With generative artificial intelligence (GenAI) “at the forefront of customer conversations,” Snowflake CEO Frank Slootman recently revealed that 9 of Snowflake’s top 10 customers boosted spending last quarter in what he said reflects a “broadly stabilizing macro environment.”
That confident outlook was shared by the other two Cloud Wars Top 10 companies whose fiscal Q3 ended Oct. 31: Workday and Salesforce. The recent upbeat results from those three, combined with very strong results from Microsoft, SAP, and ServiceNow for the quarter ended Sept. 30, offer compelling evidence that customers are spending more aggressively as they look to take part in the remarkable GenAI Revolution sweeping the business world.
In his opening remarks during Snowflake’s fiscal-Q3 earnings call late last month, Slootman tightly coupled the company’s strong results — product revenue up 34% to $699 million — to the growing realization among business executives that successful GenAI strategies must be centered on data.
“Our results reflect strong execution in a broadly stabilizing macro environment. While Snowflake’s global revenue mix is highly diverse in terms of industries and geographies, the company is deriving an ever-larger revenue share from mainstream enterprises and institutions, as compared to a newer crowd of digital natives that have made up many of Snowflake’s early adopters,” he said.
“Generative AI is at the forefront of customer conversations, which in turn drives renewed emphasis on data strategy in preparation of these new technologies. We’ve said it many times: there’s no AI strategy without a data strategy. The intelligence we’re all aiming for resides in the data — hence the quality of that underpinning is critical.”
In this analysis, I want to focus on one vital factor that not only drove Snowflake’s strong Q3 but also Slootman’s confidence in the company’s future: The new ability to bring unstructured data into the AI fold. While every Cloud Wars Top 10 company is eager to harness the power of unstructured data, Slootman offered a couple of numbers indicating that Snowflake is building some serious momentum.
Consumption of unstructured data in Q3 was up 17X year over year, Slootman said, adding that in the month of October, almost one-third of its customers were using Snowflake to process unstructured data.
One of the approaches Snowflake is taking to help customers leverage the vast potential of unstructured data is a new service called Document AI.
“It’s just going into preview, and is incredibly popular out there,” he said on the earnings call.
“Document AI turns an unstructured document into a semi-structured document so it can become a full participant in analytical processing,” Slootman said.
“There’s a ton of interest in that. And that really brings the entire estate of unstructured data, which is 80% of the world’s data, into the analytical sphere.”
Since AI and large language models are so heavily focused on unstructured data — particularly textual data — “this will be a driver in our business,” Slootman said.
The key is new technology that makes unstructured data referenceable in analytical workloads —and Snowflake has developed that capability, which turns something that Slootman said was “borderline unusable for analytical purposes” into a vital and vibrant raw material in the burgeoning world of GenAI.
“It’s ironic that both through the onslaught of large language models [LLMs] that are extraordinarily capable of dealing with textual data, as well as things such as Document AI that Snowflake has developed and is bringing to market, that this [unstructured] data is going to become a full participant in these types of workloads,” he said.
“It’s super exciting because it’s going to really enrich and really unlock insights and outcomes and all of that that we haven’t had before. So, this is going to be a driver of our world in terms of this type of computing.”
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