The Hidden Footprint of Building Intelligence: Measuring AI’s Environmental Impact Before We Scale

Explain why AI adoption in the built environment should be evaluated for both benefits and environmental footprint.

Identify major contributors to AI’s footprint, including model size, inference demand, hardware, cloud/data center location, energy, and water.

Describe how AECO teams and owners can ask better procurement and transparency questions before adopting AI-enabled tools.

Apply a net-positive impact lens to determine when AI is appropriate, right-sized, or potentially overused in high-performance building workflows.