AI Security
We've curated 152 cybersecurity statistics about AI security to help you understand how AI is being used to detect threats, enhance defenses, and even automate responses in the ever-evolving landscape of cybersecurity in 2025.
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85% of security and IT leaders identify security incidents, data exposures, or near misses where the root cause is an AI system.
42% of security professionals plan to increase human-led red team operations.
60% of security professionals state they require stronger LLM testing capabilities.
32% of AI-related pentest findings were classified as high risk, compared to 12% of all pentest findings overall.
77% of organizations conduct regular security assessments and pentests for AI-powered products, an increase of 11 percentage points from last year.
The meantime to resolve (MTTR) for AI/LLM security issues is 36 days, up from 19 days in 2025.
82% of security professionals report that their teams are dedicating significantly more effort into AI security initiatives.
38% of LLM vulnerabilities were fixed while 62% remain open.
55% of security and IT leaders cite AI agents, agentic infrastructure, and Gen AI applications as the biggest cybersecurity risk to their organization.
36% of security and IT leaders identify third-party vendor or supply chain breaches involving integrated AI or agents as security incidents tied to AI systems.
38% of security and IT leaders identify compromised AI identity and session theft as security incidents tied to AI systems.
30% of security and IT leaders report AI-generated alerts produce false positives that negatively impact investigation timelines.
Among organizations with confirmed AI-related security incidents, Shadow AI contributed to 44% of incidents, data or model poisoning 41%, improper output handling 41%, supply chain vulnerabilities 35%, and prompt injection 34%.
42% of U.S. mid-market enterprise IT leaders reported a confirmed AI-related security incident or exposure in the past 12 months.
31% of U.S. mid-market enterprise IT leaders reported an AI-related near-miss in the past 12 months.
Roughly 73% of U.S. mid-market enterprise IT leaders have either confirmed an AI-related security incident or experienced a near-miss in the past 12 months.
83% confirmed incident rate for organizations using multi-tenant SaaS identity platforms.
30% of development professionals believe the same AI model that generated the code should also review it for security issues.
65% of organizations experienced a confirmed AI identity-related security incident in the past 12 months.
80% of organizations report shadow AI (employees connecting AI tools without security or IT review).