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Securing LLMs in the Enterprise: Managing Risk Without Slowing Innovation


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Tunde Dada of inq. digital Group guides leaders through enterprise LLM security challenges, offering practical strategies for managing data leakage, prompt injection and compliance gaps while enabling AI innovation.

Large language models are rapidly entering enterprise workflows - from customer service automation to threat intelligence augmentation.

But with new opportunities come new risks: data leakage, prompt injection, unauthorized access and compliance gaps. This session will guide security and IT leaders through the evolving threat landscape of enterprise LLMs, offering practical strategies for securing models, controlling access and aligning deployments with internal policies and regulatory requirements.

In this session, led by Tunde Dada, group CIO/BCM at inq. digital Group, you will:

  • Learn how prompt injection, model manipulation and data exposure can compromise enterprise LLM deployments;
  • Explore frameworks for access controls, usage monitoring and internal policy enforcement around generative AI tools;
  • Discover how to secure LLM pipelines - from data inputs and APIs to model hosting environments and third-party integrations.
 

Here is the course outline:

Securing LLMs in the Enterprise: Managing Risk Without Slowing Innovation

Completion

The following certificates are awarded when the course is completed:

CPE Credit Certificate