Generative AI for Construction Cost Estimation and Budget Optimization in Construction Projects

The construction industry is undergoing a significant transformation due to the adoption of advanced digital technologies such as Artificial Intelligence (AI), Building Information Modeling (BIM), and data analytics. Among these innovations, generative artificial intelligence has emerged as a powerful tool capable of improving decision-making processes and automating complex analytical tasks. One of the major challenges in construction project management is achieving accurate cost estimation and maintaining effective budget control throughout the project lifecycle. Traditional cost estimation methods mainly depend on historical data, manual calculations, and professional experience, which can sometimes result in inaccurate forecasts and financial inefficiencies. Generative AI offers new possibilities for construction management by analysing large datasets, identifying hidden patterns, and generating predictive models that assist project managers in making informed financial decisions. This research paper examines the potential role of generative AI in improving construction cost estimation and optimizing project budgets. The study explores how AI-based systems can support automated quantity take-offs, predictive cost modelling, real-time cost monitoring, and efficient resource allocation. The research also analyses the advantages and limitations associated with implementing generative AI technologies in the construction sector. The findings suggest that generative AI can significantly improve cost estimation accuracy, reduce financial risks, and enhance project planning. However, effective implementation requires reliable digital infrastructure, high-quality datasets, and trained professionals with expertise in AI technologies. The study concludes that generative AI has the potential to transform construction cost management practices and contribute to more efficient and sustainable project execution.