Neocloud providers target 20% of AI cloud market by 2030

The term "neocloud" may sound like analyst shorthand, but the category is gaining traction as enterprises seek alternatives to hyperscale infrastructure for AI workloads. These providers focus on high-performance and AI-specific computing rather than general-purpose cloud services, addressing gaps in GPU availability, deployment friction, and regulatory compliance that hyperscalers have struggled to fill at scale.

Gartner’s latest forecast suggests this segment could account for 20% of a $267 billion AI cloud market by 2030, a share larger than many CIOs anticipated entering 2026. The projection underscores how quickly procurement priorities are shifting, with enterprises increasingly willing to diversify infrastructure spend beyond traditional hyperscale providers.

Market dynamics

Neocloud providers are positioning themselves as solutions to three persistent pain points: GPU scarcity, deployment complexity, and data sovereignty. Hyperscalers have faced criticism for opaque pricing, long lead times for high-end accelerators, and limited flexibility in tailoring infrastructure to AI workloads. In contrast, neocloud vendors are designing platforms around AI from the ground up, often with clearer pricing models and faster access to cutting-edge hardware like NVIDIA’s Blackwell GPUs.

The trend is particularly pronounced in Europe, where regulatory uncertainty around data transfers and AI governance has pushed organizations toward providers offering localized infrastructure. Irish startup TensorX, for example, recently committed €8 million to secure NVIDIA Blackwell GPUs, including B300 processors, to build an inference platform for enterprises unwilling to move sensitive workloads outside European jurisdiction. The move reflects broader demand for AI infrastructure that aligns with regional compliance requirements, a niche hyperscalers have been slower to address.

Competitive pressures

The rise of neoclouds is forcing hyperscalers to adapt. While providers like AWS, Google Cloud, and Microsoft Azure still dominate the broader cloud market, their share of AI-specific workloads is under pressure. Neocloud vendors are not only competing on hardware but also on service models, offering more transparent pricing, faster deployment cycles, and specialized support for AI workloads. Some are even partnering directly with chipmakers to secure supply, as seen in Micron’s strategic agreement with Anthropic, which ties memory architecture planning to AI infrastructure demand.

For enterprises, the shift presents both opportunities and challenges. On one hand, neoclouds offer a way to bypass hyperscaler bottlenecks, particularly for GPU-intensive workloads. On the other, the fragmentation of the market could complicate procurement, as organizations weigh the benefits of specialized providers against the convenience of consolidated hyperscale services. The decision may hinge on factors like workload specificity, regulatory constraints, and long-term cost structures.

What to watch

The next 12 months will be critical in determining whether neoclouds can sustain their momentum. Key indicators include:

• Hardware access: How quickly neocloud providers can secure and deploy next-generation GPUs, particularly as demand for NVIDIA’s Blackwell and GB300 series grows.
• Regulatory clarity: Whether European and other regional regulators provide clearer guidelines on AI governance, which could either accelerate or slow adoption of sovereign-focused neoclouds.
• Hyperscaler responses: How AWS, Google Cloud, and Microsoft adapt their AI infrastructure offerings to compete on flexibility, pricing, and compliance.
• Enterprise adoption: Whether large organizations begin shifting significant portions of their AI workloads to neoclouds or continue to rely on hyperscalers for the bulk of their infrastructure needs.

The outcome will shape not only the competitive landscape but also the pace of AI adoption across industries, as enterprises weigh the trade-offs between specialization and consolidation in their infrastructure strategies.