AI
We've curated 1475 cybersecurity statistics about AI to help you understand how machine learning algorithms, automated threat detection, and AI-driven defenses are shaping the landscape of cybersecurity in 2025.
Showing 1241-1260 of 1475 results
Only 22% of all AI applications are in adherence to one or more compliance certifications such as HIPAA, PCI, ISO, FISMA, and FedRAMP.
44% of security leaders surveyed plan to prioritize security infrastructure oversight and implementation, much of which now focuses on securing AI systems and preventing data leakage.
84% of AI applications don’t support ‘Data Encryption at Rest’.
95% of AI applications are at medium or high risk for EU GDPR violation.
In response to simple, “naive” prompts, all LLMs tested generated insecure code vulnerable to at least 4 of the 10 common CWEs.
When prompted to generate secure code, GPT-4o still produced insecure outputs vulnerable to 8 out of 10 issues.
Some open security issues in Agentic AI are lingering for 1,200-plus days.
Prompts specifying a need for security or requesting OWASP best practices produced more secure results, yet still yielded some code vulnerabilities for 5 out of the 7 LLMs tested.
Only 15% of organizations deployed their most recent automation in under a month.
Traditional integrated development environments (IDEs) experienced a 23.7% decline in usage when AI alternatives become available
Llama has consistently accounted for at least 50% of local model development over the past twelve months.
Only 6% of respondents currently have fully mature automation programmes.
53% of organizations plan to adopt AI agents for threat detection.
Only 15% of organizations deployed their most recent automation in under a month.
Developer adoption of DeepSeek surged rapidly, reaching 17.7% of AI development activity by February 2025.
DeepSeek usage in developer activity partially subsided by March 2025, settling at 11.0%.
Only 16.2% of enterprise data input into AI tools is destined for enterprise-ready, low-risk alternatives.
Health records comprise 7.4% of sensitive data going into AI.
94% of energy firms are pushing to adopt AI-driven cybersecurity due to revenue losses and disruptions caused by ransomware and phishing.
29% of organizations struggle with compliance since auditors require proof of data security and privacy in AI-based systems.