Snowflake and AWS: $6B AI chip deal reshapes the cloud

Timeline of a deal that redefines cloud priorities

On May 27, 2026, TechCrunch reported the official news: Snowflake has signed a five-year contract with Amazon Web Services worth six billion dollars. The contract covers CPU chips designed for artificial intelligence workloads. So this is not a simple commercial renewal, but a structural commitment to infrastructure.

Snowflake is one of the most widely used data cloud platforms among enterprise companies worldwide. In recent years, the company has invested heavily in native AI capabilities, building language models and machine learning pipelines right into its data analysis environment. As a result, reliance on high-performance, scalable hardware has become a top priority in its business plan.

The agreement with AWS strengthens an existing relationship and takes it to an unprecedented depth. In particular, betting on CPU chips, and not only on Nvidia GPUs, is a deliberate architectural choice. It also reflects a broader trend that we at SHM Studio are watching closely in the global cloud market.

Nvidia on notice: the context of the hardware challenge

Nvidia has dominated the AI chip market thanks to its GPUs, which became the de facto standard for training and inference of complex models. However, that position is no longer unchallenged. Over the past eighteen months, Amazon has accelerated the development of its own proprietary chips: Trainium for training and Inferentia for inference.

The deal with Snowflake strengthens the AWS Graviton ecosystem and Amazon's family of custom chips. As a result, Nvidia faces competition that comes not only from AMD or Intel, but from its own largest customers. This phenomenon, known as the vertical integration of AI hardware, has already been analyzed by Gartner as one of the structural trends of the decade.

Contrary to what you might think, Nvidia is not at risk of an immediate collapse. Global demand for GPUs remains extremely high. Still, every major deal like the Snowflake-AWS one erodes potential market share and reduces systemic dependence on the California-based supplier. So in the short term, the signal is more strategic than operational.

Winners and losers: a multi-layered reading

The first clear winner is Amazon. The six-billion-dollar deal brings guaranteed revenue for five years and cements AWS as the preferred platform for the AI workloads of one of the leading data cloud players. It also validates Amazon's in-house hardware roadmap in the eyes of the enterprise market.

Snowflake, in turn, gets priority access to computing capacity at a time when the scarcity of AI chips is still a critical variable. The deal lowers operational risk and lets the company plan the expansion of its AI features with greater certainty. According to Harvard Business Review, multi-year contracts of this kind offer a measurable competitive advantage in time-to-market for AI features.

The most direct losers are alternative cloud infrastructure providers that lack a comparable vertical chain. In particular, those that control neither the silicon nor the orchestration software struggle to compete on pricing and performance. Likewise, resellers of Nvidia hardware serving the enterprise segment could see their pipeline shrink in the coming years.

SHM Studio's take: what's moving beneath the surface

Deals like this rarely concern only the two companies that sign them. They reshape expectations across the whole ecosystem. Italian SMEs building their digital strategy on cloud platforms should keep in mind that the infrastructure choices of the big vendors trickle down, with a six-to-twelve-month delay, into the costs and features available at the lower tiers of the market.

In particular, those who use Snowflake for analytics or data warehousing will indirectly benefit from greater availability of AI capacity at potentially lower costs. As a result, features like Snowflake's Cortex AI, which lets you query data in natural language, could become faster and more accessible. This has direct implications for the applied artificial intelligence initiatives that companies are building into their processes.

On top of that, the consolidation of the AWS-Snowflake axis raises a strategic question for SMEs: is it better to diversify across several cloud providers or to go deeper with a vertically integrated ecosystem? There is no one-size-fits-all answer. However, the direction of the market suggests that depth of integration tends to reward those who choose deliberately.

Implications for cloud-first SMEs: three areas to watch

Italian businesses operating in cloud-first environments should monitor three specific areas over the coming quarters.

• AI workload pricing: the availability of proprietary AWS chips could lower inference costs for those running models on Amazon infrastructure. It is worth re-evaluating your existing architectures with your technology partner.
• Data platform roadmaps: Snowflake will accelerate the development of native AI features. If you already use the platform, check which new capabilities will become available over the next twelve months.
• Single-vendor dependence: exclusive deals on this scale increase vendor lock-in. It makes sense to consider data portability strategies and contracts with appropriate exit clauses.

To dig deeper into these topics from a digital strategy and competitive positioning perspective, it is also worth reading the analyses by McKinsey Digital on the infrastructure transformations underway in the enterprise sector.

The Work Still Ahead: What Remains Unresolved

The Snowflake-AWS deal is public in its general financial terms, but many technical details remain confidential. For example, it is not yet clear which specific mix of Trainium, Inferentia and Graviton chips will be used in different application scenarios. It is also unknown whether the deal includes exclusivity or simply a minimum spend commitment.

These details matter. The difference between an exclusivity agreement and a multi-year committed spend has very different implications for market competition. In the first case, Snowflake ties itself fully to AWS for AI chips. In the second, it keeps the flexibility to integrate hardware from other suppliers.

Finally, the question of how Google Cloud and Microsoft Azure will respond remains open. Both providers are developing proprietary chips, TPU and Maia respectively, and may seek similar deals with other major data cloud players. The AI cloud chip market is therefore set to become even more fragmented and competitive over the next twenty-four months.

Next moves: navigating the AI cloud ecosystem in 2026

For Italian SMEs, the takeaway is clear. First, map precisely which parts of your digital infrastructure depend on vendors exposed to these dynamics. Then, assess whether your current technology choices still line up with where the market is heading.

SEO, Google Ads campaigns and LinkedIn campaigns that rely on AI tools for automatic optimization depend indirectly on the quality of the underlying cloud infrastructure. So understanding where hardware value is concentrating also means understanding where the quality of digital marketing tools will concentrate in the years ahead.

If you run a company website or an e-commerce store on cloud architectures, you should consider reviewing your technology dependencies on a regular basis. Web development and SEO copywriting services are increasingly integrated with AI tools that run on infrastructure like AWS. As a result, the quality of the final output is tied, in part, to the infrastructure choices of the big vendors.

Want to talk through what these dynamics mean strategically for your company? The SHM Studio team is available for a consultation. You can also follow the SHM Studio blog, where we regularly publish analysis on these topics to support Italian SMEs in making decisions in today's digital landscape.