Using AI to Manage Hybrid Environments – and Improve Security

It has taken very little time for AI’s risks to emerge. According to Verizon’s 19^th annual Data Breach Investigations Report, AI is fundamentally remodeling cyber security in real time, for everyone to see.

The benefits of AI take longer to manifest. Today’s government agencies find themselves managing a hybrid AI approach, balancing a mix of hosted provider models (like OpenAI and AWS Bedrock), open-source self-hosted models, and organization-specific fine-tuned models. When an organization scales AI, they don’t just use one model; they use a hybrid ecosystem. This is one area where AI’s protective capabilities can come into play.

Learning Objectives:

• Assess how your organization governs user access and identity controls across multiple AI models, platforms, and services within a Zero Trust framework
• Identify gaps in visibility, monitoring, and policy enforcement across AI endpoints, APIs, and models, and outline strategies to improve consistency and oversight
• Delineate safeguards and access controls that help prevent sensitive data exposure when employees and contractors interact with external AI services and generative AI tools