Splunk survey: AI agent observability lags hallucination detection
Original title: AI agent observability is struggling to keep up with hallucinations
Of 2,050 respondents in ten countries, 85% want hallucination detection but only 58% say they can catch it.
Splunk surveyed 2,050 IT and engineering professionals across ten countries on AI agents used in operations. Sixty-two percent frequently rely on agents to diagnose why systems broke, yet more than half cannot measure whether the agents are right. Most call monitoring AI a priority, but 38% have not decided who owns a misbehaving agent, and in 57% of organizations observability now costs more than the infrastructure it monitors.
Unconfirmed: Figures are Splunk's survey results, not independently verified measurements of agent accuracy.
- About a quarter of respondents never let agents write new code.
- Fourteen percent say recovery got slower after agents arrived.
- About half say their observability tools were not built to watch AI.
- Half received a surprise telemetry bill this year.
- Eighty-one percent say AI monitoring pushed closer work with security.
From the original article
2 min read at helpnetsecurity.com
Sixty-two percent of IT and engineering professionals now rely on AI agents frequently to work out why their systems broke, and more than half have no way to measure whether the agents get it right. Splunk surveyed 2,050 of them across ten countries. Source: Splunk Agents diagnose, people still ship the code Teams have been careful about where they let agents work.
By Anamarija Pogorelec · helpnetsecurity.com
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