Author: Kanishka Ajmera, Deborah Mary Sophia, Reuters; Compiled by: Rhythm BlockBeats

The narrative of AI transactions is spreading further from chips and models to the data infrastructure layer.

After experiencing pressure on its stock price since the beginning of the year, Snowflake’s stock price surged more than 33% in a single day as it raised its full-year revenue forecast and reached a $6 billion five-year cooperation agreement with AWS. The core of the market reaction this time is not just that the financial report exceeded expectations, but that investors began to re-evaluate Snowflake’s position in the enterprise AI implementation chain.

In the past year, enterprise software companies have generally faced a question: Will AI become a growth engine, or will it in turn weaken their original business models? Snowflake's latest performance and AWS cooperation give a relatively clear answer - when enterprises begin to deploy AI applications on a large scale, data storage, processing, analysis and model deployment capabilities will become more important.

In this cooperation, AWS Graviton chip supply solves the problem of computing power constraints, while the further integration of the Snowflake platform and AWS AI workloads points to deeper enterprise needs: instead of simply "using AI", enterprises need to integrate their own data into AI workflows and build runnable, manageable, and scalable application systems.

This is why Snowflake is being reinstated into the “AI winner” narrative. AI software stocks have experienced a sell-off before, and the market is full of doubts about whether AI can really contribute to revenue. But Snowflake’s case shows that market sentiment can also quickly reverse once AI moves from concept demonstrations to real revenue growth. At least 30 analysts have raised their target prices, which shows that the capital market is repricing the value of data platforms in the AI ​​infrastructure cycle.

What is more noteworthy is that this transaction also strengthens the presence of AWS’s self-developed chip ecosystem. From Anthropic to OpenAI to Meta to Uber to Snowflake, Amazon is embedding itself deeper into AI infrastructure through cloud, silicon and enterprise software partnerships. For Snowflake, this means that it is not just an enterprise data warehouse company, but is becoming a key data layer in the implementation of enterprise AI applications.

The following is the original text:

Snowflake Inc.'s corporate logo appears on a banner on the New York Stock Exchange (NYSE) to celebrate the company's IPO.

On May 28, Snowflake shares surged more than 33% on Thursday. The company previously raised its full-year revenue forecast while striking a $6 billion partnership deal with Amazon, bolstering investor confidence that it will be one of the main beneficiaries of the AI ​​boom.

The five-year agreement with Amazon Web Services (AWS) will provide Snowflake with a critical supply of AWS Graviton chips. Currently, with the substantial growth in the use of AI, computing resources are becoming increasingly stretched.

The agreement will also further deepen the integration between Snowflake’s data storage, processing and analytics products and AI workloads on the AWS cloud. As enterprises rapidly scale their AI applications, Snowflake is poised to capture even more demand. Currently, most of Snowflake’s customers run on AWS.

At least 30 analysts raised their price targets for Snowflake following the announcement, taking the median price target to $280 from $230 before Wednesday's earnings release. The stock last traded at $233.50 in early trading.

If current gains are maintained, Snowflake's market value will increase by about $20 billion from its original $60.75 billion.

Matt Britzman, senior equity analyst at Hargreaves Lansdown, said the sharp rise in Snowflake shares - which have fallen 20% this year through the close of the last trading day - "illustrate how strong the skepticism has built up in the market as data companies are dragged down by the broader sell-off in AI software."

“But it also shows how quickly market sentiment can turn once a company proves that AI is already driving revenue growth, rather than just decorating PowerPoint presentations.”

Currently, Snowflake trades at 85.21 times forward 12-month earnings, compared with 85.19 times for Datadog and 47.17 times for MongoDB. A higher P/E ratio usually means investors are betting on stronger future growth.

Previously, the market was worried that AI would subvert enterprise software, which put Snowflake under pressure. Today, the company is embedding AI into its platform, helping companies integrate data from multiple sources, conduct analysis, and build AI tools.

“We believe this result puts Snowflake firmly into the ‘AI winner’ camp and deserves a higher valuation multiple,” said Patrick Colville, equity research analyst at Scotiabank. This is a clear indication that Snowflake is benefiting from the growth in enterprise AI adoption, he added.

Snowflake helps businesses store, manage and analyze all their data on one platform. Its AI tools, such as Cortex Code and Snowpark, are seeing strong adoption, allowing enterprises to build generative AI applications and deploy machine learning models based on their own data.

This agreement also casts another vote of confidence in Amazon’s self-developed chip business. In recent months, Amazon has signed up a number of key customers, including Anthropic, OpenAI, Facebook parent Meta and Uber.