Agentic AI for Personal Task Automation

Prof. Sakshi Wankhede; Pratik Lambat; Aryan Bhoyar; Falgun Wabhitkar

doi:10.26706/ijceae.7.4.20260711

Abstract

Agentic AI is changing the way we think about intelligent systems. Instead of waiting to be told exactly what to do, these AI agents can plan, think things through, and get tasks done largely on their own. That is what makes it different. Old automation tools were rigid — they only did what they were programmed to do. Agentic AI is not like that. It reads the situation, understands what you actually need, and adjusts as things change around it. This research paper analyzes the application of Agentic AI in personal task automation and explores the potential application of intelligent agents for automating personal tasks such as scheduling, information retrieval, communication management, and workflow optimization. The paper explains the main functional process of Agentic AI, which includes task understanding, decision-making, and action execution using large language models and third-party services. Real-world examples are also provided to demonstrate the application of Agentic AI for enhancing productivity, efficiency, and usability. We also take a honest look at where things can go wrong with autonomous agents. Data privacy, security risks, and reliability — these are real concerns that cannot be ignored. And yet, the overall picture remains exciting. Agentic AI is showing us that personal automation does not have to be rigid or impersonal. It can actually grow with you, work smarter over time, and feel a lot more human.

Keywords

Agentic AI Personal Task Automation Intelligent Agents Autonomous Systems Large Language Models AI Decision-Making

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[ref5] 5. Significant Gravitas , “Auto-GPT: An autonomous GPT-4 experiment,” GitHub Repository, 2023. [Online]. Available: https://github.com/Significant-Gravitas/Auto-GPT

[ref6] 6. W. van der Aalst , Process Mining: Data Science in Action. Berlin, Germany: Springer, 2016.

[ref7] 7. IBM Research , “Agentic AI and autonomous systems,” Tech. Rep., 2023.

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