As operational energy efficiency improves, embodied carbon becomes a larger share of a building's total carbon footprint. For a high-performance building, embodied carbon can represent 50% or more of lifetime emissions. Yet most architects lack the time and tools to analyze embodied carbon systematically. AI changes this equation.
Comparative Material Analysis
AI can rapidly compare alternative material assemblies:
"Compare these three structural systems for a 4-story, 40,000 SF office building: Option A: Steel frame with composite metal deck Option B: Cast-in-place concrete frame with post-tensioned slabs Option C: Mass timber (CLT floors, glulam beams and columns) with concrete podium
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What you'll learn:
- Use AI to compare material assemblies by embodied carbon, cost, and performance
- Evaluate Environmental Product Declarations (EPDs) using AI-assisted analysis
- Make data-driven material substitutions that reduce embodied carbon without compromising performance