AI Development Risk Case Studies and how Agentic AI is the future of Appsec

AI is transforming how software is designed, developed, and deployed, dramatically accelerating velocity while introducing new categories of risk. As organizations adopt AI-assisted coding, autonomous agents, and increasingly complex model interactions, traditional application security approaches struggle to keep pace. This talk examines emerging AI-driven risks through real case studies from the field, highlighting issues such as insecure code generation, data-leakage pathways, model manipulation, and evolving supply-chain threats. We will explore how engineering teams must adapt their people, processes, and governance models to secure AI-augmented development workflows effectively. The session will then introduce agentic AI as the next evolution in application security—autonomous systems capable of continuous analysis, multi-step reasoning, and real-time remediation. Attendees will learn how combining agentic AI with modern practices can reduce developer friction, improve coverage, and create a future-ready application security strategy designed for the demands of AI-native software development