Intelligent Context-Aware Agent for Automating Repetitive Digital Tasks

Abstract

As digital platforms grow in education, business, and personal use, people rely more on automation tools. Yet, most current systems are rule-based and do not adapt well to changing user needs. This paper introduces an intelligent context-aware agent that automates repetitive digital tasks by understanding user intent, context, and interaction patterns. The system uses a context-driven decision engine, adaptive memory, and a task execution framework that works across different platforms. By learning from user actions and feedback, the agent offers personalized automation, reduces repeated inputs, and keeps multi-step workflows running smoothly. The design focuses on scalability and user control, letting users override decisions when needed. This approach aims to lower digital workload and improve productivity and user experience in various fields.