5 Security Risks Every Business Should Know Before Deploying AI Agents

More than half of organizations have already watched an AI agent do something it was never authorized to do. In the Cloud Security Alliance’s April 2026 study of 445 security and IT professionals, 53% said an agent had exceeded its intended permissions and 47% had suffered a security incident involving an agent in the previous year. Only 16% were highly confident they could detect an agent-specific threat at all.

Those numbers describe agents that are already in production. The decision that matters most happens earlier, when a business chooses which agent to deploy, what it can touch and how it will be tested. This article covers the five risks that decision has to account for: goal hijacking through untrusted content, over-permissioned agent identities, poisoned tools and supply chains, memory and context poisoning and, finally, cascading failures with no human checkpoint. Each one maps to a category in the OWASP Top 10 for Agentic Applications, published December 9, 2025, and each one can be tested for before an agent goes live.

Why AI agents are a different security problem than chatbots

An AI agent differs from a chatbot in one way that changes its whole risk profile: it acts. A chatbot returns text. An agent reads email, queries databases, calls APIs, runs code and hands work to other agents. The model in the middle cannot reliably tell an instruction from its operator apart from an instruction hidden in the data it processes, so every document, web page and tool output the agent touches becomes a possible command channel. A penetration test of the API gateway says nothing about whether a calendar invite can talk the agent into forwarding a customer list.