Up until now, when it comes to real estate, Blackstone was best known in recent years for dumping many of its trophy office properties - which in the aftermath of work from home never recovered their projected cash flow potential - at a huge discount. Now, it may be pulling a page from its old, pre-Lehman playbook by calling the top in yet another commercial real estate segment: data centers.
According to Bloomberg, Blackstone is selling its stakes in a trio of data centers across Northern Virginia for $3.5 billion, cashing out of part of a bet it made less than three years ago.
Digital Realty Trust will pay $1.2 billion of cash and offer $2.3 billion of its shares to Blackstone funds, the firms said in a statement Monday. In exchange, the data center company will acquire Blackstone’s 80% interest in two 96-megawatt data centers in Manassas, Virginia, and a 50% interest in a 96-megawatt center in nearby Sterling.
The assets involved in this week’s sale were part of a joint venture that Blackstone announced it would set up with Digital Realty in 2023 as it sought to get ahead in the AI arms race that has engulfed Wall Street in recent years. Blackstone and Digital Realty will continue to work together on their remaining data center investments located elsewhere in Northern Virginia as well as in Paris and Frankfurt.
“We have developed a strong partnership with Blackstone,” Greg Wright, Digital Realty CEO, said in the statement. “This transaction reflects the next phase of that relationship, allowing us to increase our ownership in a portfolio of fully leased, high-quality hyperscale assets.”
It does. The question is why did Blackstone decide to pull the cord now, just as fresh doubts are creeping whether the Mag 7s will continue funding the AI expansion with virtually unlimited capex.
As part of Wall Street’s broader push into data centers, investment has poured into Northern Virginia, which is considered the country’s largest data center market, and is better known as "Data Center Alley".
That includes Digital Gateway, an ambitious plan for a 2,100-acre corridor in the region that would house as many as 37 data-center buildings.
Data center developers eyeing that land have faced strident opposition. Compass Datacenters, backed by Brookfield Asset Management, recently pulled out of a yearslong effort to build a key part of the development after facing intense pushback from local residents. Blackstone’s QTS is also fighting in court to salvage a similarly sized development on adjacent parcels.
The increasingly vocal political and grassroots pushback against new data center construction may explain why Blackstone is getting cold feet just as the AI bubble is peaking. A recent Gallup poll found that 7 in 10 Americans oppose constructing data centers for artificial intelligence in their local area, including nearly half, 48%, who are strongly opposed. Barely a quarter favor these projects, with 7% strongly in favor.
Half of opponents mention data centers’ excessive use of resources, including 18% each mentioning their use of water and energy. Sixteen percent mention a related environmental concern of pollution, including noise pollution and air and water pollution.
About one in five opponents are concerned with the impact on local quality of life, including increased population, increased traffic and preferring that the land be used for other purposes. A similar share mention potentially negative economic consequences, including higher utility bills, cost-of-living increases, and the cost of building the data centers (which could involve the use of taxpayer funds).
Most of the remaining opposition stems from general or specific concerns about artificial intelligence.
Blackstone, which manages more than $1.3 trillion, bills itself as the largest global provider of data centers, and also owns some of the utilities that power them. It acquired QTS in 2021 and bought Australian computing provider AirTrunk in 2024. In May, the firm held an initial public offering for Blackstone Digital Infrastructure Trust Inc., its data center acquisition vehicle, which aims to buy already built and leased properties benefiting from the artificial intelligence boom.
The firm has more than $150 billion of data center assets, and it has identified an additional $160 billion worth of opportunities for its pipeline, CEO Steve Schwarzman said in April.
Affiliates of Blackstone are already selling the Digital Realty equity they’re set to receive from this week’s deal, which is expected to be completed Tuesday. They’re offering the stock at as much as a 2.9% discount to Monday’s closing price of $190.58, Bloomberg reported citing people familiar.
Tyler Durden Tue, 06/30/2026 - 13:25In his market note published this morning, Apollo's chief economist Torsten Slok delivers a scathing review of the failure of AI to boost profit margins outside of tech... which of course is what AI is supposed to do since it is meant to boost productivity across the entire economy, not just a select group of chipmakers.
As Slok shows in the chart below, so far there are no signs of profit margins rising outside the tech sector. He notes that "this is ultimately what we are waiting for, because the value of AI companies today rests entirely on the promise that margins in the S&P 493 will eventually climb."
As Slok notes, the promise of higher margins for all is the link to current (soaring) market prices, since implicit in the valuations of AI companies are assumptions about future earnings. That's why the current debate about token costs, model routing and token marketplaces is important. If token costs converge toward zero for most AI use cases, then there is not enough revenue for all hyperscalers even in a situation where compute demand surges higher, Slok cautions stomping all over the now traditional "but Jevon's paradox" counterargument. (for more discussion, Slok recommends reading this piece from his colleagues in Apollo Thematic Investing).
Going back to the matter at hand, the key issue is the length of the ROI runway outside the tech sector. In a handful of sectors, software and tech above all, implementation is nearly immediate, since these firms can fold AI into their own products and processes overnight (ironically, it is the same software sector that has been crushed in 2026 due to doubts over the terminal values of ventures which may well be made obsolete by the same AI that is meant to boost their margins).
But that is the exception. Across most of the economy, and especially in capital-intensive, heavily regulated sectors, deep process re-engineering and data governance requirements could delay structural productivity gains well beyond what the market currently projects. The list of slow-moving sectors is long, spanning health care, banking and insurance, energy and utilities, defense and aerospace, pharma and life sciences, manufacturing, transportation and logistics, construction and real estate, education, legal and the public sector.
This, according to Slok, creates a dangerous divergence between aggressive, front-loaded valuations today and a much slower cash flow reality, since equity markets priced for instant earnings growth will face a painful repricing if the productivity hockey-stick takes five years rather than five months.
Put differently, companies will slow their AI spending if they don't see ROI quickly, and the current focus on token optimization is an early warning that AI implementation could be a bumpier, slower road than expected.
Slok's bottom line is that a mismatch between current earnings expectations and the actual time firms need to generate ROI on AI investments could have significant implications for many AI company valuations today
Tyler Durden Tue, 06/30/2026 - 13:00