Former New York Federal Reserve President Bill Dudley broke the current narrative of "AI = pure technology story" around October 21, 2026, elevating it directly to the level of interest rate paths: in his view, the capital expenditure on AI infrastructure flowing into data centers, chips, and computing power in recent years is simultaneously pushing up economic growth rates, asset prices, and financing demand, exerting upward pressure on both real and nominal interest rates in the U.S., which has been underestimated by Wall Street. Based on this, he depicted a distinctly different interest rate trajectory— the Federal Reserve may continue to raise rates or maintain high rates during the AI boom phase, leading the peak interest rates to be significantly higher than the current market's forward pricing; then, once AI capital expenditure peaks, financing conditions worsen, and investments shift from being a driver to a drag, the Fed will be forced to initiate a sharp reversal of "substantial rate cuts," resembling a classic interest rate roller coaster, rather than a linear decline. Within this framework, all current market quotes for forward rates and future rate cuts may need to be rewritten. For high-risk assets including BTC and ETH, it is not the "AI concept" that is truly being repriced, but rather the path of the discount rate itself: the high-rate phase raises the discount rate, compresses valuations, and draws away some risk capital that was originally rotating between crypto and tech stocks. The subsequent easing period will alter the relative attractiveness of dollar assets versus crypto assets, reshaping on-chain dollar yield products and interest rate-related trading structures. This makes Dudley's "AI interest rate roller coaster" assessment a key exogenous variable in the pricing logic of BTC and ETH for the coming years.
How AI Capital Expenditure Pushes Up Interest Rates
In Dudley's narrative, the current massive capital expenditure on data centers, chips, and computing power for AI is not just another tech cycle, but a real demand shock for funds. These investments are large in scale and long in cycle, requiring continuous financing and reinvestment, competing for limited funds along with government debt, traditional corporate expansion, and household credit. The result is that while economic growth rates and asset prices are elevated, the balanced real interest rate is pushed to a higher level, raising the overall "base price" of borrowing. Dudley views AI as an important force driving economic growth and funding demand, which in turn elevates interest rates, and this force is far from peaking at the current stage.
From the perspective of the interest rate curve, this means that the upward pressure on the short end may be stronger than what the market has already reflected in its forward rate pricing of a "higher but stable" path. If the Federal Reserve faces more stubborn demand and inflation, it can only increase rates at the front end or extend the time spent at high levels, thereby narrowing policy choice space due to AI capital expenditure. This sets the stage for the so-called "first raise, then significantly cut" roller coaster trajectory. For traditional high-volatility risk assets, higher real interest rates directly increase the cost of capital, compressing the valuations of tech stocks and growth stocks. For the crypto market, BTC, ETH, and a range of on-chain dollar yield products will also need to recalculate future cash flows and risk premiums using a higher discount rate. Currently, many asset prices are still being priced according to a mild interest rate cycle, overlooking the potential for underestimated interest rate rises and volatility brought by AI investments, which lays a time bomb for subsequent concentrated repricing and cross-asset misalignment as AI capital expenditure continues to grow.
Interest Rate Roller Coaster Rewrites BTC/ETH Pricing
In Dudley's path hypothesis, AI capital expenditure first pushes interest rates to higher levels, and then forces the Federal Reserve to make significant cuts once it peaks. This means BTC and ETH will have to first go through a stage where they are held underwater by a "high discount rate." Short-term interest rates exceeding expectations push up the risk-free rate in valuation models, directly raising the risk premium requirements for crypto assets: the same on-chain cash flow and network usage data are converted into lower fair prices under a higher discount rate. For institutional investors, the adjustment of weight in asset allocation models centered on interest rates and macro liquidity reduces high-volatility BTC and ETH from being considered "growth assets that can be increased" to "risk exposures that lack cost performance compared to high-yield dollar assets.” Additionally, themes related to AI and tech stocks have drawn away substantial risk capital, leaving the crypto circle often to serve as a passive tool for deleveraging and hedging rather than a proactive battleground for speculation.
The real turning point occurs in what Dudley calls the "latter half of the process": as AI investment shifts from a driving force to a drag, the Federal Reserve is forced into a substantial rate-cutting cycle, and the discount rate environment instantaneously changes from suppression to support. The downward segment of the interest rate roller coaster will reignite global liquidity expansion; the risk appetite that typically accompanies easing cycles will easily lead previously suppressed growth assets to undergo concentrated recovery, with BTC and ETH again becoming "high-beta chips" for institutional investors rotating among stocks, on-chain dollar yield products, and other dollar assets. Rate cuts bring not only price elasticity magnification but also a rewriting of trading structures: shifting from a defensive period using high rates to earn dollar interest differentials to an offensive period using lower rates to boost duration assets and leveraging crypto assets. Under the interest rate roller coaster path described by Dudley, the core pricing of BTC and ETH is no longer the narrative itself, but the ability to judge the timing of the discount rate turning point.
Funding Battle: Rotation Between AI Stocks and Crypto
In Dudley's narrative, the high-rate phase is not a "vacuum," but one filled with AI capital expenditure. The investment boom in data centers, chips, and computing power boosts economic and funding demand, and Wall Street's most direct reaction is to direct funds towards technology and semiconductor sectors in the equity market: these companies can tell the AI growth story while also providing cash flow and buyback expectations, making them easier for investment committees to approve compared to purely high-beta BTC and ETH in an environment where the discount rate is raised. The result is that tech stocks and crypto, both part of the "high-risk asset basket," become embroiled in a funding battle—incremental funds chase AI-themed equities first, leaving higher discount rates and thinner liquidity premiums for on-chain assets.
However, this battle for funds is not one-dimensional. Dudley warns that once the growth rate of AI capital expenditure slows or financing conditions worsen, this force that previously pushed asset prices up will quickly shift from being a growth driver to an economic drag, and high rates will negatively evolve into an aggressive rate-cutting cycle. At that time, the valuation narrative for tech stocks will face both earnings revisions and severe re-pricing expectations for interest rates, while the narrative for crypto assets will shift to "pure liquidity + high-beta leverage": in the latter half of the interest rate roller coaster, funds will withdraw from the crowded AI stocks at high levels, seeking assets that are most sensitive to rate cuts and not directly exposed to corporate earnings declines, allowing BTC and ETH's relative advantages to emerge. The real focus should be on the turning point of AI capital expenditure and the momentum in the U.S. tech sector, as they will determine the scale and pace of the next wave of funds flowing back from AI stocks to BTC/ETH.
Post-Substantial Rate Cuts: The Dollar and On-Chain Yields
When the "latter half of the process" envisioned by Dudley begins, and the Federal Reserve is forced into a significant rate-cutting cycle, the first thing that gets rewritten is the yield curve for the dollar: short-term yields quickly decline from the previously elevated positions pushed up by AI investments, while the long-term end begins to reprice weaker growth and inflation expectations, shifting the entire curve from "higher for longer" to "lower for longer." The narrowing of interest spreads diminishes the attractiveness of global risk-free dollar assets, while the strong dollar's monetary dividend begins to fade, shifting the focus of rebalancing funds from "which dollar assets are safer" to "which non-dollar assets exhibit the greatest resilience during the easing cycle," reopening exposure to high-volatility, high-beta crypto assets.
In recent years, on-chain dollar yield products and off-market interest rate instruments have essentially been repackaging U.S. short-term rates: translating treasury yields and money market rates into various dollar-denominated token yields. The lower segment of the interest rate roller coaster means that the natural yield of these products will be continuously compressed, making the narrative of "earning the spread effortlessly" less attractive, with fewer investors willing to hold on-chain dollars for yields. More people begin to recalibrate, comparing the compressed interest yields with the potential volatility space of BTC and ETH during the easing cycle. Historically, every round of significant rate cuts leads crypto trading to shift from interest rate arbitrage and dollar yield farming back to trend trading and volatility trading—moving from earning interest toward trading volatility. Those who can identify the timing of this strategy switch first will have the opportunity to position themselves favorably in the next main battlefield of risk preference recovery at the end of the interest rate decline.
How Traders Price AI Interest Rate Risks
In the interest rate roller coaster described by Dudley, where there are "first rate hikes, then significant cuts," AI investment actually becomes the invisible main driver of crypto asset pricing: as capital expenditure on data centers, chips, and computing power remains high, economic and funding demand continue to rise, increasing upward pressure on short-term rates, and raising the discount rate, valuations for long-duration risk assets like BTC and ETH will be compressed, with funds preferring to stay in dollar rate products and AI-themed assets; once AI spending peaks or the financing environment tightens, growth dynamics shift to being a drag, and the Fed's language and dot plot begin to slide from "higher for longer" towards easing expectations, rate futures and swaps will first reflect a path of halting rate hikes or even rapid cuts, narrowing the coupon advantages of on-chain dollar yield products, and BTC and ETH's relative attractiveness will reemerge in asset rotation. For crypto traders, pricing this interest rate path begins with treating the intensity of AI capital expenditure as a new macro-leading indicator, closely monitoring corporate capital expenditure cycles and changes in financing environments; next, they must read the Fed's forward guidance, proactively adjusting risk preferences and position durations based on subtle shifts in language and dot plots; finally, calibrating expectations for the time windows of "squeeze during high-rate phases" and "repair during easing phases" through the implied path of rate futures and swaps. In practice, an uncertain interest rate path means rapidly deleveraging, shortening liability durations, reducing unhedged long-duration exposures, while using multi-asset hedges (such as appropriately allocating interest-sensitive assets or options protection), layered position structures, and rolling stop losses to transform AI-driven interest rate volatility from an unpredictable black swan into a core variable quantifiable and manageable within trading books. For traders, the true core task is to unify and translate the AI capital expenditure curve, Fed language, and the prices of interest rate derivatives into actionable positions and risk control thresholds.
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