CIOs: here's how to operationalize security for LLMs and AI agents

As enterprises integrate large language models into operations, security often becomes secondary. With 71% of organizations using generative AI, CIOs face challenges securing systems against threats like prompt injection, model poisoning, and data leakage that traditional defenses can't address.

This guide offers a framework for LLM security across the AI lifecycle. Key areas include:

· Detecting shadow AI deployments to protect intellectual property
· Building runtime security and red teaming to counter emerging threats
· Securing Retrieval-Augmented Generation (RAG) and autonomous AI agents

Read the white paper to develop a proactive AI security program.