Survey Finds Most Organizations Lack Visibility Into AI Agent Activity

A survey released in 2026 reported that 88 percent of organizations experienced security incidents involving AI agents during the previous 12 months. The same poll found that only 21 percent of respondents maintained runtime visibility into what those agents were doing.

The findings come as enterprises shift from testing AI assistants to deploying agents that reason, plan, and act with limited human oversight. These systems now read support inboxes, reconcile records, file tickets, and execute transactions at machine speed and around the clock.

Security teams need three capabilities to monitor agent activity. They must reconstruct the full path from an agent's prompt through its reasoning and tool calls to any real-world effects. They also require correlation across multiple agents rather than isolated logs, because malicious patterns often appear only when traces from several agents are combined.

Detection must operate at runtime and at machine speed, since pre-deployment testing cannot account for behavior changes that occur once agents are live.

Existing identity systems establish who an agent is and what resources it may reach. They do not show whether an authenticated agent performed an action that was intended or whether its intent was altered. The survey indicates that most breaches are expected to involve legitimate, correctly scoped agents that read the wrong data or follow hijacked instructions.

Without a behavior-monitoring layer, those actions remain invisible to security teams.