SoftBank’s DigitalBridge deal shows AI impact on telecom networks

For much of the past decade, telecom infrastructure investment followed a familiar playbook. Capital flowed into towers, fibre, and data centres as long-term, yield-driven assets. Growth was steady, demand was predictable, and returns were shaped more by tenancy rates than by how networks were actually used.

That model is starting to change.

SoftBank Group’s agreement to acquire DigitalBridge is less about owning more infrastructure and more about positioning for how demand is shifting as AI workloads reshape traffic patterns, compute needs, and network design. The deal offers a useful case study in how investors and operators are beginning to rethink what “strategic infrastructure” means in an AI-driven environment.

From passive assets to active systems

DigitalBridge’s portfolio spans data centres, fibre, towers, and edge infrastructure across multiple regions. On paper, this looks like a conventional infrastructure play. In practice, it reflects a bet that these assets will no longer operate as passive capacity but as active systems tied closely to where compute is generated, processed, and consumed.

AI changes the profile of network demand. Large models require dense compute in central locations, but inference, analytics, and real-time services increasingly push workloads closer to users and devices. That shift puts pressure on data centre placement, backhaul capacity, and latency management in ways that traditional telecom planning models were not built for.

For operators, this means infrastructure decisions are no longer just about coverage and scale. They are about how well networks can support uneven, bursty, and compute-heavy traffic that does not behave like consumer video or voice.

Why infrastructure ownership matters again

Over the past few years, many operators moved away from owning infrastructure outright. Towers were spun off—fibre assets were shared or sold down. Data centres were outsourced to specialist providers. The logic was clear: free up capital and focus on services.

AI complicates that logic.

When compute location, data movement, and network control start to affect service quality and cost in real time, ownership and influence over infrastructure begin to matter again. Operators may not need to own everything, but they do need tighter alignment between network assets and the workloads running on them.

SoftBank’s move suggests that large investors see value in controlling infrastructure platforms that can be tuned for AI demand rather than simply leased out as neutral capacity. This is not about reversing asset-light strategies overnight, but it does point to a more selective approach to where control is retained.

What SoftBank’s AI infrastructure bet means for operators

For telecom operators, the lesson is not to copy SoftBank’s investment strategy. It is to recognise that AI is changing the assumptions behind network planning and partnerships.

Operators are already seeing this in areas such as:

• Edge deployments, where demand is driven by enterprise use cases rather than consumer traffic
• Private networks, where AI workloads require predictable performance and local processing
• Interconnect strategy, as data centre-to-data centre traffic grows faster than access traffic

These pressures make infrastructure decisions harder to outsource without losing flexibility. They also raise questions about how operators price connectivity when value is increasingly tied to performance rather than volume.

How SoftBank is positioning infrastructure for AI-driven demand

DigitalBridge’s appeal lies in its ability to operate across multiple infrastructure layers rather than in any single asset class. That flexibility matters as AI blurs the lines between telecom, cloud, and data centre economics.

Infrastructure investors are starting to assess assets based on how adaptable they are to changing workload patterns, not just on occupancy or long-term contracts. Data centres that can support higher power density, fibre routes that connect compute hubs, and sites that can host edge processing all carry different risk and reward profiles than they did five years ago.

This shifts the conversation from “how full is the asset” to “how useful is the asset under new demand conditions.”

A signal, not a blueprint

It would be a mistake to treat SoftBank’s DigitalBridge deal as a template for the wider market. Most operators are not in a position to make large infrastructure acquisitions, nor should they try to.

What the deal does offer is a signal. AI is pushing infrastructure back into the centre of strategic decision-making for both investors and operators. Control, flexibility, and placement are becoming more important than pure scale.

For telecom leaders, the key question is not whether to own more assets, but which parts of the infrastructure stack need closer alignment with AI-driven demand. The answer will vary by market, regulation, and enterprise mix.

What is clear is that the era of treating telecom infrastructure as a slow-moving backdrop is ending. AI is turning it into a variable that can shape cost, performance, and competitiveness in ways operators can no longer ignore.

(Photo by Etienne Martin)

See also: 5G network strategies diverge: Inside AT&T, Verizon, and T-Mobile’s different technology bets

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Tags: ai, cloud, connectivity, data centre, fibre, networks, telecoms