64% of development teams express moderate or extreme concern about AI coding assistants introducing security defects or vulnerabilities.

48% of development teams experience bottlenecks in code rework related to AI-generated code.

51% of development teams experience bottlenecks in security testing related to AI-generated code.

29% of security leaders identify insecure coding patterns as the leading risk introduced by AI coding assistants.

15% of security leaders cite misalignment with internal security policies as a major concern with AI-generated code.

90% of security leaders have active concerns about security risks introduced by AI-generated code.

38% of organizations still rely primarily on manual review for AI-generated code.

67% of organizations report that AI coding assistants are now widely adopted across development teams.

45% of security and DevOps professionals say reviewing and hardening AI-generated code is now a major time drain.

35% of enterprises report limited or no visibility into their AI-generated code.

86% of enterprises are using AI-generated code in production.

Only 17% of enterprises have full visibility into their AI-generated code.

46% of enterprises use AI-generated code frequently or always.

89% of enterprises are confident in their ability to secure AI-generated code.

70% of enterprises have confirmed or suspected vulnerabilities introduced by AI-generated code in their production systems.

Nearly half (48%) of all code is now AI-generated.

24% of organizations perform comprehensive IP, license, security, and quality evaluations for AI-generated code.

76% of organizations check AI-generated code for security risks.

54% of organizations evaluate AI-generated code for IP and license risks.

56% of organizations assess quality issues in AI-generated code.