Looking Forward: Challenges and Opportunities in Agentic AI Reliability

TL;DR

This paper discusses the challenges and future research directions in ensuring the reliability of agentic AI systems, focusing on risks, testing, and evaluation in dynamic and complex environments.

Contribution

It identifies key open problems and proposes research opportunities for improving the reliability of agentic AI systems in various challenging scenarios.

Findings

Highlighting risks of cascading failures in agentic AI

Identifying challenges in testing and evaluation of reliability

Proposing future research directions for reliable agentic AI

Abstract

This chapter presents perspectives for challenges and future development in building reliable AI systems, particularly, agentic AI systems. Several open research problems related to mitigating the risks of cascading failures are discussed. The chapter also sheds lights on research challenges and opportunities in aspects including dynamic environments, inconsistent task execution, unpredictable emergent behaviors, as well as resource-intensive reliability mechanisms. In addition, several research directions along the line of testing and evaluating reliability of agentic AI systems are also discussed.