This session moves past the noise and shows what artificial intelligence actually does on a construction and infrastructure operation today. Drawing on real deployments, it demonstrates how AI agents and advanced analytics are already being used to report and investigate incidents, build risk matrices, calculate risk, and guide site teams and contractors through the decisions that keep people safe.

The argument at its center is simple: the value depends far less on any single tool than on what comes before it — digitalization and data quality, without which no algorithm can work, and a sustainable architecture built around organizational structure, legislation, legacy systems, processes, and people. Construction remains one of the least digitized sectors in the world; this session shows what closing that gap actually looks like in practice.

Learning Objectives:

●      Understand why digitalization and data quality must come before any AI tool — and how to work backward from the decisions that matter to capture the right data from the start.

●      Recognize why sustainable architecture (organizational structure, legislation, legacy systems, processes, and people) determines AI success far more than isolated pilots or general-purpose tools.

●      Examine real-world safety use cases — contractor management, incident and behavioral-observation reporting, and critical risk and fatality prevention — powered by AI agents.

●      Evaluate advanced analytics in action: predictive risk calculation, scoring, and recommendations that guide site-level decisions.