Yes, artificial intelligence is increasingly being utilized to forecast project costs by evaluating historical data from similar previous projects. This predictive power is particularly useful in businesses where cost overruns are common, and forecasting accuracy is critical.
- Data Aggregation - AI systems combine previous project data, such as work length, resource rates, material costs, and contingency spending. It finds cost drivers by comparing these to project type, scope, and complexity.
- Machine Learning Models - This dataset is used to train regression models, decision trees, and neural networks. These models identify trends such as scope expansion, risk impact, and resource utilization anomalies that influenced prior expenditures.
- Real-Time Adjustment - When applied to new projects, AI can provide real-time forecasts based on project parameters such as progress, delays, and scope changes.
- Scenario Simulation - AI can simulate cost outcomes under various assumptions (e.g., reduced labor and supplier delays) to help with financial planning.
AI-based cost prediction eliminates guesswork, gives early warning signals, and improves budget accuracy—particularly useful for long-term or resource-intensive undertakings.
