9% of organizations have full integration of AI with modified workflow.

20% of organizations are implementing AI in high-priority systems.

35% of organizations reported a lack of AI policy as a challenge in using AI for cybersecurity.

36% of organizations reported a lack of appropriate data sets as a challenge in using AI for cybersecurity.

16% of healthcare IT and compliance leaders admit compliance was never consulted before AI email tools were enabled.

41% of healthcare IT and compliance leaders feel confident they could detect improper AI use before a HIPAA violation occurs.

Only 42% of healthcare organizations have signed a Business Associate Agreement (BAA) covering any AI assistant used in email.

Only 29% of all companies have fully integrated AI into security and identity systems, compared to 62% of Pacesetters (most AI-ready group).

81% of Pacesetters (most AI-ready group) report full capability to detect and prevent unauthorized tampering, compared to 29% of all companies.

51% of organizations surveyed focus on recruiting the right talent to manage AI-specific cybersecurity threats.

Talent gaps are most acute in the area of cybersecurity for AI, affecting 60% of all companies surveyed.

41.9% of organizations surveyed perceived generative AI applications as a risk, ranking third compared to legacy systems at 23.5% and endpoint devices at 30.6%.

68% of developers, architects, and executives rely on AI to improve code quality.

23% of organizations identify leveraging AI/ML capabilities for business insights or automation as a main driver behind the use of APIs.

43% of organizations are using specialized AI security tools.

26% of organizations are adopting governance frameworks to establish rules for AI use in development.

41% of developers, architects, and executives rely on AI to generate API documentation.

33% of developers have ethical, legal, and compliance concerns about AI tools.

24% of developers actively design APIs with AI agents in mind.

5% of developers are actively transitioning from human-first to AI-first design for APIs.