Ai-driven Smart Project Management System With Predictive Analytics (ml + Nlp)

Abstract

This Paper Presents An Artificial Intelligence Driven Project Management System Designed To Predict Project Delays And Assess Associated Risks Using A Hybrid Analytical Approach. The Proposed System Integrates Machine Learning And Natural Language Processing To Evaluate Both Structured Project Data And Unstructured Textual Updates. A Random Forest Model Is Employed To Estimate Delay Probability Based On Key Project Attributes, While A Rule Based Text Analysis Module Identifies Risk Indicators From Progress Reports And Team Communications. These Outputs Are Further Combined Through A Risk Fusion Mechanism To Generate A Comprehensive Risk Score, Enabling More Accurate And Context Aware Decision Making. In Addition, A Root Cause Analysis Component Is Incorporated To Provide Interpretable Insights Into The Factors Contributing To Potential Delays, Thereby Supporting Proactive Intervention Strategies. The System Is Implemented Using A Flask Based Backend With A Lightweight Database For Data Management And A User Interface For Interaction. Experimental Evaluation On An Agile Project Dataset Demonstrates The Effectiveness Of The Integrated Approach In Identifying Risk Patterns And Improving Early Detection Of Delays. The Proposed Framework Offers A Practical And Scalable Solution For Enhancing Project Monitoring, Reducing Uncertainty, And Supporting Informed Managerial Decisions In Dynamic Development Environments.

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