The text discusses the critical importance of securing generative AI systems due to emerging vulnerabilities and threats in the AI supply chain, emphasizing the expanded attack surfaces that autonomous systems present. It highlights the necessity of multiple layers of protection, including strong processes, governance, and technical safeguards, to prevent attackers from exploiting AI systems. The text introduces frameworks like ISO/IEC 42001 and the NIST AI Risk Management Framework, which provide organizations with guidelines for managing AI risks across international boundaries and specific industries like healthcare and finance. It stresses the significance of secure AI lifecycle management, continuous security audits, red teaming, and incident response to safeguard AI systems effectively. To achieve robust AI security, the text advocates for a holistic approach involving cross-functional collaboration, comprehensive training, clear policies, and transparent documentation, integrating security considerations throughout the AI development lifecycle. This comprehensive strategy enables organizations to protect data, maintain customer trust, and innovate responsibly while embedding security-by-design principles in their AI strategies.