Why AI agents need Zero Trust infrastructure
The question is no longer whether organizations will deploy AI agents. The question is whether they can trust them.
As more organizations move from AI experimentation to real-world deployment, one thing becomes clear very quickly: building an AI agent is an inevitable part of IT operations. Making that agent useful, scalable, and trustworthy in an enterprise environment is the real challenge.
The moment an AI agent can access data, call APIs, and take action on infrastructure, it becomes part of your operational stack - raising important questions around access control, data governance, resilience, and visibility.
This blog explores what it takes to run AI agents effectively on NetApp, from understanding agents and MCP servers to securely operationalizing agentic workflows. But perhaps the most important lesson is this:
The greatest risk isn't a malicious AI agent. It's a well-intentioned AI agent with too much access. The next generation of breaches may not begin with a hacker breaking in. They may begin with an AI agent faithfully executing a task it was never authorized to perform in the first place.
The lesson from incidents like Pocket OS isn't that AI is dangerous. It's that autonomy without governance is dangerous.
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