AI-Driven Budget Estimation in End-User Software Engineering: An Excel-Python Approach

Abstract

Artificial Intelligence (AI) is rapidly transforming the landscape of project management by enhancing the accuracy, efficiency, and responsiveness of key operations such as budget estimation, resource allocation, and scheduling. This research introduces an AI-driven model that leverages machine learning techniques within an integrated Excel-Python framework to predict software project budgets. Utilizing historical data from completed projects, the model delivers precise cost estimations, enabling project managers to plan effectively and allocate resources efficiently. In contrast to traditional estimation approaches, this method supports real-time decision-making, predictive analysis, and dynamic adjustments throughout the project lifecycle. The approach incorporates AI techniques such as linear regression, genetic algorithms, and neural networks to optimize budget forecasting and personnel distribution. Designed to be accessible to end users with minimal technical expertise, the model provides a practical, data-driven tool that enhances the operational and financial performance of software development initiatives. This work not only extends prior research on AI-enabled resource management but also contributes a user-friendly solution for the modern demands of intelligent project planning.