Q&A: UL Solutions Experts Offer Insights on Managing AI’s Footprint in a Carbon-Constrained World

Key Points

• Dr. Anastasia Behr and Dr. Young Lee of UL Solutions have written an article offering insights on how AI is increasing energy demand and shaping sustainability considerations.
• The article in POWER magazine discusses high electricity consumption in data centers, and it examines how AI's environmental footprint goes beyond energy use.
• The authors make observations about efficiency, sustainability, responsible AI growth and the importance of a full-system perspective.

In a recent POWER magazine article, two UL Solutions experts - Dr. Anastasia Behr, senior director, Sustainability Science and Technologies, and Dr. Young Lee, principal engineer, Artificial Intelligence - explore how the rapid growth of AI is increasing energy demand and shaping sustainability considerations. The article answers these key questions:

Why is AI driving increased energy demand?
AI technologies require significant computing power for both training and everyday use. As adoption grows across industries, data centers and supporting infrastructure are consuming increasing amounts of electricity.

What are the environmental impacts of AI?
In addition to electricity use, AI systems require cooling and specialized hardware, contributing to water use, resource extraction and electronic waste. These impacts extend across the full life cycle of AI systems.

Why aren't efficiency improvements enough to address AI's footprint?
Even as systems become more efficient, overall demand continues to rise as AI becomes more widely used. This effect can increase total energy consumption despite gains at the individual system level.

Why is a broader, system-level view important?
Understanding AI's impact requires looking beyond individual technologies to consider energy sources, infrastructure and life cycle effects. This perspective helps identify where meaningful reductions can be achieved.

What role does measurement play in managing AI's impact?
Clear and consistent ways to measure energy use and emissions are essential. Improved visibility allows organizations to make informed decisions and track progress toward sustainability goals.

How can organizations support more sustainable AI growth?
Efforts to reduce AI's footprint include improving reporting practices, advancing lower carbon energy systems and strengthening collaboration across industries to develop shared approaches.

Where can I learn more?
Read the full article in POWER magazine: Managing AI's Footprint in a Carbon-Constrained World

More information about how UL Solutions helps companies navigate complex regulatory and voluntary commitments to reduce carbon impact is available at the Life Cycle Assessment Services page at UL.com.