Snowflake Signs $6 billion AWS Deal As AI Infrastructure Demand Rises
The five-year agreement expands Snowflake’s use of AWS Graviton processors and AI infrastructure as enterprises move more AI workloads into production.
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Image Credit- Chetan Jha/ MIT Sloan Management Review India
Cloud data firm Snowflake has signed a five-year, $6 billion infrastructure deal with Amazon Web Services (AWS), deepening a long-running cloud partnership as enterprise demand for AI infrastructure rises.
The agreement covers AWS Graviton compute and AI spending, and is intended to help customers build and deploy generative and agentic AI applications on governed enterprise data, Snowflake said on Wednesday.
The deal expands product integrations between Snowflake and AWS, along with joint customer programs, workload migrations and go-to-market efforts through AWS Marketplace. Snowflake said it has surpassed $7 billion in lifetime AWS Marketplace sales.
Snowflake was built on AWS before later expanding support to Microsoft Azure and Google Cloud. The company said most of its customers continue to run on AWS.
“AI has generated enormous excitement, but for enterprises, the real challenge and opportunity is turning intelligence into action,” Snowflake CEO Sridhar Ramaswamy said.
AWS CEO Matt Garman said Snowflake’s expanded use of Graviton would give customers “performance, flexibility, and cost savings” for data warehousing and AI workloads.
The agreement comes as Snowflake pushes further into AI products tied to corporate data. Its Cortex AI platform allows customers to use capabilities such as text-to-SQL, summarization, sentiment analysis and entity extraction within Snowflake’s environment.
Separately, Reuters reported that Snowflake raised its fiscal 2027 product revenue forecast to $5.84 billion from $5.66 billion, citing stronger demand for AI applications and data workload migrations. The company reported first-quarter revenue of $1.39 billion, above analysts’ expectations of $1.32 billion.
The deal also strengthens AWS’s push to place its own chips deeper inside AI infrastructure. In April, Meta agreed to use AWS Graviton5 processors for AI workloads in a multiyear deal.
Nvidia remains the dominant supplier of AI accelerators, but cloud providers are expanding their own chip strategies as companies shift from AI pilots to routine deployment.
CPUs such as Graviton continue to handle large parts of cloud data processing and operational AI workloads, even as GPUs remain central to model training and inference.
