Cohesity Launches Enterprise AI Resilience Strategy to Power and Protect AI Initiatives

SANTA CLARA, Calif. — March 10, 2026 — Cohesity, the leader in AI data security, today unveiled its Enterprise AI Resilience strategy. This unified approach enables organizations to confidently adopt and scale AI by strengthening cyber resilience across the AI ecosystem. 

AI adoption is accelerating, but for many enterprises, the pace of innovation is outstripping risk tolerance. As AI systems become embedded in core operations, organizations must manage new infrastructure and automation risks without slowing business transformation. 

Cohesity’s Enterprise AI Resilience strategy enables enterprises to play strong defense, protecting AI systems and mitigating agent-driven disruption, so they can confidently go on the offense and harness AI to drive growth. 

“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.” 

Defense: Protecting AI Infrastructure, Governing Data, and Mitigating Agent Risk 

As AI systems move from experimentation into production, enterprises must extend cyber resilience across the full AI stack. AI agents increasingly interact directly with enterprise systems and data, expanding operational dependencies and introducing new risk surfaces. 

Cohesity addresses three critical dimensions of defense: 

Protecting AI and Agent Infrastructure 

Enterprises must safeguard the infrastructure that builds and runs AI systems, including: 

• AI agents and agent memory 
• Vector databases 
• Model configurations and policies 
• Training and fine-tuning datasets 
• Enterprise data stores 

These components introduce a new stateful, machine-speed operational tier that requires coordinated, signal-driven recovery. 

Cohesity preserves immutable snapshots of AI environments and enables synchronized, point-in-time recovery of agents, data, and supporting infrastructure, including files, databases, object storage, SaaS applications, vector stores, and agent memory, reducing downtime without full system rebuilds. 

Protecting Against Rogue, Unintended, or Malicious Agent Actions 

AI systems operate at machine speed. Logic errors, corrupted inputs, prompt injection, or malicious manipulation can trigger cascading automation mistakes in seconds.

Detection alone is insufficient. Organizations must contain and rapidly recover from unintended or malicious agent-driven activity.  

Because AI agents operate across a broad enterprise ecosystem—spanning IT service management, observability, data platforms, and automation systems—effective remediation requires coordinated action across those environments. Through deep integrations with leading control and observability platforms, including ServiceNow and Datadog, Cohesity translates agent risk signals into automated, API-driven recovery workflows

Anomalous behavior or policy violations can automatically trigger API-driven, point-in-time restoration—reducing mean time to containment in AI-driven incidents. 

Governing Sensitive Data for AI 

Continuous visibility and governance are essential as AI systems access sensitive enterprise data across cloud, SaaS, and hybrid environments.  

Cohesity Data Security Posture Management (DSPM), powered by Cyera, discovers and classifies sensitive data, monitors access patterns, and supports governance controls across AI-accessible environments. Combined with Cohesity’s recovery capabilities, organizations can detect exposure or misuse and restore affected data and AI systems to trusted states. 

Offense: Activating Trusted Enterprise Data for AI 

Strong defense drives confident innovation. 

Enterprises store vast amounts of unstructured and time-series data—often representing decades of institutional knowledge — within the Cohesity Data Cloud. Once protected and governed, this data can securely power AI initiatives. 

Cohesity has announced federated semantic search via the Model Context Protocol (MCP), enabling AI-powered enterprise tools, including Glean, to securely access governed backup data without duplicating it 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, the upcoming Cohesity Gaia Catalog extends the Cohesity Gaia AI platform, so teams can securely access protected data directly from leading analytics platforms such as Databricks and Microsoft Fabric, without duplicating data or rebuilding ETL (extract, transform, load) pipelines. 

By activating protected data directly from the Cohesity Data Cloud, organizations can improve data freshness, governance, and compliance, while empowering AI systems with trusted enterprise context. 

A Unified Platform for Enterprise AI Resilience 

All capabilities are delivered through the Cohesity Data Cloud, enabling organizations to: 

• Protect data across on-premises, cloud, and SaaS environments 
• Safeguard AI and agent infrastructure 
• Govern sensitive data exposure across AI environments 
• Rapidly recover AI environments and data to trusted states 
• Activate governed enterprise data securely for AI and analytics