Our Take
Gartner is forecasting market share, not measuring it—this is a prediction, not evidence that neocloud providers are winning today.
Why it matters
Cloud market share forecasts shape vendor strategy and customer procurement timelines. If the prediction holds, it signals structural shifts in how enterprises buy AI infrastructure over the next half-decade.
Do this week
Infrastructure teams: audit your cloud lock-in terms (multi-year discounts, custom hardware requirements) against your actual AI workload roadmap—renewal windows are the moment to renegotiate.
Gartner's 2030 neocloud prediction
Gartner predicts that neocloud providers (company-defined category, not independently verified) will account for 20% of a $267 billion AI cloud market by 2030 (per Gartner's forecast). The analyst firm does not specify which vendors qualify as neocloud or provide the methodology underlying the $267 billion market size estimate or the 20% share projection.
The forecast implies the AI cloud market will grow substantially from its current size. Gartner does not disclose the baseline figure for 2024 or the compound annual growth rate assumed in the model.
What Gartner's framing reveals about cloud competition
The introduction of "neocloud" as a distinct category signals that Gartner expects the market structure to shift away from dominance by the three hyperscalers (AWS, Azure, Google Cloud). This framing matters because enterprise procurement teams use analyst reports to justify vendor diversification and because it influences which vendors receive venture funding and board attention.
However, category definitions matter more than percentages. Gartner does not publish which vendors it counts as neocloud in this model. Without clarity on the roster (Does CoreWeave count? Lambda Labs? Crusoe? All three?), the 20% figure is opaque to practitioners deciding where to build.
The $267 billion market size itself is a projection, not a market today. Gartner's estimates for AI infrastructure spending vary widely across analyst firms and depend heavily on how "AI cloud" is bounded (Does this include GPU resale? Inference-only? Multimodal workloads?). No independent source validates the numerator.
How to read this forecast
Treat this as a directional signal, not a prediction with reliability bounds. Gartner's historical accuracy on market share forecasts three to six years out is uneven, especially in nascent categories where vendor consolidation or exit can reshape the landscape.
For infrastructure teams: the forecast is useful as permission to test neocloud providers (CoreWeave, Lambda, others) in non-critical workloads today. Diversification from hyperscalers has value independent of whether neocloud hits 20% by 2030. Lower switching costs, price competition on GPUs, and custom hardware optimization are happening now and do not depend on Gartner's prediction coming true.
For vendors selling into this space: the forecast is ammunition for sales conversations but does not substitute for evidence that your platform reduces latency, cost, or time-to-deployment relative to AWS SageMaker or Azure AI. Gartner's prediction creates no customers; product-market fit does.