• Dhivarath S
• Nithishkumar N
• Jeyam Brijith J
• Aswath A B
• Anuradha K

The rapid evolution of Artificial Intelligence (AI) has ushered in a new era of Agentic AI - systems capable of autonomously planning, reasoning, and executing multi-step tasks with minimal human intervention. This paper explore s the architecture, capabilities, and real-world applications of Agentic AI built upon Large Language Models (LLMs) such as GPT-4, Claude 3, and Google Gemini, deployed on cloud computing platforms including AWS, Azure, and Google Cloud. Unlike conventional AI systems that perform isolated, single-step tasks, Agentic AI systems leverage tool use, memory, and chain-of-thought reasoning to accomplish complex workflows autonomously. We examine frameworks such as Lang Chain, AutoGPT, Crew AI, and ReAct, evaluate their performance across diverse tasks, and analyse their integration with cloud-native microservices. Experimental analysis demonstrates that cloud-deployed LLM agents achieve task-completion accuracy exceeding 91% with average response latencies under 400 milliseconds. The findings suggest that Agentic AI represents the next frontier in intelligent computing, with transformative implications across healthcare, education, finance, and software development.

Agentic AI, Large Language Models (LLM), Cloud Computing, AutoGPT, Lang Chain, Autonomous Agents, Chain-of-Thought, Tool Use, GPT-4, Generative AI.

"AGENTIC AI: AUTONOMOUS INTELLIGENT AGENTS USING LARGE LANGUAGE MODELS AND CLOUD COMPUTING FOR REAL-WORLD TASK AUTOMATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 5, page no.d5-d9, May-2026, Available :http://www.jetir.org/papers/JETIR2605302.pdf

"AGENTIC AI: AUTONOMOUS INTELLIGENT AGENTS USING LARGE LANGUAGE MODELS AND CLOUD COMPUTING FOR REAL-WORLD TASK AUTOMATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 5, page no. ppd5-d9, May-2026, Available at : http://www.jetir.org/papers/JETIR2605302.pdf