AI Task Classification And Prediction

The project “AI Task Classification and Priority Prediction” is an intelligent system designed to automatically analyze, classify, and prioritize tasks in project management environments. It uses Natural Language Processing (NLP) and Machine Learning models to examine task descriptions, determine the type of task (such as bug fix, feature development, testing, or documentation), and predict its urgency level based on factors like deadlines, dependencies, keywords, and historical data. The main purpose of the system is to reduce the time teams spend manually organizing tasks and deciding which tasks are most important. By automating these activities, the system helps organizations improve productivity, avoid delays, and ensure that critical tasks receive immediate attention. The proposed system includes: Automatic task classification using AI and NLP. Priority prediction using machine learning. Integration with project management tools such as Jira and Asana. An analytics dashboard to monitor classification accuracy, task distribution, and team performance. For example, if a task says: “Users are reporting issues logging in after a password reset,” the system classifies it as a Bug Fix with high confidence and assigns it a High priority because it affects user access. Technically, the project relies on tools such as BERT, spaCy, TensorFlow, and scikit-learn, while using PostgreSQL, Redis, and a data warehouse to store and manage task information. The architecture includes a frontend interface, backend services, AI models, and a database layer working together to provide fast and scalable task management. This work was conducted at Arab International University (AIU), Syria. The official website of the university is: https://www.aiu.edu.sy