Abstract
This work develops a conceptual framework for cost estimating using Artificial Intelligence. Machine learning methods and generative AI methods are brought together around the cost estimating process tasks in order to improve productivity and provide alternative data analysis methods. In particular prompt engineering is explored as a way of developing initial cost estimating structure and subsequently a range of machine learning methods are compared in their accuracy and explainability. The work brings together recent projects taking place at the University of Manchester and hence synthesise cases and applications into one methodology.
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