AI hype fuels financial bubble, but real bottlenecks loom

🔴Is the U.S. economy booming❓ 🔸What if you remove the contribution from the AI-related sector - how does the economy look❓ 10 Oct 2025 Reflection on a post by Warwick Powell 🌐🔗 https://lnkd.in/gs8iFrU4 #AISector #supplychain #freight #economics #logistics 🔶This sector includes firms like Nvidia 🔸as well as companies that sell goods like power generation equipment. 🔸🚨My concern is both charts show an eerie similarity to the incredible increase in the value of shipments from US computer & electronic products manufacturing plants in the late 1990s (https://lnkd.in/gXZ-Yq5m). We all know how that ended. 🔶Implication: Investment in the physical infrastructure needed to support AI computing has been so pronounced 🔸that it is materially affecting macroeconomic indicators like GDP. 🔶If investment were to show a significant slowdown 🔸before labor market conditions improve, 🔸this could be the proverbial straw that results in an economy-wide recession (something we have avoided, apart from the incredibly brief COVID-19 lockdown period, since the Global Financial Crisis). 🔶At some point, the growth rate of investment in AI infrastructure will slow: 🔸the question isn’t if, 🔸but when this happens 🔸(and how suddenly the slowdown takes place).

Weekend Read: The Emerging AI Financial Bubble I spent part of my weekend digging into some fascinating — and slightly unsettling — readings about how deeply the U.S. economy has become intertwined with the artificial intelligence boom. What started as a wave of innovation is now driving an entire financial ecosystem: data centers are being financed like real estate, AI companies are investing in one another through complex cross-holdings, and an enormous amount of corporate debt is being funneled into AI-related infrastructure. It’s starting to look less like a tech revolution and more like a high-stakes financial experiment. A few takeaways that stood out: - AI companies are massively interlinked. Giants like Nvidia, Microsoft, OpenAI, AMD, and Oracle are not only partnering but also investing in each other — a closed loop of leverage and dependency. - Debt exposure is growing fast. JPMorgan reports that over $1.2 trillion of investment-grade debt is now tied to AI-related companies — making it the largest single segment in the market. - Data centers are the new subprime mortgages. Private equity firms are funding massive data center projects, which are then being repackaged into financial instruments — eerily reminiscent of how mortgage-backed securities operated before 2008. In short, a large portion of the U.S. economy is now a high-risk bet on AI — with inflated valuations, complex financing structures, and interdependent investments. I’m not predicting a crash — but the patterns feel familiar. The parallels to 2008 are hard to ignore. Curious to hear what others think: 🔸Are we building real long-term infrastructure value here? 🔸Or are we repeating history — just with GPUs instead of mortgages? #AI #Finance #Economy #Investing #Technology #DataCenters #WeekendRead

Add to this the concentration of capital in just a few companies in a single sector – AI. For now, capital expenditures are driving demand growth. What if AI doesn't deliver productivity? (You’ve been given free access to this article from The Economist as a gift. You can open the link five times within seven days. After that it will expire.) Gita Gopinath on the crash that could torch $35trn of wealth https://lnkd.in/dYDew4zg

AI Investments: $252B Boom or Bubble About to Burst? "Where will the $6.7 trillion come from?" - The question every investor should be asking. THE DATA: Global AI investment: $252.3B in 2024 (↑13x since 2014) Mag 7 = 33% of S&P 500 (2x the 2000 bubble!) OpenAI: $500B valuation, $0 profit IMF & Bank of England: Warning flags raised 🚩 BOON CASE: → Real results: Walmart 35%↓ inventory, Rocket Mortgage $40M saved → Fundamentals: 28x P/E vs 89x in 1999 → ChatGPT: 800M users (fastest adoption ever) BUBBLE CASE: → Circular financing (Nvidia→OpenAI→Oracle→Nvidia) → $1 customer revenue = $8+ supply chain cascade → Margin debt: 3.7% GDP (near 2000 levels) Full case study: Below ↓  Constructive criticism welcome - it's how I grow. Challenge my analysis, share alternative views, or suggest improvements. Every insight makes me a better analyst. Disclaimer: This case study is for educational purposes only with information collected from public sources and does not constitute investment, financial, legal, or tax advice; it carries no guarantees, assumes no liability, and urges independent due diligence, professional consultation, and verification of all information. #AI #TechBubble #InvestmentAnalysis #IndianInvestors #StockMarket #AIInvesting #FinancialMarkets #MarketAnalysis #ContinuousLearning #TechInvesting #AcademicResearch #AIIndex #UniversityReport #TechnologyMetrics #NewsAgency #GlobalNews #EconomicAnalysis #Reuters #CentralBank #InternationalFinance #EconomicOutlook #BankOfEngland #IMF #InvestmentBank #ResearchReport #AIStocks #GoldmanSachs #NewsNetwork #WallStreet #MarketFears #NBCNews

I asked AI about historical trends in the market, this is what it told me ... but if there someone out there that can verify, I would appreciate it: 🌅 What Happened in 1972 — and Why It Feels the Same Now Back in 1972, the U.S. looked strong. The stock market was booming, people were spending, and the government said everything was fine. But underneath, big changes were quietly starting — the kind that took a few years to show up. 1. Money changed. In 1971–72, the U.S. stopped backing the dollar with gold. That made money easier to print, and prices slowly began rising. Within a few years, inflation exploded and people’s savings lost value. 2. Everyday costs went up. Wages didn’t keep up with prices. Groceries, rent, and gas all got more expensive — but paychecks didn’t grow much. Families felt squeezed, even though the government said the economy was “growing.” 3. Stocks looked unstoppable — until they weren’t. Big, famous companies (like IBM and Polaroid) were called “can’t-lose” stocks. Then, in 1973–74, the market crashed almost 50 %. People who thought they were rich lost half their savings in a year. 4. Politics and trust broke down. The Watergate scandal made Americans lose faith in leaders. Today we see the same kind of political fighting and public frustration. 5. Gold quietly became the winner. While stocks fell, gold rose sharply. People who owned gold protected their savings when everything else fell apart. --- 🔁 Why 2025 Feels the Same Inflation is back and prices still hurt. The U.S. is putting up tariffs again. Tech stocks (like Nvidia and AI companies) look unstoppable — just like IBM did in 1972. And once again, gold is rising quietly in the background, because people sense trouble.

Rate cut signals from the Federal Reserve - combined with continued enthusiasm around AI - sparked a market resurgence late last week, even amid trade uncertainty and political gridlock. While no one can fully predict where markets are headed, a well-diversified portfolio remains essential to navigating a wide range of outcomes - and to capturing opportunities as new asset class leaders emerge. Read more in this week’s Northwestern Mutual commentary: https://lnkd.in/gvB2VSDA

DeepSeek launched in January 2025. AI stock prices crashed overnight. The Bank of England had been watching this exact scenario. Their warning just became reality. This wasn't just another market wobble. The BoE had specifically warned about AI infrastructure debt financing. They saw what was coming. Here's what makes this different: • AI infrastructure needs $5.2 trillion by 2030 • $800 billion will come from private debt • Banks have both direct and indirect exposure • Asset price crashes get amplified by debt The DeepSeek event proved their point perfectly. One AI model launch triggered massive repricing across the sector. What's really interesting? The BoE drew parallels to the dot-com bubble. Same pattern. Massive capital investment. Heavy debt financing. Sudden reality check. But here's what I'm curious about: Are we building sustainable AI infrastructure? Or are we repeating old mistakes with new technology? The math is staggering. Trillions in spending. Much of it borrowed money. Banks are exposed through direct lending to AI companies. Plus indirect exposure through funds and institutions. One price correction could cascade through the entire system. The BoE is monitoring this closely now. They're tracking commodity markets too. Energy infrastructure. Data centers. The whole ecosystem. What do you think? Are we in an AI infrastructure bubble? How should financial institutions manage this risk? #AIInfrastructure #FinancialStability #BankOfEngland 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/e2KjqscW

There are 2 big proxy plays on the AI value chain that Mr. Market currently does not seem to value at all. Both are very simple basic businesses. On one end you have power and utilities and on the other end you have distribution. Let's say you want to setup a 1MW data centre tomorrow, you need servers, racks, chips and a host of other equipment apart from of course Real Estate. Now here comes the catch - Can you call NVidia and say - "Hey Jansen, send those chips over!" Here's what Jansen is going to tell. "Thanks for calling me, while I try running this trillion dollar company, why don't you get in touch with Mr. X from Gupta Sales, he will make sure you get them all" No OEM in the world directly deals with end customers - the supply chains are too efficient and controlled by master distributors. We covered two such businesses in the Growth Titans of Q1 deep dive (https://lnkd.in/gGNsd867) last. month, but Mr. Market is valuing the two biggest companies in this space at almost single digit PE. An old school contrarian Value Investor has already built sizeable position in one of these names. Now, let's come to the other end. Cocoa, Gold, Coffee, Silver, Copper -> All commodities have shown to us how disproportionate spikes come through, but somehow there is one commodity that can make our deficit spiral out of control and can give the whole world a rude shock - Crude (pun intended) While it would not be fair to me to say that they are very cheap because they have always generally traded on the lower end of valuation multiples but it does seem that there is a case for them to get re-rated given the massive power spikes that are going to come in due course. Do not be surprised at all if there are talks about energy scarcity in a few years - provided the AI bubble does not burst before the grid (emperically) blows up. If you are reading this post for the first time, I send one distilled insight every morning at 8:00 AM that helps you get institutional grade coverage on Indian and Global Capital markets. Even if you are not an investor, this will help you with a differentiated framework to look at things. Link to subscribe is in the first comment.

Great insights — the interplay between labour market strength and questions around the AI rally makes this a crucial moment for fixed income investors. Through EFG and our New Capital funds, we focus on capturing opportunities across global fixed income while maintaining a strong emphasis on risk management and long-term value creation. Raphael Pinheiro, CFA Thiago Favery, CFA Fernando Olea New Capital

With markets focused on US labour trends and question the AI rally, Michael Leithead, explains the implications for fixed income investors.