AI security is often reactive, addressing vulnerabilities only after they are exploited. This session advocates for a proactive approach, demonstrating how security-minded strategies can enhance model robustness and prevent attacks before they occur. Attendees will learn about techniques such as adversarial training, threat modeling, and real-time monitoring to mitigate risks. By contrasting proactive security strategies with traditional reactive approaches, this session highlights the benefits of integrating security into the AI development lifecycle. Organizations adopting a proactive mindset can achieve not only robustness but also greater trust and reliability in their AI systems.