AI Spend Is Now Paying Off Inside Portfolio Companies

What's New Blackstone argues the return on AI spending has moved from forecast to evidence inside its own portfolio. Jon Gray made the case at the firm's September 2026 annual meeting. Blackstone tracks AI spend across 1,400 portfolio companies, GP stakes, and borrowers. Their spend on Anthropic reached $525 million annualized. That is a 21-fold increase from September 2025. Gray paired the spend with company-level results, including a 5x speed gain in lease processing at Phoenix Tower. Allocators can now ask managers for measured AI returns at the company level.

Why It Matters

The finding challenges the view that AI capex is a bubble with no downstream payoff. Private equity software owners are on the exposed side. Fear of AI obsolescence compressed software multiples, often for businesses Gray says were fine. PE software deal activity fell 66%. Gray's retail parallel sets the filter. Systems of record that move from per-seat to outcome-based pricing survive, as Walmart and Costco did. The rest face the Sears outcome.

By The Numbers

• $105 billion combined annualized run rate at Anthropic and OpenAI as of July.

• $820 billion in capex from the top five hyperscalers, about double the prior year.

• 700 basis points of EBITDA margin expansion at Blackstone portfolio companies over four years. The S&P gained 500.

• 32% portfolio earnings growth over the last 12 months. The prior average was 15%, and Gray is unsure the new pace will last.

• 2.6% annualized US labor productivity growth over the past 2.5 years. The 10-year baseline was 1.5%.

Between The Lines

Gray speaks as an owner on both sides of the trade. Blackstone invested in Anthropic and OpenAI, so part of the portfolio's Anthropic spend flows to a company the firm owns. Its data center leasing is projected to reach at least 6 GW in 2026. AI-related investments, including the model company stakes, made up 9 of the firm's 10 top-appreciating assets in Q2. The ROI evidence is a curated set of case studies from its own companies.

Gray also hedges unevenly. He says it's hard to know how much of the productivity gain is AI-driven. He then says adoption is "of course" showing up in margins, with no such caveat. The margin gain spans four years. The Anthropic spend jump spans one. He never addresses how fast chips lose value. If chips need replacing within a few years, the payback window on much of this capex is shorter than for the power and real estate around them. The most useful claim for allocators is the supply bottleneck. Turbine and chip shortages favor owners of power and grid assets.

The Wrap

Senior exposure to compute is where Gray says Blackstone has the most confidence. That is the clearest signal for private markets investors: hold the part of the stack paid first while demand outruns supply. The case holds while contracted power and data center capacity stays with low-leverage tenants. Gray argues a cyber-driven regulatory response would not stop diffusion. A disruption to chip supply from Taiwan is the harder risk. The test runs through 2030 to 2031, the current lead time for heavy-duty turbines.