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 261-280 of 1475 results
23% of organizations identify leveraging AI/ML capabilities for business insights or automation as a main driver behind the use of APIs.
41% of developers, architects, and executives rely on AI to generate API documentation.
49% of developers are concerned about AI systems accessing sensitive data they shouldn't see.
43% of organizations are using specialized AI security tools.
47% of respondents cited difficulty understanding and securing AI-generated code.
68% of developers, architects, and executives rely on AI to improve code quality.
45% of respondents cited the potential for new API vulnerabilities tied to AI-generated code.
26% of organizations are adopting governance frameworks to establish rules for AI use in development.
5% of developers are actively transitioning from human-first to AI-first design for APIs.
13% of developers design APIs equally for humans and AI agents.
7% of developers primarily design APIs for AI agents/machine consumption.
35% of respondents cited difficulty ensuring quality and reliability of AI-generated code.
46% of developers worry about AI systems sharing or leaking API credentials.
62% of AI users within the global workforce use AI tools daily.
17% of employees in healthcare and pharma reported no training in AI tools.
65% of AI users in manufacturing engage with AI daily.
49% of AI users in education engage with AI daily.
54% of non-managers say they use AI in their work.
31% of organizations identify data sources and embeddings as their greatest AI supply chain risk.
Among managers, AI adoption sits at 79%.