What is generative AI?
Generative AI is a type of artificial intelligence that actually creates things—meaning it doesn't just analyze data.
Whether it's writing text, generating code, making images, composing music, or even designing new product ideas, generative AI uses patterns in data to produce brand-new content that looks like a human made it.
Depending on what it generates, it's powered by large language models (LLMs) or Generative Adversarial Networks (GANs).
What role does generative AI play in identity security?
You might not expect creativity in cybersecurity, but generative AI plays a powerful behind-the-scenes role. It can help write access policies, generate risk scenarios, draft documentation, or simulate attacks for testing security controls—all based on learned patterns and context.
What are the key characteristics of generative AI?
- It's trained on massive datasets, making it possible to learn how we write, speak, code, or behave
- It creates net-new content, which means it doesn't just pull from a template; it generates original responses
- It's highly adaptable, making it possible to tailor outputs based on prompts, inputs, or changing goals
- It's designed to help humans be more productive, creative, and efficient
Why should you care about generative AI?
Generative AI is changing the way just about everyone works, from writing content to making decisions. In your identity security tech stack, it can help you stay ahead of threats, reduce busy work, and respond faster by creating the right resources at the right time.
Real-world example of generative AI:
You ask a generative AI tool to draft a policy for least privilege access in a hybrid environment. It uses existing best practices, industry terms, and risk frameworks to create a solid first draft—saving your team hours of work.
How are organizations leveraging AI in their identity security strategies?