The AI Fog Report: When the Signal Becomes the Noise

Among cybersecurity decision-makers and practitioners experiencing increased alert volume, 26.2% attribute the growth to AI enabling attackers to launch attacks faster

84.5% of cybersecurity decision-makers and practitioners have encountered a confirmed or suspected AI-assisted attack during the past year

54.8% of cybersecurity decision-makers and practitioners say alert noise interferes with incident response daily or several times each week

48.9% of cybersecurity decision-makers and practitioners identify AI-generated alerts lacking sufficient context as a leading source of low-quality signal

56.0% of cybersecurity decision-makers and practitioners rank faster detection-to-containment as AI's most valuable operational outcome

16.5% of cybersecurity decision-makers and practitioners plan to increase AI-powered security tool adoption over the next 12 months

24.5% of cybersecurity decision-makers and practitioners fully trust autonomous AI remediation

87.1% of cybersecurity decision-makers and practitioners report making at least minor security policy exceptions to enable AI tools

51.9% of cybersecurity decision-makers and practitioners maintain a comprehensive inventory of AI tools operating across their environments

Among cybersecurity decision-makers and practitioners experiencing increased alert volume, 40.2% attribute the growth to adding more detection tools

Among cybersecurity decision-makers and practitioners experiencing increased alert volume, 20.1% say multiple factors are contributing simultaneously

75.5% of organizations still don't fully trust AI-powered remediation without human review

86.1% of cybersecurity decision-makers and practitioners report security alert volumes increased over the past 12 months

8.7% of cybersecurity decision-makers and practitioners report that alert noise rarely or never affects operations

50.4% of cybersecurity decision-makers and practitioners identify duplicate alerts from overlapping tools as a leading source of low-quality signal

37.8% of cybersecurity decision-makers and practitioners say both broader detection coverage and better signal precision are equally important AI optimization goals

32.6% of cybersecurity decision-makers and practitioners prioritize broader detection as AI's optimization goal

29.6% of cybersecurity decision-makers and practitioners prioritize fewer, higher-confidence alerts as AI's optimization goal

81.0% of cybersecurity decision-makers and practitioners have meaningfully increased AI-powered security tool adoption during the past year

62.7% of cybersecurity decision-makers and practitioners require full explainability before trusting autonomous AI

59.8% of cybersecurity decision-makers and practitioners require built-in human override before trusting autonomous AI

41.0% of cybersecurity decision-makers and practitioners are very confident their existing security stack can keep pace with AI without a significant overhaul

24.2% of cybersecurity decision-makers and practitioners say alert volume increased by more than 50% over the past 12 months