Successfully migrating AI initiatives from proof of concept to production is critical to achieving a competitive advantage. AWS provides robust infrastructure to support the development and deployment of AI systems, including their Bedrock AI platform, support for a range of AI models and rich data storage capabilities.
The explosive growth of enterprise data, coupled with a complex regulatory landscape, makes securing sensitive data a formidable task. The rapid adoption as well as integration of GenAI and Agentic workflows further amplifies these challenges. While organizations are eager to leverage GenAI and deploy agents' data with AI, legacy security tools are ill-equipped to address the unique risks of this new paradigm, from data leakage to shadow AI.
Join Zscaler and AWS for an exclusive session to learn how our solutions work together to secure your data and accelerate AI adoption on the AWS platform. We will explore critical strategies and real-world use cases for navigating the intersection of AI, security, and compliance.
In this session, you will learn about:
- Emerging Risks: A deep dive into risk trends like shadow AI, data poisoning, and more.
- AI Governance Frameworks: How to apply best practices and standards like the NIST AI Risk Management Framework (RMF) to your organization.
- Actionable Strategies: Practical insights for building and executing a robust data and AI governance strategy.
Whether you are evaluating AI security solutions or defining your governance roadmap, this session will equip you with the insights to innovate securely, maintain compliance, and protect your enterprise data from costly risks.
