Risks in AI-Native Systems: Why AI Security Is Still an API Security Problem | On-demand Webinar | Harness Resources

The shift to AI-native design drastically expands the enterprise API attack surface. Large Language Models (LLMs) and autonomous agents operate via complex, API-chained workflows. This reality of AI system architecture introduces high-velocity, non-deterministic execution paths across your cloud footprint. For security teams, this mandates a strategic pivot: AI security is fundamentally still an API security challenge, but with additional AI uniqueness that can’t be overlooked. AI systems create severe, novel risks around sensitive data exposure, agent identity management, and behavioral anomalies that legacy application security tooling fails to address. In this session, you will learn: How threats such as prompt injection, model misuse, shadow AI and supply-chain poisoning impact AI-native systems Why limited visibility and control across the AI and API ecosystem creates significant security risk How organizations can apply proven API security practices to AI-driven environments Strategies for improving AI discovery, testing and protection across AI-native applications.