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Enterprise AI agent controls lag deployment
A June survey of 573 technical leaders reveals that many enterprises are deploying AI agents without sufficient control systems in place. Over half of the surveyed companies experienced an AI agent security incident in the past year, underscoring the risks associated with their rapid deployment. The survey indicates a significant 86% of enterprises report their GPU utilization is low, hinting at inefficiencies in resource management. Many companies are now budgeting to implement essential control layers—identity, evaluation, cost telemetry, context, and orchestration—within the upcoming year, reflecting an urgent need to enhance management of AI outputs and expenditures.
MonitorConfidence: HighShort term horizonCybersecurity risk: High
Published 10 Jul 2026, 20:26 UTC9 min read
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Summary
TL;DR
- 86% of enterprises report GPU utilization at 50% or less
- 54% experienced a security incident or near-miss in the past year
- 71% say few of their AI agents can complete multi-step tasks independently
- Most companies are planning to enhance AI control layers over the next year
- Only 44% track AI computing costs rigorously
Interesting facts
- A significant number of AI agents are misrepresented as capable agents when they are merely simple chatbots.
- Gartner forecasts rapid integration of task-specific AI agents in enterprise applications by 2026.
- Only 5% of enterprises fully trust automated evaluations for deploying AI changes.