50% of enterprises have at least partially documented governance policies for AI agent usage.

29% of enterprises report transitions between teams or tools as a meaningful source of workflow delay.

39% of enterprises identify investigation and analysis as a top bottleneck in workflows.

29% of enterprises prioritize risk management, 28% prioritize monitoring, and 19% prioritize permission control for AI agents.

30% of enterprises name AI governance and risk management as their top AI security challenge.

Only 9% of enterprises report no significant workflow delays.

91% of enterprises experience workflow bottlenecks despite deploying AI and automation.

39% of organizations say their unstructured data is somewhat or fully prepared for AI use.

89% of enterprises are confident in their ability to secure AI-generated code.

86% of enterprises are using AI-generated code in production.

39% of enterprises identify over-trust in AI-generated outputs as a leading anticipated risk.

21% of managers at enterprises report being very confident in AI’s outputs.

67% of C-suite leaders at enterprises report being very confident in AI’s outputs.

19% of enterprises identify shadow AI outside approved tools as a top anticipated risk.

Only 32% of enterprises apply AI and automation to clearly different tasks based on their distinct strengths.

78% of IT and cybersecurity decision-makers at enterprises say AI delivers greater financial return than automation.

17% of managers at enterrpises report that AI exceeded expectations.

52% of C-suite leaders at enterprises report that AI exceeded expectations.

87% of enterprises have deployed AI and automation in security operations simultaneously.

92% of IT and cybersecurity decision-makers at enterprises say automation has met or exceeded operational expectations in security operations.