An enormous portion of revenue for cloud providers and other AI infrastructure players comes from just OpenAI and Anthropic. This extreme customer concentration creates a fragile system where the failure of one or two key players could trigger a widespread collapse.

Despite massive compute demand from frontier AI labs willing to buy out all supply, AWS intentionally reserves GPU and accelerator capacity for early-stage startups. Matt Garman estimates that 30% to 40% of AWS's current revenue comes from companies that began as startups on AWS. Sacrificing short-term lab revenue ensures a healthy ecosystem and guarantees access to the next generation of enterprise customers.

NVIDIA doesn't simply sell its scarce chips to the highest bidder. It strategically allocates them to cultivate a diverse ecosystem of cloud providers and customers. This prevents any single customer from becoming too powerful and ensures healthy competition among its buyers, which ultimately drives more demand for NVIDIA's hardware.

Once a haven for startups struggling to get GPUs, NeoClouds like CoreWeave have shifted their strategy. They now prioritize serving the largest customers, mirroring the behavior of AWS and Azure and leaving startups with fewer alternative compute options than in 2023.

Cloud providers like Amazon and Google benefit regardless of which AI model wins. By structuring deals as large-scale compute commitments in exchange for equity (e.g., with Anthropic), they profit from cloud usage fees, drive adoption of their in-house silicon, and gain visibility into data center capex recovery, effectively hedging their bets across the entire AI ecosystem.

For leading AI labs like Anthropic and OpenAI, the primary value from cloud partnerships isn't a sales channel but guaranteed access to scarce compute and GPUs. This turns negotiations into a complex, symbiotic bundle covering hardware access, cloud credits, and revenue sharing, where hardware is the most critical component.

Despite predictions of commoditization, the AI inference layer remains competitive. The market is supply-constrained, and GPU makers like NVIDIA intentionally avoid customer concentration with hyperscalers, creating space for specialized, innovative providers to thrive.

Jensen Huang strategically allocates GPUs to NeoClouds and new AI labs to prevent a world dominated by a few hyperscalers building their own custom chips (like TPUs). This ensures a diverse customer base and prevents NVIDIA's core products from being commoditized by a handful of powerful buyers.

While the market may currently reward high revenue concentration (e.g., NVIDIA's reliance on a few customers), operators should view it as a significant risk. ClickHouse's CEO actively manages exposure, ensuring no single customer or industry exceeds 10% of total revenue to maintain durable growth.