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rtificial intelligence and machine-learning algorithms have struggled to make sense of chaotic construction jobsites, but recent years have seen industry firms build the vast data lakes and analytics systems necessary for these machines to provide useful advice on how to plan, schedule and execute projects. In some cases, these AI advisors have become a standard part of some firms’ project delivery methods. But it’s still a challenge to convince construction professionals to listen to these AI advisors, and there are emerging questions of how risk will be allocated once algorithm-driven decisions start to steer projects.