AI Security Benchmark
2026 Benchmark Report

State of Enterprise
AI Security

The 2026 benchmark of enterprise AI security practices, shadow AI prevalence, and governance readiness, compiled from published industry research. Understand the risks. Take control.

48%
of employees have entered non-public company information into AI tools (Cisco, 2024)
63%
of organizations lack AI governance policies to prevent shadow AI proliferation (IBM, 2025)
83%
year-over-year surge in enterprise AI activity (Zscaler 2026)
16 min
average time to compromise an enterprise AI system (Zscaler ThreatLabz 2026)
Executive Summary

AI adoption is outpacing security at every level

Enterprise AI adoption has reached an inflection point. Published research paints a stark picture: enterprise AI activity surged 83% year over year (Zscaler ThreatLabz, 2026), while security and governance frameworks have failed to keep pace.

Shadow AI (the use of unsanctioned AI tools by employees) has emerged as the single largest unmanaged risk in enterprise security. With 78% of AI users bringing their own AI tools to work (Microsoft & LinkedIn Work Trend Index, 2024), sensitive data is being shared with third-party models at an unprecedented scale.

This benchmark curates that data for CISOs, CIOs, and security leaders. Figures with a named source come from published research; the remaining figures are illustrative estimates, clearly marked as such.

AI Governance Maturity (IBM, 2025)

10%Enforced policy
27%Policy exists (unenforced)
63%No AI governance
Preview

Top Findings at a Glance

Shadow AI in Published Research

AI users who bring their own AI tools to work (Microsoft & LinkedIn, 2024)78%
Organizations lacking an AI governance policy (IBM, 2025)63%
Gen AI adopters using unapproved tools at work (Salesforce, 2024)55%
Employees who entered non-public company data into AI tools (Cisco, 2024)48%

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