Announcing Agent Commander - The First Integrated solution from Veeam + Securiti.ai enabling the scaling of safe AI agents

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The AI Trust Gap: Why Scaling Agentic AI Safely Demands a New Security Foundation

In this Whitepaper, you’ll learn about:

  • How agentic AI challenges the enterprise security model
  • Why visibility into agents, data access, permissions, and actions is now critical
  • Why runtime guardrails alone are not enough to secure AI adoption
  • How to benchmark your current posture with the 4-step maturity framework

DOWNLOAD WHITE PAPER

Agentic AI introduces a security challenge enterprises have not faced before: autonomous systems that can access sensitive data, inherit user permissions, interact with tools, and take high-impact actions at machine speed. For security leaders, the challenge is no longer just protecting data from users. It is protecting data from agents acting on behalf of users.

This whitepaper explores the risks security and governance teams must now prepare for, from shadow agents and prompt injection to overpermissioned identities and unintended deletions. Learn how Agent Commander provides the unified control layer needed to secure agentic AI across data, identity, runtime activity, and recovery.

 

Download Whitepaper
The AI Trust Gap: Why Scaling Agentic AI Safely Demands a New Security Foundation

Award-winning technology, built by a proven team, backed by confidence. Learn more.

Frequently Asked Questions (FAQs)

 

The AI trust gap refers to the lack of visibility, control, and governance over autonomous AI agents that can independently access data, execute actions, and interact with enterprise systems.

Unlike traditional AI, agentic systems can act autonomously at machine speed, inherit user permissions, and make decisions without constant human oversight, creating new security and governance risks.

Key risks include shadow AI agents, prompt injection attacks, overpermissioned access, sensitive data exposure, and unintended or destructive automated actions.

Organizations can strengthen governance through unified visibility, least-privilege access controls, continuous monitoring, and centralized policy enforcement across AI systems.

Agent Commander provides a unified control layer for monitoring AI agents, managing permissions, securing runtime activity, and enabling recovery from AI-driven incidents.

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