Google’s latest paper on measuring the environmental impact of AI at…

Google’s latest paper on measuring the environmental impact of AI at scale is an important step forward. It’s the first time we’re seeing production-grade reporting of Gemini Apps serving metrics—and credit to Google for bringing this transparency to the industry.

The numbers stand out:
0.24 Wh of energy per prompt
0.03 g CO₂e per prompt
0.26 mL of water (about five drops)

On their own, these impacts seem tiny. But scale changes everything. If AI prompts begin to replace traditional search queries, we’re looking at at least 1 billion prompts per day. That translates to 240 MWh of energy, 30 tons of CO₂, and 260,000 liters of water daily. At full search scale (~14 billion queries daily), the footprint becomes grid-level and industrial in magnitude.

And that’s just for text prompts. As usage shifts toward multimodal prompts—text-to-image, text-to-video, and more—the per-request footprint will be significantly higher. Add in Agentic AI workflows, where multiple models, tools, retrieval calls, and reasoning loops are orchestrated for a single outcome, and the cumulative impact grows even further.

While the report focused on text prompts, it showed a 33× reduction in energy and a 44× reduction in emissions over one year—a reminder of how important continued efficiency gains will be as AI expands into more resource-intensive multimodal and agentic use cases.

Check out the technical paper here: https://lnkd.in/djFw265T

One point to note: the report presents market-based emissions, which credit clean energy procurement. It would be equally valuable to see location-based emissions, reflecting the actual grid mix where workloads run.

Google’s broader Carbon Footprint tools already show both market-based and location-based emissions side by side. Extending that same dual reporting to AI serving would provide even more clarity and comparability for the ecosystem.

While providers will continue to improve efficiency at the infrastructure and software/model level, it is equally important to design applications in a lean way—minimizing cost, carbon, and complexity, improving energy efficiency, and playing our part. That’s the mindset I explore in detail in my book: leanagenticai.com

#google Green Software Foundation #sustainability