As part of its annual Snowflake Summit, the AI data cloud company, has announced a host of new artificial intelligence (AI), governance, and data interoperability innovations. The new announcements aim to help companies speed up their transition to what it describes as an ‘agentic enterprise’, which is essentially a business environment where AI agents can autonomously perform tasks, make decisions, and take action backed by trusted enterprise data.
The announcements were made at Snowflake Summit 2026, in San Francisco, where the company highlighted updates across AI development tools, enterprise intelligence platforms, governance frameworks and open data ecosystems. According to the company, the latest innovations are aimed at providing enterprises with a unified control plane that connects data, business context, governance, and AI-powered action in a single platform. “As enterprises move from AI experimentation to autonomous systems operating at scale, they need a platform that connects data, business context, governance and action across the organisation,” the company said.
Meanwhile, Vijayant Rai, managing director for India at Snowflake, said the future of enterprise AI will depend on how effectively organisations connect intelligence, trusted data and business processes. “The future of enterprise AI will be defined by how well organisations connect intelligence, trusted data and action across the business,” Rai said. “These innovations help provide a trusted foundation for building AI faster, operationalising it securely at scale and enabling teams and AI agents to work together from a shared business context.”
New capabilities for AI development
Perhaps one of the major highlights of this year’s summit was the expansion of Snowflake CoCo, earlier known as Cortex Code. CoCo functions as an AI-powered coding agent that has been designed to help developers automate workflows, build applications and operationalise AI systems through interactions in natural language.
At the summit, the company said that CoCo can now function across multiple environments, including desktop, mobile applications, Slack, Visual Studio Code, Claude Code, Microsoft Excel, etc. According to the company, the goal is to enable developers and business users to access AI-assisted development tools from the software they are already using.
On the other hand, the company also introduced Snowflake Datastream, which is a fully managed streaming service for Apache Kafka. Snowflake said that Datastream has been designed to offer real-time data flows directly within Snowflake, allowing companies to build AI apps and agents that operate on continuously updated information.
According to the company, when combined, CoCo and Datastream can simplify how companies build and operationalise real-time AI. This is possible as they can combine AI-assisted development with governed, real-time data in a single platform.
For enterprise knowledge workers
At the summit, the company also announced some new capabilities for Snowflake CoWork, formerly known as Snowflake Intelligence. The company said that the platform serves as a personal AI agent for knowledge workers, assisting employees in accessing information, generating insights and taking actions based on enterprise data. The new features for CoWork include Cortex Sense, Artifacts, Deep Research, User Skills and personalisation capabilities. A combination of these tools are intended to create a context-aware AI experience that can understand enterprise data and support workflows.
According to the California-headquartered company, CoWork is designed to move beyond traditional question-and-answer interactions and offer more proactive and personalised intelligence. The company said that the platform can help automate routine tasks, accelerate decision-making and make AI more useful across various business functions. The company also introduced Cortex Training, a managed service that lets companies customise and train foundation models directly within the Snowflake environment, eliminating the need to move enterprise data to external AI training platforms.
Governance and security enhancements
In order to redefine how enterprises govern, contextualise, and secure AI at scale, Snowflake announced new innovations across the Snowflake Horizon Catalogue. The new additions include Horizon Context that ensures every person, tool, and AI agent operates from the same trusted source at the same time. AI security innovations bring purpose-built control for governing and securing enterprise AI systems. According to Snowflake, this shared context is critical for maintaining trust and consistency as AI adoption grows.
Other features include agent identity that allows companies to manage and monitor AI agents and enhancements to Snowflake Trust Centre that help in improving visibility, governance, and security controls for AI systems. Additionally, Adaptive Compute capability automatically optimises compute and software resources in real time to offer fast and efficient AI and application performance at enterprise scale without the need for manual infrastructure management.
On data interoperability
Another key focus area at the summit was interoperability. For the uninitiated, interoperability simply means the ability of different systems, devices, or applications to communicate, exchange data, and use that information accurately. Snowflake introduced new capabilities that enable organisations to access, govern and share data across Snowflake environments, external data lakes and open systems without moving or duplicating datasets. The company also announced support for Apache Iceberg v3, Snowflake Storage for Apache Iceberg Tables, external engine access management, and support for the Iceberg REST Scan Plan API.
Powered by Snowflake Horizon Catalogue and Apache Polaris, these capabilities are aimed at allowing organisations to work from a single governed copy of enterprise data across different clouds, analytics tools and enterprise systems. The company also unveiled Automatic Data Agents and Agent Sharing, which can transform shared datasets into conversational AI agents while maintaining governance controls. Combined with CoCo and CoWork, these capabilities can let users interact with enterprise data using natural language while maintaining security and compliance requirements.
The announcements reflect Snowflake’s broader strategy of helping organisations move from AI experimentation toward deploying AI agents and autonomous systems at enterprise scale on a governed and interoperable data foundation.
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