XAI-enabled probabilistic pipeline for predicting delay and cost overrun risk in construction

Purpose We develop an uncertainty-aware, Explainable Artificial Intelligence (XAI)-enabled probabilistic framework to predict and explain delay-driven cost risk in construction, accounting for time-varying exposures driven by supply reliability, regulatory cadence and labor stability. Design/methodology/approach Using data from 46 US high-rise projects, we estimate a hierarchical competing-risks Weibull survival model with time-varying covariates and project-level random effects via HMC/NUTS. We link posterior predictive delay exceedance to a stochastic cost overrun layer and integrate XAI through posterior-aware SHAP (global and local importances with 95% credible bands), interaction effects, and counterfactual recourse. Decision-curve analysis quantifies net benefit across operational trigger thresholds. Findings Relative to non-XAI baselines, the approach improves time-to-event discrimination and calibration (e.g. median C-index 0.81 vs 0.73; IBS reduction −0.027; both with 95% credible intervals). Global explanations identify supply reliability as the dominant driver, with a positive supply-regulation interaction. Scenario analyses show median reductions of 11–20% in cost overruns under feasible interventions (e.g. reliability uplift and buffer policies), with uncertainty reported. Practical implications The suggested framework provides a clear and interpretable information to the project managers both locally and globally. It recognizes the actual counterfactual activities that are associated with procurement scheduling and vertical logistics, it determines the decision-thresholds whose anticipated benefits are clearly outlined. All these characteristics allow more active, transparent and evidence-based management of complex project risks. Originality/value As far as we can determine, this paper is the first attempt to integrate hierarchical competing-risks Weibull modeling with uncertainty-aware explainable AI and a structural interdependence between schedule delay and cost escalation in a high-rise construction. The result is an interpretable, more practically oriented decision-support system that converts the findings of the analysis into practical directions to managers.