AI Tools
We've curated 75 cybersecurity statistics about AI Tools to help you understand how automation, machine learning, and predictive analytics are reshaping threat detection and response strategies in 2025.
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48% of employees say they would continue using AI even if it were explicitly banned
69% of C-suite leaders prioritize speed over security when using AI tools
37% of frontline employees prioritize speed over security when using AI tools
45% of employees find workarounds when AI tools are restricted
Nearly 90% of development teams encounter issues with AI-generated code.
86% of development professionals believe an AI agent or model should evaluate AI-generated code.
AI coding assistants have 97% adoption among enterprise development teams.
97% of development teams have adopted AI coding assistants.
Deployment of AI tools initially reduces performance by 10–20% before improvements are realized through repeated testing.
42% of organizations globally identify a lack of visibility into the AI tools employees use as a significant identity governance gap.
47% of large organizations do not have full visibility into employee AI tool usage.
47% of U.S. cybersecurity decision-makers report concern about lack of visibility into employee AI tool usage, compared with 42% globally.
Enterprises can track only 44% of the AI tools handling sensitive company and user data.
84% of people have not shared personal health information with AI tools.
88% of people do not freely share personal information with AI tools like ChatGPT and Gemini.
36% of CISOs report insufficient AI-specific security tools as a top challenge.
61% of organizations report the use of unsanctioned AI tools, creating significant visibility and governance gaps.
95% of surveyed organizations reported using AI tools in software development.
28% of organizations reported that cybersecurity AI tools improved their detection and response capabilities.
56% of employees are unhappy with their company's approach to AI tools, which can drive them toward unsanctioned platforms and creating 'shadow AI' risks.