SoftBank has agreed to acquire DigitalBridge in a deal valuing the digital infrastructure investor at roughly $4 billion, including debt. The transaction, if it closes, would take DigitalBridge private at $16 per share in cash.
SoftBank says the acquisition is intended to accelerate its global AI infrastructure strategy by giving it direct access to data center development pipelines, financing mechanisms, and power-constrained real estate as AI compute demand collides with physical limits. SoftBank’s founder, Masayoshi Son, has been repositioning the company around AI after years of mixed results from its Vision Fund strategy.
SoftBank's deal comes days after Alphabet announced that it would acquire Intersect — another provider of data center and energy infrastructure solutions — for $4.75 billion in cash. Taken together, the two deals demonstrate how AI infrastructure planning is moving upstream into power origination and grid access, rather than continuing to focus solely on server procurement.
A power and financing platform
DigitalBridge, a specialist investor and asset manager, does not operate data centers in the way hyperscalers do. It functions as an infrastructure investment and management platform that raises capital, acquires or develops assets, and places operational teams around them. According to its most recent public disclosures, DigitalBridge manages more than $100 billion in digital infrastructure assets across multiple portfolios. Within its data center holdings, the company says it has a "power bank" of around 22 gigawatts across land it owns, facilities already operating, and projects under development.
Modern AI data centers are increasingly defined by how quickly developers can secure grid connections and deliver reliable power at densities far above historical norms. DigitalBridge has been clear that its competitive advantage lies in sourcing entitled land with power access, financing long-duration infrastructure, and then pairing those assets with operators or hyperscalers. Its portfolio includes well-known data center platforms such as Switch, Vantage Data Centers, DataBank, AtlasEdge, Yondr, and AIMS, alongside Takanock, a vehicle created specifically to assemble powered land for future data center builds.
This solves a problem for SoftBank that money alone cannot fix. AI compute buildouts are increasingly bottlenecked by physical infrastructure rather than silicon supply. Even when accelerators are available, bringing a new AI facility online can take years due to grid interconnection queues, local permitting, and the need to design cooling and power delivery systems that can sustain extremely high continuous loads. DigitalBridge’s model is designed to compress those timelines by doing the slow work in advance and spreading capital risk across long-term infrastructure funds rather than a single corporate balance sheet.
Why AI data centers are different
Traditional enterprise and cloud data centers were built around rack densities measured in single-digit or low double-digit kilowatts, but AI systems have surpassed that by a significant margin. Training clusters built around modern accelerator pods routinely target rack densities that approach or exceed 100 kilowatts, forcing fundamental changes in power distribution and cooling architecture.
These requirements ripple through the entire facility, with high-density AI racks demanding liquid cooling, often with direct-to-chip cold plates and increasingly with rear-door heat exchangers or full immersion in some designs. Power distribution moves away from conventional raised-floor layouts toward busways, higher-voltage feeds, and redundant substations sized for continuous peak load. Water availability, heat rejection, and serviceability become first-order constraints rather than secondary design considerations.
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