Skip to content
NewA calmer, faster ZeroHour

Survey: security teams plan most monitoring investment for AI agents

Original title: Security teams want to spot unusual AI agent behavior while they’re still defining normal

Help Net Securityby Anamarija Pogorelec ()3 min read1 · 1 read
AI summary · x-ai/grok-4.7Summaries by Vani AI

Nearly half of respondents said their organizations cannot effectively baseline normal AI agent behavior.

Abnormal AI’s 2026 State of Behavioral Security Report says AI agents were the top planned behavioral-monitoring investment. Respondents were split on whether they can maintain baselines for agent activity. Coverage was higher for user sign-ins than for agents, APIs and service accounts, and just over half of anomaly investigations take at least four hours.

Unconfirmed: Figures come from Abnormal AI’s survey and are not independently verified.

Key facts
  • 43% chose AI agents, more than three times the share for API integrations.
  • More than 81% rely on behavioral anomaly detection to a major or extensive degree.
  • About 72% said they detect unusual non-human identity behavior better than human behavior.
  • 76.2% baseline user sign-ins; agent, API and service-account coverage is about half.
  • False positives and difficulty defining normal activity were the most cited obstacles.
Analyze this story with Vani AIImpact, who is affected and what defenders should do, in a new chat

From the original article

3 min read at helpnetsecurity.com

AI agents topped the list of planned investments in behavioral monitoring in Abnormal AI’s 2026 State of Behavioral Security Report. Asked where their organizations would invest most over the next two years, 43% of respondents chose AI agents, more than three times the share who chose API integrations, the next most common answer.

Help Net Security

By Anamarija Pogorelec · helpnetsecurity.com

Read the full article at Help Net Security

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.