AI Security
Cybersecurity statistics about ai security
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42% of security professionals plan to increase human-led red team operations.
85% of security and IT leaders identify security incidents, data exposures, or near misses where the root cause is an AI system.
The meantime to resolve (MTTR) for AI/LLM security issues is 36 days, up from 19 days in 2025.
60% of security professionals state they require stronger LLM testing capabilities.
38% of LLM vulnerabilities were fixed while 62% remain open.
32% of AI-related pentest findings were classified as high risk, compared to 12% of all pentest findings overall.
82% of security professionals report that their teams are dedicating significantly more effort into AI security initiatives.
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%.
77% of organizations conduct regular security assessments and pentests for AI-powered products, an increase of 11 percentage points from last year.
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.
31% of U.S. mid-market enterprise IT leaders reported an AI-related near-miss in the past 12 months.
42% of U.S. mid-market enterprise IT leaders reported a confirmed AI-related security incident or exposure in the past 12 months.
30% of development professionals believe the same AI model that generated the code should also review it for security issues.
45% of organizations are still developing AI governance programs.
64% of organizations that rate themselves "very confident" in their AI security posture have experienced a confirmed AI identity incident.
80% of organizations report shadow AI (employees connecting AI tools without security or IT review).