AI Project Controls & Risk Forecasting

Machine learning models trained on historical project data can identify leading indicators of risk (RFI velocity, change-order patterns, procurement slippage, productivity variance). The goal is not perfect prediction, but earlier intervention: re-sequencing work, accelerating procurement, or renegotiating scope before impacts compound.