On July 14, 2026, a point still “suspended” by data, the Federal Reserve's “mouthpiece” Nick Timiraos has already set the stage: even if June's overall CPI might show a beautiful reading of “inflation easing” due to the drag of falling energy prices, what really determines the path of interest rates is the expected month-on-month core CPI of about 0.21%, which is similar to May—this is the part that excludes energy fluctuations but stubbornly refuses to revert significantly, representing sticky inflation. Almost simultaneously, Goldman Sachs provided another massive macro narrative: from Google, Amazon, Meta, to Microsoft and Oracle, a total of about $5.8 trillion in AI infrastructure investments has been projected until 2030, for which these giants are responsible for nearly $200 billion in corporate bond issuance this year and about $90 billion in debt through joint projects to fund data centers. One side is high interest rates, with core inflation not budging; the other is the AI boom, with tech giants leveraging up. Under the intertwining of these two debt and pricing chains, the capital order of global risk assets is forced to be rearranged: BTC and ETH, highly sensitive to U.S. inflation and interest rate expectations, as well as the Nasdaq tech stock market, will reshape their risk premiums, supply of on-chain dollar-pegged assets, and exchange balances with each release of inflation data and progress in AI financing over the coming months.

Energy Drag on CPI: The Facade of Inflation Easing

With the drag of weakening energy prices, economists widely expect the overall CPI for the U.S. in June to decline, and “inflation easing” quickly became a consensus on trading desks: bond bulls bet on falling yields, gold packaged itself as a hedge, while both long and short funds build leveraged positions in BTC and ETH around the imminent CPI and PPI announcements based on inflation direction. Historical experience has been repeatedly cited at this moment—whenever the market believes that inflation has peaked, BTC and other risk assets often see a period of risk appetite recovery and capital inflow, as if this time could replicate the same path.

However, this narrative has been firmly split into two layers by the Federal Reserve's statements. Energy and food are the main causes of overall CPI fluctuations, yet they are excluded from core CPI, while the market currently expects June's core CPI to be around 0.21% month-on-month, similar to May, indicating that endogenous inflation stickiness has not really loosened. Just as the market comforts itself by saying “energy dragged down overall CPI,” Fed “mouthpiece” Nick Timiraos has explicitly stated—at this stage, policymakers pay more attention to core CPI rather than the more energy-sensitive overall CPI, and a sustained and significant decline in core inflation may be necessary to pivot the monetary policy path substantively. On the surface, overall inflation data may bring a short-term boost to BTC and ETH, but in the context of a still cautious policy and unchanged interest rate expectations, their sensitivity to a one-time overall CPI “positive” will be compressed, with capital more likely to follow changes in core CPI and interest rate expectations for portfolio adjustments: the expansion of on-chain dollar-pegged asset supply and the consumption of BTC and ETH balances on exchanges will reflect whether funds are truly willing to escalate a one-time energy-driven inflation decline into a bet on the Fed's pivot, while the real focus should be on how core CPI and interest rate expectations jointly reprice BTC and ETH’s sensitivity and risk premiums in this inflation trade.

Core CPI Stickiness: The Cost of Staying at High Interest Rates

The market's expectation of June's core CPI month-on-month at around 0.21% is almost flat to May's level, essentially telling the Fed: price pressures are still present but not out of control. This “sticky range” that is neither out of control nor declining rapidly fits exactly at the edge of the Fed's comfort zone—insufficient to support aggressive rate cuts, yet raising the political cost of “policy misstep-style easing.” In the past few quarters, the Fed has repeatedly emphasized that core inflation needs to “sustainably and significantly” decline before it might adjust its stance, and now that core CPI is locked in at around 0.2%, it suggests that policy rates are more likely to remain at high levels awaiting further evaluation rather than make a rapid descent. For asset pricing, this is not a debate over a few basis points for the future, but a rewriting of the entire “how long high rates should last” discounting framework.

Once the consensus of “higher, longer” risk-free rates emerges, all assets supported by forward stories will be repriced: technology stocks and AI concepts will need to use higher discount rates to calculate cash flows over the next decade. The curve of about $5.8 trillion in AI infrastructure investment that Goldman Sachs describes will appear steeper and more expensive when viewed on the interest rate curve; the nearly $200 billion in corporate bonds and about $90 billion in project loans financing this curve will also see their credit spreads more easily widen due to any “AI returns failing to meet expectations.” This logic is not unfamiliar to the crypto market—during the 2022-2023 interest rate hike cycle, BTC and ETH already demonstrated their high sensitivity to interest rate expectations through a complete valuation compression. Under the current “high rates lasting longer” framework, they will be traded as purer high-beta chips: investors will demand higher risk premiums, current prices must show discounts, and volatility must increase enough to attract marginal funds moving out of bonds and tech stocks. Ultimately, all of this will settle into the repricing of BTC and ETH’s price elasticity and risk premiums following each release of core CPI data.

$5.8 Trillion in AI Infrastructure: The New Bubble Wall Street is Betting On

While the market is still betting on the Fed's path based on the next core CPI, another capital tide has quietly formed. Goldman Sachs’ calculations depict the future capital expenditures of Google, Amazon, Meta, Microsoft, and Oracle as a new “macro mainline”—before 2030, these five companies’ cumulative investment in AI data centers and computing facilities could reach about $5.8 trillion. This year, they have already begun to test the waters: issuing nearly $200 billion in corporate bonds collectively and borrowing about $90 billion through joint projects for data centers. AI is no longer just an equity story; it has become a core source of demand in the credit market. If the Fed's “higher rates longer” serve as a ceiling on risk assets, this wave of AI-induced debt expansion creates a new channel breaking through the floor of the credit market: one side is viewed as an “unmissable” long-term infrastructure bet, while the other is the anxieties of bond investors regarding whether the risks of project failures and underperforming profits are underestimated. Once the latter is repriced and credit spreads widen, the entire risk asset chain will need to be reevaluated.

The stock market has already provided the first round of feedback. The AI theme has propelled U.S. large tech stocks into a new expansion cycle, with every breakout in the Nasdaq sending the same signal to global capital: tech risk appetite has returned. In this framework, BTC and ETH are repositioned as “high-beta assets at the edge of tech stocks”—when large-cap tech stocks driven by AI concepts strengthen, investors overall adjust up their tolerance for growth risk in their portfolios, resulting in a noticeable increase in correlation between tokens related to computing power, AI narratives, and these tech stocks over the past year, forming a risk appetite spillover effect from AI stocks to crypto assets; conversely, if the market begins to question the return on this $5.8 trillion investment or fears the hidden credit risks behind nearly $300 billion in early financing, a pullback in tech stocks and rising spreads will trigger cross-asset deleveraging. The concurrent contraction of on-chain dollar-pegged asset supply and exchange BTC and ETH balances will appear, accelerating the “reverse spillover” of risk appetite from AI to crypto, meaning that this round of super capital expenditure in AI infrastructure is becoming the second macro mainline influencing BTC and ETH pricing, following core CPI and interest rate expectations.

$200 Billion in Corporate Bonds, $90 Billion in Loans: The Fragile Chain of AI Financing

While everyone is focused on a couple of digits in core CPI, another thicker lever is silently extending: to support the estimated $5.8 trillion AI infrastructure plan by 2030, Google, Amazon, Meta, Microsoft, and Oracle have together issued nearly $200 billion in corporate bonds this year and borrowed about $90 billion through joint projects for data centers. This is not ordinary balance sheet expansion; it is packaging forward, highly uncertain AI cash flows into current credit duration risks and pushing them onto the asset-liability balance sheets of the entire bond market, all while interest rates remain high.

The problem is that the punishment in bond pricing for “project failures” and “underperforming profits” is evidently not harsh enough. If at some point in the future the market is forced to acknowledge that the returns on these AI projects cannot cover financing costs, the first to react will not be the projects themselves but the sudden widening of credit spreads: high-yield bonds and high-valuation growth stocks will be sold off first, triggering cross-asset deleveraging as funds simultaneously withdraw from tech stocks and credit products, starting to clean up all high-volatility positions. In such a compression cycle, BTC and ETH are often sold first due to their superior liquidity, leading to a contraction of on-chain dollar-pegged asset supply and rising exchange balances, causing prices to quickly pull back. This fragile financing chain from AI corporate bonds to crypto assets will manifest in the form of “credit contraction.” For crypto traders, the movements of the credit spreads related to AI debt are becoming an important macro observation variable alongside core CPI.

Choices of Funds Under the Narrative of Interest Rates and AI

In the current context of overlapping narratives of high interest rates and AI debt expansion, global asset management institutions are essentially rebalancing portfolios by continuously adjusting among three types of exposures: first is the still attractive risk-free rates and high-grade bonds; second is tech growth stocks supported by the story of $5.8 trillion in AI investments; and third are high-beta assets like BTC and ETH, which are highly sensitive to macro and sentiment. The stickiness of core inflation means that policy rates are unlikely to decline rapidly, the yields from extending bond durations are limited, while tech giants have elevated AI theme stocks to a new valuation level by issuing nearly $200 billion in corporate bonds and jointly raising about $90 billion in debt for data centers, embedding tail risks of credit spread repricing into both equity and bond ends. In this structure, an increasing number of institutions will view BTC and ETH as risk factors comparable to the Nasdaq but with different styles: they do not provide cash flow but are extremely sensitive to interest rate expectations and risk appetite, capable of bearing the most elastic layer of risk in a portfolio within the range of “interest rates peaking but not declining soon.”

The structure of on-chain and off-chain funding provides real-time feedback for this adjustment. The expansion of on-chain dollar-pegged asset supply often corresponds with off-chain capital entering the crypto system through compliant channels, whereas a decline in exchange BTC and ETH balances is often interpreted as holders extending their holding period and reducing the supply of sellable tokens. In an environment where AI theme stocks are at highs and bond investors are concerned about widening credit spreads, commonly seen trading structures will evolve into: a portion of funds reducing allocations to individual AI high-beta stocks while increasing allocations to BTC or ETH to hedge against potential earnings distortion from single AI projects; another portion will directly trade the relative strength of “long AI stocks, short BTC/ETH” or reverse combinations, trading the “AI debt story vs macro interest rate path.” As core CPI and AI giant earnings reports collectively drive swings in interest rate expectations and credit sentiment over the next few months, the simultaneous changes in on-chain dollar asset supply and exchange BTC and ETH balances will be a key indicator in judging whether funds choose to crowd into the AI debt narrative or shift towards crypto as a more pure risk factor.

Inflation Path and AI Leverage: The Next Step for Crypto Traders

When the “mouthpiece” fixes the spotlight on core CPI, and AI giants write long-term leverage checks with trillions of capital, global risk appetite in the coming months will in fact be directed by two curves: one for core inflation and interest rate expectations, and one for AI investment and credit spreads. The June CPI, followed by PPI and PCE, will determine whether the market bets on “core inflation truly declining and interest rates peaking and falling,” or is forced to acknowledge the greater stickiness, with longer rates and discount rates staying high for longer; AI data center inputs and debt progress will continually be re-evaluated in tech stock valuations and the credit market; once the market believes a significant portion of the $5.8 trillion plan is unlikely to break even, the fluctuations in tech stock indices and credit spreads will rapidly spill over to other high-beta assets. For the bulls and bears of BTC and ETH, traders will need to monitor several sets of signals: the repricing of core CPI, PPI, and PCE on the interest rate futures curve, the direction of the dollar index and U.S. Treasury yields, the performance of Nasdaq and other tech stock indices during AI earnings season, and the synchronous changes of on-chain dollar asset supply and exchange BTC and ETH balances around data release and earnings windows—where the former determines whether the “discount rate” measurement shortens, the latter indicates whether capital is willing to pull away from the AI debt story and turn towards crypto as a more pure risk factor. As long as core CPI and AI leverage remain tugged in these two main lines, the main task of the crypto market will not be to predict a single price target, but to dynamically adjust the weight of BTC and ETH positions between the scenarios of “interest rate easing and AI tailwind” and “interest rate stickiness and AI pullback” around these macro and credit indicators.

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