UPDATED 11:24 EDT / JUNE 08 2026

Nancy Wang, CTO of 1Password, and Artin Avanes, head of core data platform at Snowflake, talk with theCUBE about AI agent security at Snowflake Summit 2026. AI

Snowflake and 1Password tackle the growing challenge of securing AI agents at scale

As AI agents gain access to sensitive enterprise data, AI agent security is becoming a top priority for organizations. The challenge is no longer just protecting systems, but ensuring autonomous agents can be trusted, governed and controlled at scale.

For the past two decades, enterprise security has focused primarily on protecting applications and infrastructure. Today, the conversation is shifting toward governing the people and AI agents that access sensitive systems and data, according to Nancy Wang (pictured, left), chief technology officer at AgileBits Inc., doing business as 1Password.

“The conversation has really changed from ‘How do we secure systems?’ to now ‘How do we govern actors?’” she said. “Agents really throw that conversation and make it truly multidimensional.”

Wang and Artin Avanes (right), senior director of product management at Snowflake Inc., spoke with theCUBE’s Dave Vellante and Rebecca Knight at Snowflake Summit 2026, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed AI agent security and the convergence of identity and data security. (* Disclosure below.)

AI agent security at scale

With AI agents increasingly accessing enterprise data, organizations must manage a vastly larger, more dynamic set of actors than ever before. That task requires greater visibility into what agents exist and stronger governance and security controls to ensure they access data appropriately, according to Avanes.

“There is no world where you can just put an agent out or run your agentic tool directly against your data without those controls,” he said. “It would destroy your business in many ways.”

As enterprises scale AI agents, accuracy and trustworthiness have become critical requirements, driving demand for a shared understanding of data through semantic layers. Snowflake’s Horizon Context capabilities are intended to tap into metadata that sits outside of Snowflake to power agentic workflows and processes much more accurately moving forward, according to Avanes and Wang.

“It’s really a case where identity security now meets data security,” Wang noted. “You have to preserve that intent across each layer of the stack.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Snowflake Summit 2026:

(* Disclosure: TheCUBE is a paid media partner for Snowflake Summit event. Neither Snowflake, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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