The ledger remembers what the market forgets. That’s a phrase I’ve clung to since the 2018 crypto winter, when my Ethereum holdings evaporated overnight. Now, as I watch the S&P 500’s concentration hit record levels and AI capital expenditure forecasts begin to wobble, I feel that same familiar tension. The BIS recently warned that the tech giants’ spending spree could turn into a long-term investment crash. Meanwhile, the Aschenbrenner fund—once a $45 billion AI-focused vehicle—imploded, shrinking to $10 billion before Citadel took over. These aren’t just tech stories; they’re macro signals that ripple through every asset class, including crypto.
For three years, the narrative has been simple: AI is the new internet, and capital expenditure is the price of entry. But as a macro watcher who navigated the 2022 bear market by pivoting to Layer 2 infrastructure and stablecoin yields, I’ve learned that when the herd is betting on a single story, the exit is rarely orderly. The AI spending slowdown isn’t just about NVIDIA’s next earnings call—it’s about whether the liquidity that fueled the S&P 500’s 50% concentration in the top 20 stocks will rotate into other assets, including digital assets. Let’s unpack this.
Hook: The BIS Warning and the Aschenbrenner Collapse
The Bank for International Settlements (BIS) doesn’t mince words. In its latest quarterly review, it flagged that the massive capital expenditure by big tech companies "could turn into a long-term investment crash." This isn’t a fringe think tank; it’s the central bank for central banks. Simultaneously, the Aschenbrenner fund—run by a former OpenAI researcher who epitomized the "AI insider" trade—saw its assets under management collapse from $45 billion to $10 billion, forcing a takeover by Citadel. The fund was heavily leveraged in AI infrastructure stocks, and when the market started questioning the ROI of datacenter buildouts, the house of cards fell.
These two events are not coincidental. They mark a fracture in the AI narrative that has dominated global markets since ChatGPT’s launch. For crypto, this fracture is a double-edged sword. On one hand, a sharp correction in AI stocks could trigger a broader risk-off move, dragging Bitcoin and Ethereum lower. On the other hand, if the AI bubble deflates gradually, the liquidity that was locked in tech giants could seek new homes—and crypto, with its uncorrelated return profile and maturing infrastructure, stands as a candidate.
But let’s ground this in data. The S&P 500’s top 20 stocks now account for 50.8% of the index’s total market capitalization, according to JPMorgan. That’s a level of concentration without modern precedent. The five largest hyperscalers—Microsoft, Amazon, Google, Meta, and Apple—are expected to deploy over $1 trillion in AI-related capital expenditure between 2025 and 2026, per Goldman Sachs. Morgan Stanley’s estimate goes further: $3 trillion by 2028, with 80% yet to be spent. These are staggering numbers.
Yet, the Bank of America July fund manager survey found that 45% of respondents now rank an "AI bubble" as the biggest tail risk—up from 28% the previous month. That’s a seismic shift in sentiment. The same survey showed that "AI bubble" has overtaken "secondary inflation" as the primary concern. For a market that has been trained to buy every dip, this is a warning sign that the consensus is cracking.
Context: The Macro Landscape and Crypto’s Place
Why should a crypto fund manager care about AI spending? Because liquidity is the only truth. The macro environment that determines capital flows into crypto is also shaped by the same forces that drive AI capex. When hyperscalers borrow to build datacenters, they compete for the same pool of global savings that could otherwise flow into bitcoin ETFs or DeFi yields. Conversely, when AI spending slows, the freed-up capital could rotate into alternative assets.
But there’s a more direct link: the AI infrastructure buildout has been a massive driver of demand for energy, storage, and networking. Storage companies like Sandisk and Western Digital have surged 396% and 145% year-to-date respectively, reflecting the data center appetite for SSDs and HDDs. If AI spending slows, those stocks will correct, and the resulting volatility could spill into crypto through the "risk-on" regime.
We built the cathedral before the saints arrived. That’s how I describe the current state of AI infrastructure. The hyperscalers are laying the foundation for a future that may take years to materialize. In crypto, we’ve seen this pattern before: the 2017 ICO boom built infrastructure that was early for the 2020 DeFi Summer. The difference is that crypto’s infrastructure cost a fraction of what AI capex requires. The scale of AI investment is so large that it alters the global macro landscape.
The BIS warning is specifically about the disconnect between the spending and the productivity gains. In the 1990s, telecom companies laid fiber optic cables that were initially underutilized, but eventually the internet economy grew into them. The question is whether AI will follow the same path. If it does, the current spending is rational. If it doesn’t, we’re looking at a wave of write-offs that could destabilize the balance sheets of the largest companies and, by extension, the financial system. Crypto, as a hedge against monetary debasement and systemic risk, could benefit from such a scenario.
Core: AI Spending Slowdown as a Macro Catalyst for Crypto
Now, let’s get into the technical analysis. The core insight is that the AI spending slowdown, if sustained, will reduce the expected return on capital for the tech sector, which in turn will lower the opportunity cost of holding non-yielding assets like Bitcoin. In a world where AI capex offers 15% returns, capital flows there. But if those returns compress to 5%, the risk-adjusted appeal of a scarce digital asset becomes more attractive.
We can draw a parallel with the 2021-2022 cycle. When the Fed raised rates, the opportunity cost of holding Bitcoin increased, driving a sell-off. Now, the AI sector is acting as a "crowding out" mechanism for risk assets. As AI capex faces diminishing marginal returns, the marginal investor may reallocate to crypto.
But there’s a more nuanced angle: the earnings quality of the S&P 500 is being artificially inflated by AI capex. Mac10, a well-known macro analyst, argues that the record forward earnings growth is largely due to companies treating AI capex as a one-time expense that flows through the income statement, rather than as a sustainable source of revenue. This means that the earnings beat (64% of companies beat estimates by one standard deviation, per Goldman Sachs) is not as robust as it appears. If AI spending slows, those earnings will revert, and the market’s valuation premium will deflate.
For crypto, this is a double-edged sword. A sharp correction in equities would likely trigger a liquidity crunch that hits all risk assets, including crypto. However, if the slowdown is gradual and orderly, the rotation out of AI stocks could benefit crypto as a beneficiary of "narrative shift." The key is velocity: how fast the money moves.
Let me share a personal experience. In 2022, during the bear market, I ran a digital asset fund that faced a 60% drawdown. Instead of panicking, I organized daily resilience circles with my team and investors. We pivoted from high-risk altcoins to stablecoin yields and Layer 2 infrastructure. That decision preserved 40% of the fund’s value. The lesson was that during macro transitions, the most important thing is to understand where liquidity is flowing, not where the hype is.
Currently, liquidity is flowing into AI infrastructure. But the marginal dollar is becoming less enthusiastic. The Aschenbrenner fund collapse is a microcosm of what happens when leverage meets a slowing narrative. The fund’s $4 billion investment in private AI companies, even after its public portfolio cratered, shows the hubris of insiders. That same hubris could lead to a broader unwind.
Contrarian: The Decoupling Thesis – Crypto’s Strength in an AI Slowdown
Here’s the contrarian angle: AI spending slowdown might actually be bullish for crypto. Not because it’s a direct substitute, but because it forces a re-evaluation of the "risk-free" tech trade. The S&P 500’s concentration is a vulnerability. The top 20 stocks are all heavily exposed to AI. If AI spending slows, those stocks will underperform, potentially breaking the positive correlation between crypto and tech stocks.
Remember, crypto’s beta to the S&P 500 has been declining. In 2024, the Bitcoin ETF approval marked a turning point: institutional inflows began to decouple Bitcoin from the Nasdaq. On days when the Nasdaq dropped 2%, Bitcoin only fell 1%. If the AI slowdown causes a rotation out of big tech, Bitcoin could act as a safe haven for capital that wants to stay in growth but avoid the concentration risk.
Moreover, the AI bubble narrative is a self-fulfilling prophecy. As more investors label it a bubble, the odds of a correction increase. This creates a "reflexive" effect: the fear of a bubble causes selling, which confirms the bubble. In such an environment, non-correlated assets like Bitcoin become attractive portfolio diversifiers. The 45% of fund managers who see AI as the biggest tail risk are likely already hedging with alternatives.
But let’s not overstate the case. There’s a real risk that the AI slowdown triggers a broader credit event. The BIS specifically warned about the "long-term investment crash" scenario. If hyperscalers have to write down billions in datacenter investments, the banking sector that lent to them could face losses. That would be a systemic shock that would hurt all assets, including crypto. However, crypto’s decentralized nature means it can survive a banking crisis, as we saw in March 2023 when the US regional bank failures temporarily boosted Bitcoin.
The key is to watch the macro triggers. The AI spending slowdown is not a binary event. It’s a process. The first sign would be a reduction in forward guidance from hyperscalers. Microsoft’s recent earnings showed a slight deceleration in Azure growth, which some analysts attributed to AI investment fatigue. If that becomes a trend, the market will reprice AI stocks.
Another indicator is the storage industry. Sandisk and Western Digital’s rally has been built on the assumption of sustained AI demand. If their earnings reports show inventory buildup or order cancellations, that would be a leading indicator. I track these stocks as a proxy for AI infrastructure health.
Takeaway: Positioning for the Next Cycle
Stability is a myth; liquidity is the only truth. The AI spending slowdown is a macro event that will reshape portfolio allocations over the next 12 months. For crypto investors, this means two things: first, prepare for potential volatility if the AI bubble bursts suddenly; second, watch for the rotation of capital out of tech and into alternatives.
I’m not predicting a crash. But I am positioning my fund to be slightly overweight crypto, particularly Bitcoin and Ethereum, with a small allocation to AI-themed tokens that could benefit from the narrative shift. The goal is to be ready for the spring after the winter.
Surviving the winter makes the spring inevitable. In 2018, I lost 90% of my capital. In 2022, I preserved 40%. The lesson is that macro cycles are not to be feared but to be understood. The AI spending slowdown is a macro event that will create opportunities for those who see the flow.
Let me leave you with a question: If the S&P 500’s top 20 stocks start to underperform because of AI fatigue, where will the next $100 billion of institutional capital go? The answer might be digital assets. The ledger remembers what the market forgets. We’ll see if the market remembers this time.