Snowflake Bets on AI Data Cloud to Power Enterprise AI Adoption

As more enterprises look to incorporate artificial intelligence into their operations, having a robust data foundation is becoming critical. Snowflake Inc. has rolled out updates to its cloud data platform aimed at supporting these AI initiatives with increased data flexibility, performance and governance controls.

The enhancements, announced at the company’s annual Snowflake Summit in San Francisco, include expanded support for open data architectures like lakehouses and meshes through Apache Iceberg table integration. There are also new features for managing and sharing datasets, AI models and applications within an organization.

“We’re giving customers more ways to leverage their data for AI while maintaining robust governance and security,” said Prasanna Krishnan, Head of Collaboration and Horizon, Snowflake. “The goal is to make enterprise data reserves more accessible and collaborative for AI workloads.”

A key part of the update is general availability of Iceberg Tables, allowing users to query and manage open source Iceberg data sets directly within Snowflake’s environment. Customers like Booking.com are using the integration to implement open, yet governed data architectures.

“We need that flexibility alongside robust governance and performance as we scale AI and analytics use cases,” said Booking.com Chief Data Officer Thomas Davey.

Snowflake has also introduced an Internal Marketplace for securely publishing and discovering datasets, models and applications inside an enterprise. AI model sharing capabilities are expected soon. To aid discovery, Snowflake is previewing AI-generated data descriptions as well.  

For regulated industries, the company launched an EU-only hosted instance to meet data sovereignty requirements, as well as a controlled cloud environment for the U.S. Department of Defense.

In addition to the open data and governance updates, Snowflake says it has improved overall platform performance. According to the company, it has reduced query response times across customer workloads by 27% year-over-year.

As AI adoption grows, enterprises are looking for secure, high-performance data fabrics to fuel these workloads. Snowflake’s enhancements position its cloud platform as one solution for managing and leveraging data for AI initiatives at scale.