AI for CM at Risk Projects
How AI supports construction management at risk project delivery.
Definition
AI for CM at Risk projects supports the preconstruction and construction management approach. AI can help with early cost feedback, GMP development, subcontractor management, and risk identification. AI-powered CM at Risk delivery improves cost certainty and project outcomes.
In Depth
Construction Management at Risk (CM at Risk) places the construction manager in the project early, during design, with a Guaranteed Maximum Price (GMP) responsibility. AI supports the CM at Risk delivery method by enabling the cost-informed design decisions that are the core value proposition of early CM involvement.
During preconstruction, the CM at Risk uses AI to provide real-time cost feedback on design options. As the architect develops the design, AI estimates the cost implications of each major decision — structural system selection, facade type, mechanical system approach — using historical cost data and current market pricing. This enables the team to make cost-informed design decisions early, rather than discovering during the GMP estimate that the design exceeds the budget.
Examples
Developing GMP estimates
Managing subcontractor scope
Tracking preconstruction deliverables
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Frequently Asked Questions
AI for CM at Risk projects supports the preconstruction and construction management approach. AI can help with early cost feedback, GMP development, subcontractor management, and risk identification. AI-powered CM at Risk delivery improves cost certainty and project outcomes.
Developing GMP estimates. Managing subcontractor scope. Tracking preconstruction deliverables.
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