Author(s): Sunil Karthik Kota
Artificial Intelligence (AI) agents have evolved from early rule‐based systems to today’s sophisticated autonomous systems. This comprehensive review examines the historical development, technical advancements, and emerging trends in AI agent research. Specifically, we address the following research questions:
• How have AI agent architectures evolved over time, and what factors drove these changes?
• What are the strengths and limitations of rule‐based versus learning‐based approaches in real-world applications?
• How can ethical frameworks and empirical case studies inform future developments in AI agent technology?
This article outlines the selection criteria for the literature review, presents empirical examples from diverse application domains, and critically analyzes methodologies. It discusses both achievements and persistent challenges in AI agent research while offering recommendations for future research directions and governance.
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