AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenge

Summary

This paper talks about the differences between regular AI agents and something called Agentic AI, explaining how they're built, what they can do, and where they're used, while also laying out the main challenges and possible solutions for each type.

What's the problem?

The problem is that people often mix up the terms AI agents and Agentic AI, even though they have different abilities and are designed in different ways, which can cause confusion when building or using these systems.

What's the solution?

The researchers created a clear system, or taxonomy, that sorts out and explains the differences between these two types of AI, shows where each one fits in real-world applications, and discusses the unique challenges and solutions for both.

Why it matters?

This matters because understanding these differences helps developers, businesses, and users choose the right kind of AI for their needs, and also prepares everyone to handle the challenges that come with more advanced, independent AI systems.