This guide explores the risks introduced by widespread adoption of generative AI coding tools, including the high likelihood of insecure code generation and overreliance by developers. It emphasizes that AI systems produce probabilistic outputs that may include vulnerabilities, biases, or inaccuracies, requiring strong human oversight and additional security controls. The guide presents a holistic approach across people, processes, and tools, including developer education, secure development practices, and continuous monitoring. It highlights the importance of integrating security into developer workflows through real-time scanning, automated remediation, and AI-aware security tools. It also addresses governance, compliance, and risk management considerations such as data protection, audit

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