The rapid adoption of AI coding assistants is reshaping software development, driving efficiency while introducing significant security and compliance challenges. These tools accelerate coding, reduce cognitive load, and democratize development, yet they also propagate vulnerabilities, amplify automation bias, and blur security responsibility. This talk explores the implications of AI-assisted coding, balancing its transformative potential with emerging risks, and outlines strategies to harness its benefits while mitigating security pitfalls.

The widespread adoption of AI coding assistants is transforming software development, offering efficiency gains while introducing new security, reliability, and compliance challenges. This talk provides a critical evaluation of their impact, examining empirical data on productivity improvements alongside emerging risks such as vulnerability propagation and automation bias. We explore frameworks for mitigating these risks through robust validation, oversight, and policy adaptation, ensuring AI-assisted development aligns with secure and responsible software engineering practices.