The Next Big Business Metric: Measuring Your AI Footprint
The Next Big Business Metric: Measuring Your AI Footprint
Author: Jeff Yurcisin, CEO of Grove
Note: The original version of this blog post first appeared in Fast Company. Amendments have been made to align with Home Planet standards.
At Grove, we’ve always believed that progress shouldn’t come at the planet’s expense. As technology reshapes how we live and work, that belief extends beyond the products we sell — it now includes the tools we use to run our business. Just like shipping a package consumes energy, so does every search, query, or ChatGPT conversation.
Our company was built on transparency and innovation, and we’re now applying the same sustainability lens to emerging technologies like artificial intelligence. In a recent piece for Fast Company, our CEO, Jeff Yurcisin, explores a new kind of sustainability challenge: the environmental cost of AI. Just like we measure carbon emissions from packaging or shipping, it’s time to start measuring the footprint of the technology driving modern business.
Jeff shares how Grove is developing one of the first frameworks to calculate an “AI footprint” and why transparency in innovation matters more than ever.
Read Jeff’s full article below to learn how companies of every size can build a more responsible path forward for people and the planet.
Rethinking solutions to measuring AI
Artificial intelligence is changing everything: how we work, build, create, and grow. It’s unlocking opportunities daily. At Grove Collaborative, we’ve seen it firsthand: AI helps us move faster, make smarter decisions, and, most importantly, serve our customers better.
But here’s the part not enough people are talking about: the environmental cost.
AI is resource-intensive, especially when rolled out at scale. It uses a ton of electricity and water, and drives new forms of e-waste. For mission-driven companies — especially those built on sustainability — that creates a real tension. We want to leverage technology that will allow us to have a greater impact. . But we also want to protect the planet we all share.
So we asked a deceptively simple question: What’s our AI footprint?
The answer: we didn’t know. There was no standard methodology. Just a growing impact no one seemed to be measuring.
A method to estimate AI emissions
Partnering with our longtime friends at Gravity, a carbon and energy accounting platform, we developed a science-informed method for estimating AI emissions — factoring in compute time, server power, and grid emissions. It’s not perfect (no model is). But it’s a practical start that gives us real visibility into the footprint we’re creating.
Our projected 2025 AI-related carbon footprint is 17.8 metric tons of CO2e, which is about the same as taking 40 round-trip flights from San Francisco to New York City. This is a first estimate based on our current usage today, but we know this number will grow. And having a baseline is essential to understand our impact so that we can explore how to reduce it over time.
During NYC Climate Week, we became one of the first retailers to disclose estimated AI emissions. And beginning in 2026, we’ll include them in our annual sustainability reporting.
But this can’t just be about us. Which is why we’re open-sourcing the methodology. Any company, whether a startup or multinational, can — and should — use it to measure and track their AI footprint. Because the speed of AI adoption is outpacing our ability to measure its impact. Without transparency, there’s no path to making AI both powerful and sustainable.
This isn’t about slowing innovation. It’s about making sure innovation and sustainability move forward together — not in opposition.
4 ways to measure your brand’s AI footprint
Here’s the playbook we’re proposing for measuring your AI footprint:
Measure what matters. Don’t guess. Track AI emissions with as much granularity as current science allows, and include it in your entire carbon footprint..
Mitigate with integrity. Offset what you can’t reduce — but don’t stop there. Balance AI emissions with high-quality carbon offsets and, based on your measurement, invest in strategies to reduce them over time.
Choose more sustainable models. Favor AI platforms that share environmental data, prioritize efficiency and water stewardship, and embrace circular design.
Lead through disclosure. Perfect measurement doesn’t exist. But transparency builds trust and drives momentum.
Of course, this only works if the upstream providers — the companies building the AI infrastructure itself — step up too. We’re calling on LLM developers to disclose their tools’ environmental impact. Without their transparency, no one can truly measure with accuracy.
Leading with transparency
We know we’re early. We don’t have all the answers. But we believe in leading with openness, not waiting for perfect data, and driving progress over perfection. Our mission at Grove has always been to create healthier homes and a healthier planet. That mission doesn’t end with AI, but it does have to evolve to include it.
Our current AI emissions are modest. But even small footprints matter. And if we don’t measure them, they’ll grow unchecked.
So here’s the challenge I’ll leave with my peers: don’t let sustainability lag behind innovation. Measure your impact. Share your findings. Hold yourself accountable.
The future of innovation isn’t just faster. It’s more responsible, more transparent, more human. That’s how we make real progress — and make sure it lasts.
