Nvidia & BlackRock Lead $40B Data Center Deal: AI Infrastructure Race Escalates

 

In a major strategic move, Nvidia and BlackRock are heading a consortium to acquire Aligned Data Centers in a $40 billion deal, marking one of the largest AI infrastructure investments ever announced. The acquisition part of a greater push into AI compute infrastructure signals strong confidence in the long-term growth of data center demand. 

The investor group includes BlackRock, Nvidia, Microsoft, xAI, MGX, and Global Infrastructure Partners (GIP). Under a new vehicle called the Artificial Intelligence Infrastructure Partnership (AIP), the group plans to invest $30 billion in equity with capacity to scale to $100 billion including debt financing. 

Aligned Data Centers operates over 50 campuses across the U.S. and Latin America, delivering more than 5 gigawatts of capacity (existing and planned). The company will stay headquartered in Dallas and remain under the leadership of CEO Andrew Schaap.

Why This Deal Matters (Beyond the Price Tag)

1. Strategic play in AI compute infrastructure
As AI models grow more complex, demand for high-performance compute and scalable infrastructure is skyrocketing. By acquiring a major data center operator, the consortium locks in vital capacity in a space with heavy barriers to entry.

2. Turning capital into capacity
The $40B figure includes planned expansion. This isn't just buy-and-hold real estate it's aggressive scaling. The consortium’s goal is to build new campuses, increase power and cooling efficiencies, and push into regions with underserved infrastructure needs. 

3. Spreading risk among heavyweight partners
Instead of a single company shouldering all operational and capital risk, risk is distributed among tech, infrastructure, and investment giants. This consortium model is a bet on synergy: capital + engineering + operational expertise together. 

4. Off-balance-sheet strategy for hyperscalers
For tech companies that want rapid expansion, owning data centers means heavy capital burden. The consortium model allows hyperscalers to lease capacity instead of owning it directly freeing up balance sheet capital for other bets. 

5. First major test of AIP’s vehicle
This is AIP’s first deployment of capital. If it succeeds, it could become the leading investment platform for AI infrastructure over the next decade. 

Risks and Challenges Ahead

• Regulatory scrutiny: Deals of this size, especially in infrastructure, may face antitrust review or regulatory hurdles.

• Execution risk: Building data centers is capital and engineering heavy delays, cost overruns, or supply constraints can derail ROI.

• Energy & sustainability: Data centers demand enormous power. Tension between growth and carbon or local grid capacity could draw public or regulatory pushback.

• Market timing & tech shifts: If AI compute needs shift architectures rapidly (e.g., toward edge, compact designs, or new cooling tech), brute-force capacity might become less competitive.

FAQs

Q1: What exactly is being acquired?
A1: The consortium will acquire 100% equity of Aligned Data Centers, a firm with 50 campuses and over 5 GW of capacity across the U.S. and Latin America. 

Q2: When will the deal close?
A2: The transaction is expected to close in the first half of 2026, contingent on regulatory approvals and customary deal conditions. 

Q3: Which companies are part of the consortium?
A3: The consortium, called AIP, includes BlackRock, Nvidia, Microsoft, xAI, MGX, and Global Infrastructure Partners (GIP). 

Q4: Why $40 billion? Is that for buying or expanding?
A4: The valuation covers acquisition plus planned expansion. The group intends to deploy fresh capital to scale existing sites and build new ones.

Q5: How does this impact AI infrastructure competition?
A5: It raises the bar. The deal crowds in institutional capital into AI data centers, intensifies competition, and might prompt similar moves by Google, Amazon, and others.

Q6: What are key risks to watch?
A6: Execution challenges, power and cooling constraints, regulatory reviews, and shifts in technology architecture (like AI moving toward smaller, distributed compute) are all risks.