Improving Project Time and Cost Estimation Accuracy Using AI-Based Predictive Models

Authors

  • Sarah Johnson Assistant Professor of Project Management, University of Engineering, San Francisco, USA

Keywords:

AI, Predictive Models, Project Management, Time Estimation

Abstract

Accurate project time and cost estimation are crucial for successful project management, yet they often present significant challenges. Traditional estimation methods frequently lead to inaccuracies, resulting in project delays and budget overruns. This paper explores the application of Artificial Intelligence (AI)-based predictive models to enhance the accuracy of project time and cost estimations. By leveraging historical data and advanced algorithms, AI models can identify patterns and trends that inform more reliable estimates. The study presents various AI techniques, including machine learning and neural networks, detailing their effectiveness in minimizing estimation variance. Additionally, real-world case studies illustrate the successful implementation of these models in different project environments. The findings underscore the potential of AI to revolutionize project planning by providing data-driven insights that improve decision-making and resource allocation. Ultimately, integrating AI into project estimation processes can lead to improved project outcomes, including increased efficiency and reduced costs.

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Published

12-12-2023

How to Cite

[1]
Sarah Johnson, “Improving Project Time and Cost Estimation Accuracy Using AI-Based Predictive Models”, J. of Art. Int. Research, vol. 3, no. 2, pp. 199–205, Dec. 2023.

Issue

Vol. 3 No. 2 (2023): Journal of Artificial Intelligence Research

Section

Articles

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