Only 17% of enterprises have full visibility into their AI-generated code.

AI-driven detection achieves 92.4% accuracy compared to 67% accuracy for human analysts alone.

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

Security teams' confidence in their ability to keep up with the security implications of AI adoption declined from 64% to 51%.

Shadow AI accounted for 20% of AI-related breaches affecting financial institutions.

44% of enterprises report low or no confidence in their ability to detect AI agent-specific threats.

All tested AI models now complete vulnerability research tasks, and 50% generate working exploits autonomously

61% of security professionals want a "strategic pause" to calibrate defenses against AI-driven threats, up from 48% last year.

8% of enterprises say AI agents never exceed their intended permissions.

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

53% of cybersecurity professionals identify lack of visibility into AI, automation and machine access as their top risk.

51% of organizations in Canada identify AI model monitoring, auditing and assurance tools as a priority.

49% of enterprise leaders anticipate a material AI-agent–driven security or fraud incident within six months.

97% of enterprise leaders expect a material AI-agent–driven security or fraud incident within 12 months.

18.39% of organizations have exposed OpenAI credentials.

28.49% of organizations have exposed Hugging Face tokens.

47% of organizations view AI as a top future threat to unstructured data, and 40% view AI as a core security capability for unstructured data.

10.10% of organizations have exposed Anthropic credentials.

41.88% of production organizations have leaked AI or ML credentials.

11.92% of organizations have exposed Databricks credentials.