How to Build AI-Native Security Resilience

The State of AI-Native Application Security 2025 research report highlights a growing divide between developers and security professionals, exacerbated by the rapid integration of AI applications within organizations, which are increasingly posing security risks. With 62% of respondents unable to identify where large language models (LLMs) are located within their organizations, and 75% acknowledging the evolution of AI applications outpacing security measures, the report underscores significant vulnerabilities. Despite the potential for collaboration, only a minority of developers consult security teams before initiating or launching AI projects, and a substantial 74% of security leaders perceive developers as viewing security as a hindrance to innovation. However, the report suggests that by adopting AI-native security resilience, organizations can simultaneously harness AI's value and ensure security, advocating for a cultural shift towards shared governance, real-time monitoring, AI-specific threat testing, and consistent security measures throughout the application lifecycle. The integration of platforms like Harness and Traceable is recommended to unify development and security efforts, ensuring seamless collaboration and reducing the burden on developers by automating security processes and enhancing AI visibility.