The headline number matters. The blind spots matter even more.
In the 2026 GenAI Code Security Report, AI-generated code shows major variation by vulnerability class. Some issues are handled relatively well. Others remain persistent weak points. That means the real control question is no longer “Do we allow AI- generated code?” It is “Where do we require independent verification, and how do we enforce it consistently?”
This is especially relevant for security leaders balancing secure delivery with regulatory accountability. If your development workflows assume the model is the control, your risk posture is built on weak assumptions.
Join this live webinar to learn how the findings should influence:
- Control design for AI-assisted development
- Release-gate policies for high-risk code paths
- Prioritization for the classes most likely to evade model reasoning
- Alignment across security, engineering, risk, and compliance
We will also discuss how stronger visibility, faster remediation, and software supply chain protections help organizations manage AI-driven development with more confidence and less friction.