Cohesity Launches Agent Resilience for AI Agent Recovery

Data security and management provider Cohesity has introduced Agent Resilience, a new capability designed to protect and recover the infrastructure that underpins AI agents. The offering targets a gap that has emerged as enterprises move from experimenting with generative AI to deploying autonomous agents inside live business processes: most organizations have backup and recovery plans for traditional applications and data, but far fewer have equivalent protection for the systems running AI agents themselves.

According to the announcement, Agent Resilience is built to safeguard agent infrastructure — the configurations, data connections and operational state that let an AI agent function — so that it can be restored quickly if it is disrupted, corrupted or compromised. The move extends Cohesity's existing data protection portfolio into the emerging category of "agentic AI" infrastructure rather than introducing a standalone AI model or assistant.

As AI agents take on more operational responsibility — routing customer requests, executing transactions, orchestrating workflows — their failure or compromise stops being a minor IT incident and becomes a service disruption with direct downstream impact on customers and employees. Enterprises have spent the past two years focused on getting agents to work; far less attention has gone to what happens when they stop working, or work incorrectly.

For digital transformation and technology leaders, this signals that resilience and recovery are becoming a required layer of agentic AI architecture, not an optional add-on. Any organization embedding autonomous agents into customer-facing or operational processes needs a credible answer to "what happens if this agent breaks, drifts, or is exploited" — and Cohesity's move suggests the vendor ecosystem is starting to build that answer into infrastructure rather than leaving it to individual AI teams.

Agentic AI has been sold almost entirely on capability — what agents can now do. Resilience is the less glamorous, more important half of that story, and it's arriving late.

Most leaders evaluating AI agents ask "how smart is it?" before they ask "how do we recover it when it fails?" — and in service design, that ordering always backfires. An agent that mishandles a customer interaction because its underlying state was corrupted, with no fast recovery path, does more brand damage than the efficiency gains it delivered ever offset. The organizations that get this right will treat agent resilience the way they treat payment system uptime: invisible when it works, catastrophic when it's missing. Build the recovery plan before the agent goes live, not after the first outage.