SAN FRANCISCO--(BUSINESS WIRE)--Jun 2, 2026--
SNOWFLAKE SUMMIT 26 –Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced at Snowflake Summit 26 new innovations across Snowflake Horizon Catalog that redefine how enterprises govern, contextualize, and secure AI.
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As organizations move from AI experimentation to autonomous systems operating at enterprise scale, they need AI that operates using trusted business context, while remaining secure, governed, and compliant. Snowflake Horizon Catalog serves as the universal AI catalog for enterprise data. New capabilities like Horizon Context ensure that every person, tool, and AI agent operates from the same trusted business context. Combined with new security innovations that provide purpose-built controls to govern and secure AI agents, Snowflake Horizon Catalog is the connected foundation for trusted AI. Built on the governance, security, and control provided by Horizon Catalog, Adaptive Compute2 automatically optimizes compute and software resources in real-time for customers, delivering fast, efficient AI and app performance at enterprise scale, without manual tuning or infrastructure management.
“When intelligence becomes autonomous, trust is no longer an afterthought, it becomes foundational,” said Christian Kleinerman, EVP of Product, Snowflake. “Organizations need AI that operates from trusted business context with governance and security built in from the start. New advancements across Snowflake Horizon Catalog give every agent, app, and team the trusted context and security controls needed to move AI from experimentation into real-world business operations.”
Create a Shared Understanding of Business Data for AI
As AI agents make more decisions on their own, even small inconsistencies in data can lead to critical mistakes. This is why many AI projects stall between proof of concept and production. Traditional semantic layers are separate from the data itself, which makes it hard to maintain consistent definitions and governance across systems. For example, an AI agent might recommend increasing prices based on revenue data, but if revenue is defined or calculated in different ways across systems, that recommendation can lead to misinformed decisions.
Horizon Context solves this by providing the context layer for AI and BI so data has the same meaning everywhere and AI-driven decisions are reliable. Enterprises like BlackRock are already using Horizon Context to ensure AI operates on a shared definition of enterprise truth. Horizon Context brings this to life by enabling enterprises to:
“In the financial industry, trusted data and consistent business context are critical to delivering accurate insights and managing risk across global markets,” said Jeff Miller, Managing Director, Global Head of Data Factory & Enterprise Data Platforms, BlackRock. “As AI becomes increasingly embedded across our enterprise, it’s essential that applications, analytics, and agents operate from the same trusted understanding of the business. Snowflake’s Horizon Context helps extend consistent business definitions across our broader data ecosystem, supporting more trusted and governed AI and analytics experiences at scale.”
Breaking the Security Barrier to Scalable AI
According to a recent McKinsey study, nearly two-thirds of organizations cite security as the top barrier to scaling AI 5. This is because traditional access controls were built for human users, not AI agents capable of independently accessing systems, reasoning over sensitive data, and taking action across enterprise environments.
Snowflake is introducing new security capabilities that bring zero-trust security to the agentic era and help enterprises like Acxiom, NewDay, and Thomson Reuters strengthen security, visibility, and control as they scale AI. Built within Horizon Catalog, these innovations make Horizon the comprehensive trust layer for enterprise AI, connecting security, governance, observability, and business continuity into a cohesive platform for securing enterprise data, agents, and apps.
To help enterprises securely operationalize AI, these new security innovations deliver:
“As AI becomes increasingly embedded across the marketing industry, having the right security foundations in place is critical to our business scaling innovation responsibly,” said Ankur Jain, Chief Cloud and Data Modernization Officer, Acxiom. “Snowflake’s new AI security capabilities have the potential to provide greater visibility and control over how AI systems access and interact with personally identifiable data, helping us scale AI adoption responsibly while maintaining the trust our clients expect.”
“At Thomson Reuters, responsible AI adoption depends on strong security, visibility, and governance around how AI systems interact with enterprise data,” said Caitlin Halferty, Head of Data & Analytics, Thomson Reuters. “As AI becomes more deeply embedded in professional workflows and customer experiences, protecting sensitive information while enabling innovation is critical. Snowflake’s new AI security capabilities give us greater control and visibility, helping us scale AI with the trust, compliance, and accountability our customers expect.”
Make Enterprise AI Faster and More Efficient
Governance and security are often perceived as barriers to AI innovation that introduce complexity, slow access to data, and create operational friction just as organizations are trying to move faster. At the same time, AI introduces highly dynamic and unpredictable workloads that make managing compute at scale increasingly difficult. Combined with the connected governance, visibility, and control provided by Horizon Catalog, Adaptive Compute removes this complexity by automatically determining the optimal mix of compute and software resources in real time to deliver fast, efficient performance for AI and app workloads without manual tuning or infrastructure management. Together, Horizon Catalog and Adaptive Compute enable organizations to scale AI with a true serverless experience that combines consistent governance and security across data, AI, and compute with the speed, simplicity, and operational efficiency required to accelerate innovation.
Learn More:
1 Snowflake product is now generally available.
2 Snowflake product is generally available soon.
3 Snowflake product is now in public preview.
4 Snowflake product is now in private preview.
5McKinsey & Company, State of AI trust in 2026: Shifting to the agentic era. Based on McKinsey’s 2026 AI Trust Maturity Survey, which gathered responses from approximately 500 organizations globally between December 2025 and January 2026.
About Snowflake
Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 13,900 customers around the globe, including hundreds of the world’s largest companies, use Snowflake’s AI Data Cloud to build, use and share data, applications and AI. With Snowflake, data and AI are transformative for everyone. Learn more at snowflake.com (NYSE: SNOW).
Forward‑Looking Statements
This press release contains express and implied forward-looking statements, including statements regarding (i) our future operating results, targets, or financial position; (ii) our business strategy, plans, opportunities, or priorities; (iii) the release, adoption, and use of our new or enhanced products, services, and technology offerings, including those that are under development or not generally available; (iv) market size and growth, trends, and competitive considerations; (v) our vision, strategy and expected benefits relating to artificial intelligence (AI), the enterprise AI revolution, Snowflake Cortex AI, Snowpark, Snowflake Marketplace, the AI Data Cloud, and AI Data Clouds for specific industries or product categories, including the expected benefits and network effects of the AI Data Cloud; and (vi) the integration, interoperability, and availability of our products, services, and technology offerings with and on third-party products and platforms, including public cloud platforms and AI models. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading “Risk Factors” and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. As a result, you should not rely on any forward-looking statements as predictions of future events.
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Snowflake Advances Trusted AI with Snowflake Horizon Catalog Centralizing Governance, Context, and Security Across the Enterprise
