Authors : Dr. Njoku Dominic Okechukwu; Ukachukwu Theddius Ndukaku; Okorie Juliet Ijeoma

Volume/Issue : Volume 11 - 2026, Issue 8 - August

Google Scholar : https://tinyurl.com/25jmfar7

DOI : https://doi.org/10.38124/ijisrt/26aug1393

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Artificial Intelligence (AI) agents have emerged as a transformative paradigm in modern computing, extending traditional artificial intelligence systems by enabling autonomous perception, reasoning, planning, learning, and decisionmaking. Recent advances in foundation models, large language models (LLMs), reinforcement learning, and multi-agent systems have significantly accelerated the adoption of AI agents across healthcare, finance, education, cybersecurity, manufacturing, transportation, agriculture, and smart cities. This review synthesizes the current state of AI agent research by examining their conceptual foundations, architectural components, classifications, learning mechanisms, and practical applications. Furthermore, the paper discusses emerging paradigms including autonomous agents, agentic AI, collaborative multi-agent systems, and LLM-powered intelligent assistants. Finally, key challenges including explainability, trustworthiness, safety, privacy, governance, and ethical considerations are critically analyzed, while future research directions are identified to support the development of robust, scalable, and human-centered AI agent ecosystems.

Keywords : Artificial Intelligence, Intelligent Agents, Agentic AI, Multi-Agent Systems, Large Language Models, Autonomous Systems, Machine Learning.

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