Watershed Guide
AI emissions: A practical guide for corporate sustainability leaders
AI is the fastest-growing driver of electricity demand—and most sustainability teams don't yet have a plan for it. Only one in four companies currently report AI-related emissions, even as enterprise adoption accelerates.
This guide breaks down what sustainability leaders need to know about AI emissions: where they come from, why they matter, and what you can do about them today.
Built with input from Watershed's climate and data science teams, it gives you a practical framework for evaluating AI's footprint, making smarter procurement decisions, and setting internal efficiency standards.
What you'll learn:
- Where AI emissions actually come from—and why inference, not training, drives more than 90% of lifecycle impact.
- How to evaluate AI vendors and cloud regions—choosing lower-carbon regions can cut operational emissions by 30–80%.
- How to track and reduce AI emissions while global accounting standards evolve.
- Why purpose-built sustainability AI can accelerate decarbonization across your program.
Bonus: The guide includes a one-page brief for internal comms—designed to help you build alignment on AI's environmental impact across your organization.
A: It's not binary. Per-query emissions are relatively small, but AI is the fastest-growing driver of electricity demand, and that demand is currently being met largely by fossil fuels. The risk isn't any single query; it's the grid trajectory at scale. AI can also be used to accelerate sustainability efforts.
