Generative to Agentic AI: Survey, Conceptualization, and Challenges

TL;DR

This paper surveys the evolution from Generative AI to Agentic AI, highlighting their differences, recent developments, practical challenges, and future research directions in creating more autonomous and reasoning-capable AI systems.

Contribution

It provides a comprehensive comparison of GenAI and Agentic AI, clarifies their distinctions, and discusses recent advances and challenges in developing agentic capabilities.

Findings

Agentic AI offers enhanced reasoning and interaction over GenAI.

The survey identifies key challenges and future research directions.

Practical concerns include defining agents and managing risks.

Abstract

Agentic Artificial Intelligence (AI) builds upon Generative AI (GenAI). It constitutes the next major step in the evolution of AI with much stronger reasoning and interaction capabilities that enable more autonomous behavior to tackle complex tasks. Since the initial release of ChatGPT (3.5), Generative AI has seen widespread adoption, giving users firsthand experience. However, the distinction between Agentic AI and GenAI remains less well understood. To address this gap, our survey is structured in two parts. In the first part, we compare GenAI and Agentic AI using existing literature, discussing their key characteristics, how Agentic AI remedies limitations of GenAI, and the major steps in GenAI's evolution toward Agentic AI. This section is intended for a broad audience, including academics in both social sciences and engineering, as well as industry professionals. It provides the necessary insights to comprehend novel applications that are possible with Agentic AI but not with GenAI. In the second part, we deep dive into novel aspects of Agentic AI, including recent developments and practical concerns such as defining agents. Finally, we discuss several challenges that could serve as a future research agenda, while cautioning against risks that can emerge when exceeding human intelligence.