Cohesity Introduces Enterprise AI Resilience Strategy to Secure and Scale AI Adoption
Cohesity, a recognized leader in AI-powered data security, has introduced its Enterprise AI Resilience strategy, a comprehensive framework designed to help organizations adopt and scale artificial intelligence with greater confidence. Through this unified approach, the company aims to strengthen cyber resilience across the entire AI ecosystem while enabling enterprises to innovate without compromising security.
As artificial intelligence adoption accelerates across industries, many organizations face a growing challenge: the pace of innovation is often moving faster than their risk tolerance. While companies continue embedding AI systems into mission-critical operations, they must simultaneously address emerging risks tied to infrastructure, automation, and data governance. Therefore, enterprises increasingly require a security framework that protects AI systems while allowing innovation to move forward.
Cohesity’s Enterprise AI Resilience strategy addresses this challenge by helping organizations strengthen their defensive posture while also unlocking the value of trusted enterprise data. By building resilience across AI infrastructure and data systems, businesses can confidently scale AI-driven initiatives and drive digital transformation.
“By strengthening defense and enabling secure data activation, Cohesity is establishing enterprise AI resilience as the foundation for responsible, high-velocity AI adoption,” said Sanjay Poonen, CEO and President, Cohesity. “Enterprises need the confidence to manage AI-driven risk and recover quickly when disruptions occur. Cohesity provides the resilience foundation that protects AI infrastructure, governs data access, mitigates agent-driven risk, and unlocks the transformative power of trusted enterprise data.”
Strengthening Defense Across the AI Stack
As AI systems transition from experimental projects to full-scale production deployments, enterprises must extend cyber resilience across the entire AI technology stack. In particular, AI agents increasingly interact directly with enterprise applications, infrastructure, and data repositories. As a result, operational dependencies expand, creating new risk surfaces.
To address these risks, Cohesity focuses on three critical areas of defense.
First, organizations must protect the infrastructure that builds and runs AI systems. This includes safeguarding AI agents and their memory, vector databases, model configurations, training datasets, and enterprise data stores. Since these components form a new machine-speed operational layer, businesses require coordinated recovery capabilities when disruptions occur.
Cohesity solves this challenge by preserving immutable snapshots of AI environments and enabling synchronized point-in-time recovery across systems. Consequently, enterprises can restore agents, data, and infrastructure including files, databases, object storage, SaaS applications, vector stores, and agent memory without rebuilding entire systems, significantly reducing downtime.
Second, companies must protect against unintended or malicious AI agent behavior. Because AI systems operate at machine speed, logic errors, corrupted inputs, or prompt injection attacks can quickly trigger large-scale automation failures. Therefore, detection alone is no longer enough. Organizations must also rapidly contain and recover from these incidents.
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To achieve this, Cohesity integrates with leading control and observability platforms such as ServiceNow and Datadog. Through these integrations, the platform converts agent-risk signals into automated, API-driven recovery workflows. As a result, anomalous behavior or policy violations can automatically trigger restoration processes, helping organizations reduce the time required to contain AI-related incidents.
Third, enterprises must govern sensitive data used by AI systems. Since AI tools frequently access data across cloud, SaaS, and hybrid environments, continuous visibility and governance are essential. Cohesity’s Data Security Posture Management (DSPM), powered by Cyera, helps organizations discover and classify sensitive data, monitor access patterns, and enforce governance policies across AI-accessible environments.
Unlocking Trusted Enterprise Data for AI Innovation
While strong defenses are critical, they also enable confident innovation. Organizations store vast volumes of unstructured and time-series data often representing decades of institutional knowledge within the Cohesity Data Cloud. Once secured and governed, this data can serve as a powerful foundation for enterprise AI initiatives.
To support this vision, Cohesity has introduced federated semantic search using the Model Context Protocol (MCP). This capability allows AI-powered enterprise tools, including Glean, to securely access governed backup data without duplicating information or compromising compliance.
“AI agents are only as useful as the information they can securely access,” said Zubin Irani, VP of Partnerships at Glean. “Enterprises have decades of critical knowledge stored across systems, but much of it remains locked away. By enabling federated access to governed data in the Cohesity Data Cloud, we’re helping organizations bring that trusted context into Glean so AI can deliver more accurate answers and actions while maintaining strong security and compliance controls.”
In addition, Cohesity plans to introduce the Cohesity Gaia Catalog, an extension of its Gaia AI platform. This upcoming capability will allow teams to securely access protected data directly from leading analytics platforms such as Databricks and Microsoft Fabric, eliminating the need for duplicate datasets or complex ETL pipelines.
A Unified Platform for Enterprise AI Resilience
All of these capabilities operate within the Cohesity Data Cloud platform. Through this unified architecture, enterprises can protect data across on-premises, cloud, and SaaS environments, safeguard AI infrastructure, govern sensitive data exposure, rapidly recover AI environments, and securely activate trusted enterprise data for AI and analytics.
Ultimately, Cohesity’s Enterprise AI Resilience strategy positions organizations to balance innovation with security. By combining robust defense mechanisms with secure data activation, the company enables enterprises to deploy AI systems confidently while maintaining resilience in an increasingly complex digital landscape.
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