it signals that the market believes the likelihood of default has also gone up. "The moves have been notable: Oracle's 5yr CDS has widened by about +60bps to 104bps since late September and CoreWeave by roughly +280bps to around 640bps since September," Deutsche's Jim Reid said in a recent note. "It's hard to know yet whether this shift will have meaningful long-term implications, but the last few weeks clearly mark a new phase of the AI boom -- one in which investors are increasingly looking to hedge their risk, and one where public credit markets are being called upon to fund growing capex needs. It's not just the hyperscalers' free cash flow anymore," he said.

OpenAI's Financial Situation Will Cause a Nauseating Sensation in the Pit of Your Stomach

OpenAI isn't just burning through cash. It's lighting an entire mountain of money on fire. But since it's not a publicly traded company, the extent of that mountain remains difficult to gauge. But clues periodically emerge: as the Financial Times reports, for instance, the company recently signed a staggering $250 billion rental agreement with Microsoft -- as well as a $38 billion contract with Amazon, less than a week later. According to HSBC, whose software and services team issued an update to its financial model of OpenAI, the company will be spending a nauseating $620 billion per year on renting data center capacity to power its AI models alone. That's despite only a third of the total contracted amount of 36 gigawatts actually scheduled to come online before 2030. It's a precarious moment, with lenders expecting a blockbuster growth in revenue -- an enormous ask that will require OpenAI to accomplish things unprecedented in business history. Meanwhile, experts are warning of an AI bubble that has grown so much that it's proping up the entire US economy. If it were to pop, the consequences could be disastrous, with the discussion shifting towards whether firms can even survive the next couple of years as spending on data centers continues to rise precipitously. And that's not the only looming challenge. OpenAI also has to contend with increased competition as well, with Google's Gemini 3 throwing down the gauntlet earlier this month. That's more naysaying from HSBC, by the way, which expects OpenAI's consumer market share to drop substantially by the end of the decade. Whether OpenAI will be able to pay its bills in the upcoming years remains hazy at best. According to HSBC, the company will need to reach three billion ChatGPT users by 2030, a steep goal considering userbase growth is already plateauing. According to CEO Sam Altman, the company has around 800 million weekly active users. As the FT reported last month, paying ChatGPT subscribers represent roughly 70 percent of the outfit's annual recurring revenue -- yet only a pitiful five percent of users are currently willing to pay for a subscription. New revenues will also have to be poured into further data center build-outs to support new users, as the FT explains, in a vicious cycle that could heavily eat into OpenAI's margins. If things were to go south, HSBC suggests that OpenAI will end up changing its data center commitments. "Less capacity would always be better than a liquidity crisis," the broker wrote. While HSBC remained bullish about the prospect of enormous "productivity-driven" economic growth that could "dwarf what is often seen as unreasonable [capital expenditure] spending at present," OpenAI still has to pull it off. And investors are already asking some tough questions over AI companies' sky-high valuations and meager revenues, with AI chipmaker Nvidia's shares falling for several weeks now -- despite posting better-than-expected quarterly earnings. And Nvidia is the one selling shovels during the ongoing AI gold rush. OpenAI has a much steeper hill to climb, since it has to create a profitable service while paying for all those shovels. In a telling moment earlier this month, Altman became irate after being asked by podcaster and OpenAI investor Brad Gerstner how a company "with $13 billion in revenues" can "make $1.4 trillion of spend commitments." "If you want to sell your shares, I'll find you a buyer," Altman shot back. "Enough."

OpenAI's AI money pit is much deeper than we thought. Here's why it matters

We live in strange times. The FT reported this week that ChatGPT maker OpenAI, which was responsible for kickstarting the surge of interest in Artificial Intelligence (AI) back in 2022, is in a deeper hole than even its harshest critics realize. According to the paper, OpenAI "needs to raise at least $207 billion by 2030 so it can continue to lose money". The paper's Alphaville service describes the company as a "burning platform" and "a money pit with a website on top". Strong words. That assessment came via HSBC's software and services team in the US, which has been tracking the company's numbers. By their calculations, OpenAI is heading for data center rental costs of $620 billion a year, rising to $1.4 trillion by 2033 - which, incidentally, is more than the GDP of Saudi Arabia ($1.2 trillion). Remember, this is the company that describes itself as "the world's biggest philanthropy", which is "curing cancer, or whatever" in the cringeworthy words of Chief Executive Officer (CEO), Sam Altman. According to Altman, OpenAI's annualized revenue is on track to hit just $20 billion this year. Impressive by most standards, but that is less than 10% of the combined $288 billion cost of its data center deals with Microsoft ($250 billion) and Amazon ($38 billion), which were announced in October. OpenAI's predicted compute costs of $1.4 trillion in seven-to-eight years' time are 70 times its current revenues. And that does not include any of its other costs, such as staffing, R&D, energy, water, and property. A money pit by any measure, therefore. And bear in mind, those compute costs may be an underestimate if user numbers explode; I have seen figures as high as $3 trillion suggested by some analysts. There are already over 5,500 data centers in the US, with growing alarm at their environmental impacts locally, so it is possible that community pressure may force up compute costs further and limit the market's expansion. Plus, dozens of 'me too' apps are launching all the time, alongside hyperscalers' own platforms, so competition for capacity can only become more intense. But back to OpenAI. Even if user numbers hit three billion by 2030, and even if the company can cajole 10% of those customers into being paying subscribers (the figure currently stands at five percent), and even if generative AI companies can capture two percent of digital advertising revenue (they are just above zero at present), OpenAI's business will - inevitably - largely be about "shovelling cash to data center owners" for the foreseeable future, the FT notes. This is why OpenAI is desperate to offload its costs onto others, even by persuading naïve national governments, such as the UK, to use taxpayers' money. And it is why OpenAI is also hell-bent on launching as many new apps and services as possible: video tool Sora, search engine Atlas, a rumoured music-generating app, plus the anticipated Johnny Ive-designed hardware assistant, which will doubtless be positioned as an iPhone killer. It's all about driving revenue, by all and any means. At this point, however, we should remember that no company on Earth comes close to making enough revenue to cover such stratospheric costs as OpenAI's. For many years, US retail giant Walmart has been the world's biggest company by revenue, and in 2025 it reported income of $680.9 billion - only slightly more than OpenAI's predicted annual compute costs this decade. But we are talking about the technology sector, of course, a vertical built almost entirely on belief, share price, and venture capital valuation - a market where revenue and (whisper it) profit are far less important than market capitalization. There are cloud companies out there that are worth billions of dollars, but which lose hundreds of millions a year, and have never turned a profit this century. Indeed, this is why nobody cares that Walmart is the most successful company on the planet in terms of selling products and services to customers: with a market cap of just $853 billion, it is a minnow compared with the likes of NVIDIA, Apple, Microsoft, Amazon, Broadcom, Meta, and Tesla, which each have market caps of well over a trillion dollars - last month NVIDIA briefly hit $5 trillion. So, OpenAI has to IPO to stand any chance of surviving as a sustainable business, and it believes it could raise as much as $1 trillion by doing so. Perhaps it will, if it can shake off the spectre of Elon Musk's rage. But it must then exceed that valuation long into the future. And lurking beneath investors' belief that the world's deepest money pit will make them a profit is a deeply dysfunctional company led by a man whose reputation for trust has long been in doubt. As I reported last month, OpenAI is thought to be shifting to an advertising model in another attempt to fill its gaping revenue hole - the chasm between the billions that come in and the trillions that go out. My earlier November report quoted an X user and AI fan called King of Prompts, who said: ChatGPT is about to introduce ads. You spent months telling it about your divorce, your new job search, your kid's health problems, where you vacation, what you're afraid of. OpenAI just hired 630 Meta employees - 20% of their entire company - to figure out how to turn those memories into ads. Projected revenue: $25 billion by 2029. The same CEO who called this scenario 'dystopic' and a 'trust-destroying moment' is now exploring it anyway, because the company burns $8.5 billion annually and won't see profit until 2029 without a new revenue stream. But as we have seen, the figures he quoted don't even come close to the financial reality or the size of OpenAI's problems - put simply, it may be hot, but only because it is on fire. As I noted last month, another user called the reported plans a "monetization of trust", with ChatGPT memorizing all a user's conversations. As King of Prompts described it, "every vulnerable moment, where you live, your pets' names, your family members, your dietary restrictions, your career struggles, your health anxieties." What a revolting business. Yet belief in it is, currently, sustaining the US stock market, if one considers the circular economy that has grown around the AI hardware, software, and services sectors. The tech industry is largely thriving by selling product and renting capacity to itself, while investors sit on their hands and hope. However, not discussed in the Alphaville piece is the thorny issue of copyright - the scraping of proprietary content to train AI models - which I believe is the real timebomb beneath OpenAI's business. In this regard, October's $1.5 billion settlement by AI rival Anthropic of the class action brought against it by US authors was the first sign of existential danger. To recap, authors sued Anthropic for scraping roughly 500,000 copyrighted books from the millions of documents on free/pirate resource Library Genesis (aka LibGen) to train its Claude Large Language Model (LLM). Other companies are known to have done the same, such as Meta - at least, according to a federal judge this year. Granted, no case law or legal precedent was established by that out-of-court settlement, but the size of the deal - essentially $3,000 per document - suggests that Anthropic believed it would lose in court and perhaps be ordered to pay billions more in damages, conceivably threatening its existence. In the Spring, Denmark's Rights Alliance published a report revealing just how many AI companies had knowingly scraped pirate sources for training data. The Anthropic case threatens all of them, therefore. Other cases spell danger for OpenAI, and for others of its ilk. For example, generative music platform Udio is transitioning to a service that only uses licensed content, after being sued by the Universal Music Group. That case left subscribers high and dry, unable to access the tracks they had paid to generate from copyrighted sources. As other generative platforms, such as Suno, have the same business model as Udio did before the settlement - CEO Mikey Schulman has admitted that Suno scraped most of the high-res audio files on the Web - it seems likely that they will be obliged to pay rightsholders. This threatens OpenAI directly, as it is thought to be planning a music service, while applications such as Sora must have been trained on unlicensed content, as otherwise users would not be able to prompt the appearance of Hollywood actors and copyrighted characters in videos. And of course, earlier this year Altman was, implicitly, encouraging the creation of Studio Ghibli memes, goading rightsholders by implication. Roughly 50 lawsuits are ongoing worldwide against AI companies for alleged copyright theft - many are essentially businesses built on unauthorized data use - and a lot of them are against OpenAI. Meanwhile, Altman's firm is also being sued over the suicides of some users who were using ChatGPT as a counsellor, mentor, and friend. (Read the transcripts: they are horrifying.) So, if the edifice of unlicensed training begins to crumble, which seems likely - and if the expensive illusion that chatbots have humanlike empathy and intelligence falls with it - then unscrupulous vendors must either pay up or hope they can lean on governments to throw out such judgements or change the law. Put simply, they will have no choice but to claim they are too big to fail. But that will hardly give OpenAI's IPO plans a boost, nor encourage users to jump onboard a business that, by that point, will struggle to claim it wants to benefit humanity. OpenAI's financial trajectory reveals a fundamental disconnect between Silicon Valley's belief-driven valuation models and basic economic reality. The company is not just burning cash - it is creating a structural dependency on data center capacity that will make it permanently unprofitable unless something radical changes. The real danger is not just to OpenAI, but to the broader AI ecosystem. If the poster child for the AI revolution cannot find a path to sustainability despite raising hundreds of billions, what does that say about the smaller players? And if the copyright cases begin to fall like dominoes - as the Anthropic settlement suggests they might - we are looking at an industry-wide reckoning that could dwarf the dot-com crash. What is most troubling is how OpenAI appears willing to sacrifice user trust and privacy in its desperation for revenue. The pivot to advertising, the monetization of intimate user conversations, the aggressive expansion into every conceivable product category - these are the actions of a company that knows its current trajectory is unsustainable. Governments and investors need to ask themselves: do we really want to bet our economies and our data on a business model this broken? Because right now, OpenAI is not building the future - it is mortgaging it.

OpenAI won't make money by 2030 and still needs to come up with another $207 billion to power its growth plans, HSBC estimates | Fortune

Although still private, the shadow of OpenAI and its still-unprofitable business despite the blockbuster success of ChatGPT has rattled markets throughout the back half of 2025. Talk of a bubble in artificial intelligence (AI) was not quelled despite Nvidia delivering yet another blockbuster quarter in November. The question remains about how OpenAI will balance ChatGPT's seemingly endless desire, on the one hand, for "compute," provided by data centers sprouting throughout the economy, with a business model that takes it from the red into the black. This is the same question that OpenAI CEO Sam Altman answered in a single exasperated word in a recent podcast appearance: "Enough." The investment bank HSBC, while clarifying that it still believes AI is a "megacycle" and that its forecasts "indicate a leading position for OpenAI from a revenue standpoint," nevertheless calculates that the company faces an extraordinary financial mountain if it is to deliver on its ambitions. HSBC Global Investment Research projects that OpenAI still won't be profitable by 2030, even though its consumer base will grow by that point to comprise some 44% of the world's adult population (up from 10% in 2025). Beyond that, it will need at least another $207 billion of compute to keep up with its growth plans. This stark assessment reflects soaring infrastructure costs, heightened competition, and an AI market that is surging in demand and cash-intensive to a degree beyond any technology trend in history. HSBC's semiconductor analyst team, led by Nicholas Cote-Colisson, produced the figure by updating its OpenAI forecasts for the first time since mid-October, factoring in recent multi-year commitments to cloud computing, including a $250 billion agreement with Microsoft and $38 billion with Amazon. Importantly, HSBC notes, these deals came without any new capital injection, and they are the latest in a series of capacity expansions that now see OpenAI aiming for 36 gigawatts of AI compute power by decade's end. Assuming that one gigawatt can power roughly 750,000 homes, electricity on this scale would represent the needs of a state somewhat smaller than Texas and a little larger than Florida. The Financial Times' AlphaVille blog, which previously reported on HSBC's forecast, described OpenAI as "a money pit with a website on top." However, the bank projects that OpenAI's cumulative free cash flow by 2030 will still be negative, leaving a $207 billion funding shortfall that must be filled through additional debt, equity, or more aggressive revenue generation. HSBC analysts model OpenAI's cloud and AI infrastructure costs at $792 billion between late 2025 and 2030, with total compute commitments reaching $1.4 trillion by 2033 (HSBC notes that Altman has laid out a plan for $1.4 trillion in compute over the next eight years). It will have a $620 billion data-center rental bill alone. Despite this, projected revenues -- though growing rapidly, to over $213 billion in 2030 -- would simply not be enough to bridge the divide. (The bank's revenue projections are based on an assumption of a higher proportion of paid subscribers in the medium term and an assumption that large language model, or LLM, providers will capture some of the digital advertising market.) The bank notes several options to close the gap, including dramatically ramping up the proportion of paid subscribers (going from 10% to 20% could add $194 billion in revenue), capturing a larger share of digital ad spending, or extracting extraordinary efficiencies from compute operations. But even under bullish conversion and monetization scenarios, the company would still need fresh capital beyond 2030. OpenAI's survival is closely tied to its financial backers and the AI ecosystem. Microsoft and Amazon are not only cloud providers but also major investors, and cloud players such as Oracle, NVIDIA, and Advanced Micro Devices all stand to gain -- or lose -- depending on OpenAI's fortunes. The risks, however, are considerable: unproven revenue models, potential market saturation for AI subscriptions, the threat of regulatory scrutiny, and the sheer scale of necessary capital injections. HSBC suggests that OpenAI could raise more debt to fund its compute requirements, but this would be "possibly the most challenging avenue in the current market conditions," as Oracle and Meta have recently raised a "significant amount" of debt to finance AI-related capex, "raising market concerns about the general financing of AI." The bank notes this is an exception as most of the so-called "hyperscalers" have funded themselves with free cash flow, as noted by JPMorgan's Michael Cembalest recently. HSBC also noted a "sharp increase" in Oracle's credit default swaps in recent days, which Morgan Stanley's Lisa Shalett voiced alarm over several weeks earlier, in a previous interview with Fortune. HSBC, like many other banks writing on the AI revolution, returned again to the famous quote by Nobel prize winner Robert Solow that "You can see the computer age everywhere but in productivity statistics," noting drily that "poor productivity gains driven by weak total factor (labour and capital) productivity are an unfortunate characteristic of today's developed economies." In fact, the bank notes that some aren't convinced of a meaningful return yet from the 30-year-old internet revolution itself, noting Federal Reserve Governor John Williams' 2017 comment that "productivity provided by modern technologies like the internet has so far only influenced our consumption of leisure - and hasn't yet trickled down to offices or factories." Bank of America Research's Head of US Equity & Quantitative Strategy, Savita Subramanian, told Fortune in August that she sees a "sea change" for productivity emerging out of the economy of the 2020s in ways that aren't fundamentally about AI. Through a combination of factors, including post-pandemic wage inflation, she said that companies have been prompted "to do more with fewer people," replacing people with process in a scalable and meaningful way. A consideration that was giving her pause, though, was a shift from an asset-light to an asset-heavier focus, as many of the most innovative tech companies have discovered a near-unquenchable thirst for a kind of hardware that carries a lot of risk with it: data centers. A few months later, Harvard economist Jason Furman did a back-of-the-envelope calculation and found that without data centers, GDP growth would have been just 0.1% for the first half of 2025. OpenAI seems to be asking markets a question: just how long can growth be built on the question of future returns -- and a productivity revolution -- from AI that are by no means ever guaranteed to arrive?

OpenAI's compute rental outgo could see $207 billion shortfall, HSBC estimates - The Economic Times

HSBC analysts project OpenAI could face a significant compute rental shortfall by 2030, despite substantial new cloud deals with Microsoft and Amazon. Even with projected revenue growth from various AI ventures, the company's massive compute needs may outpace its financial capacity, potentially leaving a substantial deficit.OpenAI could fall short of its compute rent requirements even if it maintains its current growth trajectory, according to the latest estimates by HSBC analysts for the artificial intelligence (AI) major. The US software and services team at the multinational bank has updated its OpenAI model to factor in the $250 billion of rented cloud compute from Microsoft announced late in October, and another $38 billion from Amazon, finalised the week after. These two deals would add four gigawatts to OpenAI's total contracted compute capacity, bringing its total to 36 GW. However, only a third of this power is expected to come online by the end of this decade. Revenue and expenses By certain estimates, OpenAI has an annual revenue of $13 billion, with 5% of the current user base opting for one of its paid subscription plans. In the latest financial model, HSBC estimates the company will earn from advertising, agentic AI, and the AI hardware Jony Ive is working on. It pegs consumer AI revenue at $129 billion by 2030, with $87 billion coming from search and $24 billion from advertising. Enterprise AI revenue could be $386 billion in the same period. The Sam Altman-led company will likely generate free cash flow of $282 billion during this period, per HSBC estimates. Nvidia's promised cash injections and the disposal of AMD shares can bring in another $26 billion. In addition, $24 billion of undrawn debt and equity facilities, and $17.5 billion of available liquidity as of mid-2025 are also on its books. Meanwhile, OpenAI could face a rental bill of $702 billion by 2030, and $1.4 trillion by 2033. This could leave a $207 billion hole in its finances, HSBC estimates. Way ahead Every 500 million users OpenAI adds will add around $36 billion to its cumulative revenue between now and 2030, HSBC said. Converting 20% of them to paid subscribers can lead to an additional $194 billion windfall during this period, it added. Notably, this model does not factor in the eventuality of OpenAI achieving artificial general intelligence, the next big thing every AI company is gunning for. If the revenue doesn't exceed expectations and investors turn cautious, OpenAI might have to walk away from some of its data centre commitments, HSBC pointed out. Also Read: Sam Altman acknowledges 'economic headwinds' for OpenAI as Google's AI gains pace

OpenAI's Partners Rake Up $96 Billion Debt as AI Industry's Borrowing Trend Escalates

Enter your email to get Benzinga's ultimate morning update: The PreMarket Activity Newsletter Companies supplying data centers, chips, and processing power to OpenAI have racked up a staggering $96 billion in debt to fund their operations. What Happened: According to the report, the AI industry's increasing reliance on debt and its dependence on the loss-making startup OpenAI continues to raise concerns. The revenue generated by AI firms and the rapidly expanding data center operators serving them falls short of covering their build-out costs. As per the report by The Financial Times, OpenAI has pledged a whopping $1.4 trillion to secure the energy and computing power needed for its future operations. However, it expects to generate only $20 billion in revenues this year. A recent study by HSBC indicates that even if OpenAI's revenues surpass $200 billion by 2030, it will still require an additional $207 billion in funding to stay afloat. Also Read: Microsoft's AI Chief Criticizes ChatGPT's Erotica Features Despite $13 Billion OpenAI Investment OpenAI's partners, which include SoftBank, Oracle, and CoreWeave, have already borrowed $30 billion. Blue Owl Capital and Crusoe have taken out $28 billion in loans, with another $38 billion under negotiation with Oracle and Vantage and their respective banks, reports the outlet. Why It Matters: The shift towards debt financing in the AI sector is a recent phenomenon. In the past, most AI build-outs were financed with cash directly from the balance sheets of large tech firms such as Microsoft, Alphabet, Amazon, and Meta. Furthermore, the big five hyperscalers, Amazon, Google, Meta, Microsoft, and Oracle -- have accumulated $121 billion in new debt this year to fund AI operations, according to Bank of America. This figure is over four times the average debt level issued by these companies over the past five years, indicating a significant shift in the industry's financing strategies. Read Next OpenAI's Altman Foresees AI Replacing 40% of Work Tasks Soon Market News and Data brought to you by Benzinga APIs

OpenAI needs a lot more cash to stay in business

OpenAI needs a lot of power for its operation, currently they have committed to rental of servers with a combined capacity of 36 Gigawatts, primarily from Microsoft and Amazon. In a recent report from the bank HSBC took a closer look at the economics of it all which- Financial Times has read, and come to some interesting conclusions. OpenAI has comitted to spending 1.8 trillion USD, resulting in a 620 billion USD bill anually, despite the analysis predicting that OpenAI will only be able to utilize 1/3 of the power at their disposal. The problems arise despite HSBC are utilizing an extreme best case scenario, including that 44% of the entire world population is using their product - although not including China, providing a user base of 3 billion people, almost 4x the number of users today - in five years, and having 10% subscriptions, twice the current number, and not least, profiting 2% on digital advertising, currently very close to 0%. This very positive approach to income still does no come even close to break even, with the projection being an annual loss of almost 18 billion dollars in 2030. This leaves fundraising on a gigantic scale as the only viable way to stay afloat- this is despite AI revenue is estimated to hit 129 billion Dollars for consumer sales, and 386 billion Dollars from enterprises in 20230. But with huge operating costs, and xAI and Anthropic gaining marked shares, even when excluding Google completely from the calculations. The main thing is that OpenAI's server rental costs will be 792 billion Dollars over the next five years, and then explode to 1.4 trillion Dollars from 2030-2033. This is matched by projections by OpenAI made public three weeks ago.In total, at least 207 billion Dollars are missing from the spread sheets, no matter how optimistic a frame work can be made.

OpenAI Backers Could Rack Up $100 Billion in Debt | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. As the Financial Times (FT) reported Sunday (Nov. 30), this has allowed the high profile artificial intelligence (AI) startup to reap the rewards of a debt-driven spending wave without having to take on financial risks. An analysis by the FT found that SoftBank, Oracle and CoreWeave have borrowed at least $30 billion to invest in OpenAI or help build its data centers. Meanwhile, investment company Blue Owl Capital and computing infrastructure providers such as Crusoe also depend on deals its customers have inked with OpenAI to service roughly $28 billion in loans. Lastly, a group of banks was in discussions to loan another $38 billion for Oracle and data center company Vantage to pay for additional sites for OpenAI, the report said, citing sources familiar with the matter. The deal is expected to become final in the weeks ahead. OpenAI executives have said they aim to raise substantial debt to help pay for these contracts, but thus far the financial burden has fallen to its partners and their lenders. "That's been kind of the strategy," said a senior OpenAI executive. "How does [OpenAI] leverage other people's balance sheets?" The report noted that the size of these loans that depend on OpenAI will deepen scrutiny into the $1.4 trillion in deals the company has signed this year to procure computing power in the next eight years. Those commitments, the FT added, vastly overshadow the company's $20 billion in anticipated annualized revenue for the year. Sources close to OpenAI told the FT the startup has little debt on its books, with a $4 billion credit facility it landed last year but has yet to touch. The company requires massive amounts of computing power to train and run its AI models, the report added. "Building AI infrastructure is the single most important thing we can do to meet surging global demand. ... The current compute shortage is the single biggest constraint on OpenAI's ability to grow," the company told the FT.

Managing Expectations! Sam Altman and the Investor Pressure Cooker

Sam Altman sits at the epicenter of the most expensive gamble in tech history. With OpenAI now valued at $300 billion following a record-breaking $40 billion funding round, he must perform an intricate balancing act: maintaining investor confidence while candidly acknowledging competitive threats that could undermine the entire AI narrative. His recently leaked internal memo warning employees about Google's competitive resurgence and slowing revenue growth reveals the treacherous tightrope walk required to manage expectations when burning billions. The numbers tell a stark story. lost $5 billion in 2024 despite generating $3.7 billion in revenue, spending $2.25 for every dollar earned. Projections suggest the company will burn through $115 billion cumulatively through 2029 before achieving profitability, an unprecedented capital consumption that dwarfs even the most ambitious tech ventures of previous eras. Yet Altman has convinced investors, including SoftBank, Microsoft, and Nvidia, not only to tolerate these losses but to embrace them as necessary costs of dominance. His strategy relies on reframing catastrophic burn rates as strategic investments in an inevitable future. Where traditional CEOs promise margin improvements with scale, Altman has inverted the formula; each new user adds compute-heavy costs rather than efficiency gains. The leaked memo's admission that AI's hype cycle is contracting represents a calculated risk: by acknowledging slower near-term growth internally, Altman builds credibility with employees while simultaneously raising external capital at ever-higher valuations. This dual-track communication strategy allows him to prepare his team for operational discipline while assuring investors that long-term superintelligence goals remain intact, even amid rumors of hiring freezes. The promises Altman can still make center on optionality rather than profitability. OpenAI's 500 million weekly ChatGPT users and projected 2025 revenue of $12.7 billion highlight market leadership in foundation models. Investors aren't betting on discounted cash flows but on the thesis that whoever controls the base layer of AI will dominate the ecosystem above it. Altman's recent infrastructure deals, including a $38 billion commitment with Amazon Web Services and partnerships that diversify beyond Microsoft, signal aggressive capacity-building that reinforces this narrative of inevitable dominance. Yet, certain promises must now be walked back. The trajectory from growth-at-all-costs startup to operationally disciplined enterprise is a major shift. Altman's transparency about competitive pressure from Google and Anthropic contradicts earlier suggestions that OpenAI is enjoying an unassailable position. The acknowledgment that revenue growth might collapse to just 5% shatters the hypergrowth story once justified previous valuations. His challenge is recontextualizing these admissions not as failures but as realistic adjustments in a maturing market. The investor pressure intensifies when examining the restructuring required to access this capital. OpenAI recently completed its transformation from a nonprofit-capped structure to a public benefit corporation, with Microsoft receiving 27% ownership for its $13.8 billion investment, a stake now worth nearly $80 billion on paper. Existing investors who decline to participate in future rounds face dilution as Altman requires tens of billions more to honor commitments to suppliers like Oracle and Nvidia. This creates a self-reinforcing funding cycle in which early believers must keep betting or risk watching their positions erode. Altman's unusual lack of equity ownership in OpenAI, he holds no shares and makes just $76,001 annually, paradoxically strengthens his position with investors. Without a personal financial stake, he can credibly claim mission-driven motivation for pursuing superintelligence regardless of short-term financial pain. His $1.9 billion personal fortune comes entirely from external investments in companies like Helion Energy and Reddit, creating separation between his wealth and OpenAI's fortunes that may actually enhance trust. The ultimate test of will come if OpenAI fails to reach its projected $200 billion in annual revenue by 2030 or if competitors like Google and Anthropic accelerate faster than anticipated. His leaked memo suggests he's preparing stakeholders for this possibility by emphasizing that "we are not invincible" while simultaneously arguing that focused execution on superintelligence remains the winning strategy. Whether this transparent vulnerability proves strategically brilliant or fatally honest will determine if Altman's unprecedented capital bonfire yields revolutionary returns or becomes the costliest cautionary tale in technology history.

OpenAI's long term compute commitments exceed projected cash flows By Investing.com

Investing.com -- OpenAI's latest commitments to Microsoft and Amazon have sharply increased its long term computing obligations without adding fresh capital, leaving the company facing a financing shortfall that HSBC says will surpass $200 billion by the end of the decade. OpenAI has signed an additional $288 billion of cloud contracts in the past month. Which includes a $250 billion purchase agreement with Microsoft for computing capacity announced on October and a seven year $38 billion arrangement with Amazon disclosed on November. HSBC said the expanded commitments reflect the cost of scaling large language models, but also raise questions about OpenAI's ability to match spending with revenue growth. HSBC estimates OpenAI now plans for $1.4 trillion of compute costs over the next eight years. Its updated model projects the company will pay a cumulative $792 billion on data centre rent between the second half of 2025 and 2030 and $1.4 trillion through 2033. Against its revenue outlook, which HSBC lifted modestly to reflect more paid users and a larger share of digital advertising, the bank calculates a $207 billion funding gap by 2030. The analysts said OpenAI's ability to manage the shortfall will depend on how much flexibility it has to adjust its commitments and how effectively it can expand paid adoption. Raising the share of paying users to 20% by 2030, from the 10% in HSBC's base case, would add about $194 billion in revenue over 2026 to 2030. Other options include tighter cost controls, new equity infusions or debt financing. HSBC acknowledged that the scale of spending has unsettled investors, given projected revenue of about $12.5 billion in 2025. But it argued that a long AI driven investment cycle remains intact as productivity gains spread through the economy. OpenAI's expansion sits at the centre of a broader push by model developers, infrastructure providers and chipmakers to capture demand for AI driven services. HSBC says Oracle, Microsoft, Amazon, Nvidia, AMD and Softbank as the most exposed partners to OpenAI's performance.

HSBC Warns OpenAI Could Face $207B Funding Gap Due to Rising AI Costs

OpenAI May Need $207b in Extra Funding by 2030 as Rising AI and Cloud Infrastructure Costs Outpace Projected Revenue Growth HSBC Global Investment Research estimates that OpenAI may need about $207 billion in additional funding by 2030 to sustain its growth plans. The bank links this projected shortfall to very large cloud and data-center commitments that exceed expected cash generation, even under strong revenue assumptions. The report highlights OpenAI's long-term compute deals with major technology partners. The company has signed multiyear agreements worth hundreds of billions of dollars with Microsoft, Oracle and Amazon Web Services. HSBC expects OpenAI's cloud and AI infrastructure spending to reach about $792 billion between late 2025 and 2030, and roughly $1.4 trillion by 2033.