88% of senior legal professionals believe that AI-enabled systems are driving an increase in infringement activity

85% of senior legal professionals reported an increase in intellectual property infringements at their firms over the past 12 months

40% of cybersecurity professionals in the United States reported that Multi-Factor Authentication (MFA) is not consistently enforced for privileged accounts in 2025.

16% of cybersecurity professionals in the United States reported that their organizations are fully prepared to handle AI-enhanced attacks in 2025.

72% of organizations across the U.S., U.K., France, Germany, and Australia reported that the security risks for their company have never been higher in 2025, marking a 17 point increase from 2024.

33% of respondents say AI agents shared sensitive or inappropriate data

80-90% of AI-generated code generates functional code for immediate prompts but never refactors or architecturally improves existing code.

AI-powered phishing campaigns achieve a 54% click-through rate, over four times higher than traditional phishing.

60-70% of AI-generated code lacks deployment environment awareness, generating code that runs locally but fails in production.

40% of organizations reported that they already use AI for threat hunting in 2025.

40-50% of AI-generated code defaults to tightly-coupled monolithic architectures, reversing decade-long progress toward microservices.

40-50% of AI-generated code inflates coverage metrics with meaningless tests rather than validating logic.

20-30% of AI-generated code over-engineers for improbable edge cases, causing performance degradation and resource waste.

40-50% of AI-generated code reimplements from scratch instead of using established libraries, SDKs, or proven solutions.

70-80% of AI-generated code violates code reuse principles, causing identical bugs to recur throughout codebases, requiring redundant fixes.

80-90% of AI-generated code rigidly follows conventional rules, missing opportunities for more innovative, improved solutions.

80-90% of AI-generated code creates hyper-specific, single-use solutions instead of generalizable, reusable components.

90-100% of AI-generated code contains excessive inline commenting, which dramatically increases computational burden and makes code harder to check.

42% of companies globally do not have a policy in place to govern the use of AI by employees as of 2025.

72% of companies globally do not have a policy for the use of generative AI by partners and suppliers as of 2025.