One logical question to be asked about the neocloud segment of the artificial intelligence compute value chain is how sustainable the role might become, over time, as some amount of consolidation occurs.
History suggests a new and sustainable role in the AI computing value chain could emerge.
Hardware and platform layers tend to consolidate first, which might suggest to some that neocloud service providers (as infrastructure) could consolidate and eventually be absorbed by hyperscalers.
Middleware and applications repeatedly re-fragment, on the other hand (databases, runtimes, ML frameworks). .
But there also is an argument to be made that intermediation layers survive. As time-sharing bureaus to value-added resellers and managed service providers have emerged as sustainable niches, neoclouds could emerge as a permanent part of the value chain, providing customers (hyperscalers, for example):
Price discovery
Flexibility (financial and operational)
Vendor neutrality.
Hyperscalers dominate integrated platforms, but merchant compute and specialized capacity might be sustainable positions in the value chain.
In every computing era, the dominant platform provider tries to absorb adjacent layers. But a neutral or merchant layer re-emerges when:
Utilization is volatile
Customers resist lock-in
Economics differ by workload
That pattern strongly suggests neocloud is not an anomaly, even if there are business reasons the hyperscalers providing “AI compute as a service” might prefer the role be limited.
For starters, to the extent there are supply constraints for graphics processing units, neoclouds compete for that supply, and reduce hyperscaler leverage over chip vendors.
Neoclouds also can expose:
High gross margins on certain workloads
Cross-subsidies inside hyperscaler pricing
Arbitrage opportunities hyperscalers don’t want visible
For the hyperscalers, non-existence of neoclouds strengthens the “buy from us; there is no alternative” positioning. Without neocloud alternatives, there are fewer opportunities for customers to ask “why is this cheaper elsewhere?”
So there will be some logic for hyperscalers to absorb, starve, or outflank neoclouds.
On the other hand, there are structural reasons an independent neocloud role persists. Hyperscalers are bad at merchant compute, one might argue.
Hyperscalers prefer:
Platform lock-in
Long-lived customer relationships
Bundled services
Predictable utilization.
They are not optimized for, or do not prefer:
Bursty, price-sensitive workloads
Short-term GPU leasing
Single-workload economics
Pricing experimentation.
Even if hyperscalers can do neocloud-style offerings, they often won’t, because doing so:
cannibalizes higher-margin SKUs
disrupts enterprise sales narratives
complicates investor messaging
introduces volatile revenue sources.
On the demand side, customers (including the hyperscalers themselves) want a neutral compute layer that supports multi-cloud capabilities, without a “platform” agenda. Cost and balance sheet advantages (moving capex to opex) also exist.
Neoclouds might also offer faster access to new silicon and more flexible or negotiable terms.
In terms of value chain positioning, the hyperscalers will control:
Developer ecosystems
AI platforms & models.
The value for their customers will include convenience, integration and trust.
The neoclouds, on the other hand, providing a merchant compute layer, will provide capacity arbitrage,
specialized hardware and price-performance leadership. The value is raw compute, predictable economics and speed to deployment.
So there is reason to believe that neoclouds will emerge as a permanent part of the AI compute value chain, supplying:
Merchant GPU capacity
Independent AI compute
Pricing-led infrastructure specialists/
The value chain seemingly always creates a layer where price discovery, specialization, and customer leverage are the values. Neocloud is that layer, some will argue.
And while enterprise compute will be part of the market, much of the current market is driven by compute needs of the hyperscalers themselves.
Some might question the “permanence” of neocloud providers in the “AI compute as a service” space, but current thinking tends to be that a new role within the value chain is being created.
Analysts view NeoClouds as emerging with enduring roles through specialization, partnerships, and niche dominance, rather than widespread buyouts.
Hyperscalers (Microsoft, Google, Amazon, Meta) prefer massive long-term offtake contracts and partnerships to secure capacity quickly, while building their own infrastructure. This hybrid approach allows them to use NeoCloud balance sheets for off-balance-sheet scaling without full integration risks.
Others might argue that the window for neoclouds is somewhat less certain, to the extent it is driven by hyperscale inability to rapidly supply the current demand for AI compute. Eventually, the argument goes, the hyperscalers will be able to build and operate their own internal capacity, reducing reliance on neoclouds.
When scale providers win on unit economics, merchant or brokerage layers appear wherever customers value flexibility, neutrality, or pricing innovation. In the case of AI compute, hyperscale AI compute suppliers, no less than enterprise customers, will have such needs.
Content delivery networks provide a good example of how new specialist roles can emerge. CDNs are specialized data centers whose value is edge location and latency reduction for media and content delivery.
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