A Framework for Intelligent Task Automation Using Large Language Model-Based AI Agents
Keywords:
Large Language Models, AI Agents, Intelligent Automation, Generative AI, Task Automation, Multi-Agent Systems, Artificial Intelligence.Abstract
Large Language Models (LLMs) have created new opportunities for automating complex tasks that traditionally require human involvement. Traditional automation systems mainly depend on predefined rules and fixed workflows, making them less flexible when tasks involve unstructured information or changing requirements. LLM-based AI agents can understand natural language instructions, plan activities, use external tools, and complete multiple steps to achieve a given objective. This paper proposes a framework for intelligent task automation using LLM-based AI agents. The framework combines task understanding, planning, agent coordination, tool integration, memory, result verification, and human supervision. The proposed approach enables complex tasks to be divided into smaller activities and handled by specialized agents. The framework can be applied to business processes, software development, research activities, customer support, data analysis, and other digital workflows. The study discusses the architecture, operational process, implementation considerations, advantages, limitations, and evaluation approach of the proposed framework. The proposed framework provides a structured approach for developing flexible and reliable AI-driven automation systems.
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Copyright (c) 2026 Lakshmi Priya (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
