Chapter 18Agentic AI
In this chapter, we will examine the following:
- Agentic AI
- How agentic AI works
- The orchestration layer
- Examples of real-world agentic applications
- Opportunities and risks
Chapter 17 explored generative AI (GenAI), systems that create new content based on what they’ve learned from massive datasets. GenAI marks a turning point: AI isn’t just analyzing data—it is producing something new from it. While these systems are impressive in their own right, they don’t take action. The next evolution of AI is agentic AI. In this chapter, we’ll look at agentic AI—what it is, how it works, and the opportunities and risks it poses.
What Is Agentic AI?
GenAI, powered by large foundation models, is revolutionizing the way people interact with data and technology. Organizations are using GenAI to democratize AI through natural language interfaces, copilots, assistants, and creative tools that can draft text, summarize reports, or generate images on demand. Yet as transformative as this is, these systems remain largely reactive. They respond to prompts but do not decide what to do next. They do not plan, reason over time, or act toward goals. In short, they generate but they don’t take action. Enter agentic AI, one of the hottest topics in AI today. Once mature, it may have the ability to completely disrupt how a lot of work is done.
Agentic AI extends GenAI by embedding intelligence within autonomous or semi-autonomous systems that can plan, reason, and take actions ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access