Securing AI: Runtime Protection for Multicloud Environments
Secure your AI and cloud workloads, from posture to runtime, with next-generation AI security for multicloud environments
As AI rapidly transforms enterprise workloads and multicloud adoption accelerates, security teams face growing pressure to protect distributed AI and GenAI systems, APIs, data, and cloud infrastructure in real time.
In this webinar, we'll examine how the AI threat landscape is evolving, why traditional cloud security approaches fall short, and what it takes to secure AI workloads across AWS, Azure, GCP, and hybrid environments. From posture management to runtime detection, you'll learn practical strategies for reducing risk while maintaining speed and scale.
Join Sysdig's Dan Belmonte as he breaks down emerging attack patterns, regulatory and governance drivers, and actionable approaches for securing AI and cloud workloads. He'll also explore how AI-powered security can help teams detect threats earlier, prioritise what matters most, and respond faster than ever.
Key Takeaways
- How AI-targeted attacks are increasing, including abuse of model APIs, data exposure, and cloud service misuse
- The growing importance of runtime security, as posture alone can't keep pace with fast-moving threats
- The hidden risks of "Shadow AI" and unmanaged AI services operating outside governance controls
- Implementing risk-based security controls aligned with AI governance frameworks (EU AI Act, NIST AI standards, etc)
- Why continuous compliance across clouds is becoming a competitive advantage, not just a checkbox
- How AI, through language insights and contextual security data, can help accelerate mean time to resolution in Security and DevOps teams
Speaker:
Dan Belmonte, Strategic Alliances Solutions Architect, Sysdig
