AI's $800B Spending Boom Becomes Bitcoin's Fed Problem

For the better part of two years, Wall Street has treated AI as the most bullish trade on the board, a growth engine that turbocharges earnings, underwrites stretched valuations, and promises a productivity windfall somewhere down the road. The Fed, however, has access to the same numbers and seems inclined to view the AI build-out as a fresh source of demand in a market still wrestling to drag inflation back toward its 2% target.

Goldman Sachs now expects AI-related capital spending to approach $800 billion in 2026, calculating the surge will lift its full-year business investment forecast to 7.8% while adding roughly 3.3 percentage points to capital-expenditure growth on its own. TrendForce, tracking the nine largest cloud providers in the world, places their combined 2026 outlay near $830 billion, a jump of about 79% over the previous year. A meaningful slice of that increase reflects rising prices rather than added capacity, with Microsoft attributing some $25 billion of its $190 billion budget to costlier memory and components. All of it puts considerable weight on the inputs the Fed tends to watch most closely, which could turn this investment boom into a policy headache.

Where does the $800 billion in AI spending actually go? It helps to imagine it in physical terms. All of that money takes the shape of land, steel, transformers, copper wiring, gigawatts of fresh generation capacity, industrial-scale cooling, and the incredibly skilled and incredibly rare trades hired to assemble the whole thing. Goldman described this as a wave reaching across servers, semiconductors, memory, power infrastructure, data centers, software, and research budgets, with the bank's longer-range model tracing annual AI capex climbing from around $765 billion this year toward $1.6 trillion by 2031.

Power has become the binding constraint. In a late-May speech, Fed Governor Lisa Cook noted that electricity and water prices have each climbed about 5% over the past year, that chips, high-tech equipment, and software have all grown more expensive, and that wages in specialty construction trades have picked up notably. Households feel some of that pressure on their monthly bills, which began drawing political pushback as several state legislatures move to slow large data-center development.

The central bank's leadership has been unusually direct about where this leads. Speaking back in March, Jerome Powell told reporters that the construction frenzy was "putting pressure on all kinds of goods and services that go into building these things," and he conceded the effect was "probably pushing inflation up." Cook went further in that same May address, warning that "yet another shock to prices could be layered on from the heightened investment demand due to AI" and pointing out that companies have announced more than $1.5 trillion in data-center plans, only a sliver of which has actually been built. The demand side of AI, in other words, is showing up in the price data well ahead of any productivity payoff the technology eventually delivers.

What it means for Bitcoin's rate-cut bet

The consequences travel from Silicon Valley balance sheets straight into crypto. Bitcoin spent most of the year leaning on the expectation that cooling inflation would free the Fed to cut rates, loosen financial conditions, and rekindle the risk appetite that powered the 2024 rally. CryptoSlate has documented how tightly the asset now tracks liquidity cycles, a sensitivity that has overtaken Bitcoin halving as the dominant price driver. An $800 billion demand shock makes rate cuts unlikely, since every dollar of AI-related price pressure hands the Fed one more reason to stay put.

Markets have already begun repricing that. Futures and prediction markets now put the odds of a hold at the June 16-17 meeting above 93%, which will be the first one chaired by Kevin Warsh following his May handover from Powell. CryptoSlate has tracked the