Design and Implementation of an AI-Powered Task Management System (TaskWise).

Abstract:

Managing tasks across academic, personal, and professional life remains a persistent struggle for most people, even with the growing number of digital tools available. The problem is not a shortage of apps—it is that the vast majority of them still require users to do most of the work manually: typing out tasks, setting deadlines one at a time, and remembering to check back. There is little to no intelligence built into these platforms to anticipate what a user might need next. This paper introduces TaskWise, a task management application that takes a different approach. Rather than forcing users into rigid input forms, TaskWise lets them type or speak commands in plain English—for example, “Remind me to submit my assignment by Friday”—and the system interprets those instructions to create, schedule, and organise tasks on their behalf. The application was built on a three-tier architecture: React and Tailwind CSS handle the frontend interface, Firebase Cloud Functions drive the backend logic, and Firestore provides real-time data synchronisation across devices. We also incorporated an AI-powered conversational assistant that can generate study plans, suggest tasks based on context, and respond to user queries in a natural, conversational tone. Testing with a small group of university students showed that users could create tasks significantly faster with the natural-language input compared to traditional form-based entry, and the System Usability Scale score came in at 82 out of 100. While the current version is still a prototype with clear limitations—particularly around offline support and team collaboration—TaskWise demonstrates that combining AI with cloud infrastructure can meaningfully reduce the friction involved in day-to-day task management.