AILE Environment
The most powerful technology on earth should leave the earth better than it found it. To us, that is not marketing. It is the job.
AI has a real environmental cost. We will not pretend otherwise.
A promise from our founder
I built AILE for people who quietly feel behind on AI, to help people learn about how their life can be made easier. But I can't ask you to lean on AI more and then stay quiet about what it costs. It runs on real electricity and real water, no matter how good we make the app.
So here is what we are actually going to do, in plain terms. Measure the energy and water behind what we build. Cut what we can. Pay to clean up what we can't. And when a number comes back ugly, show you the ugly one, not a rounded-off version.
We're small right now, so our footprint is small right now. I'm writing this down while it barely matters on purpose, because habits are so much easier to keep than to start. I haven't got all of this figured out, and I'm not going to pretend I do. I would just rather be honest with you the whole way than look impressive for a launch. Thank you for caring about our planet with me.
The footprint
The footprint, in the open
Two things are true at once: AI is genuinely useful, and it costs energy and water to run. One prompt is tiny. Across the whole industry it is not: Google reports its emissions 81% above its 2019 baseline, and Microsoft's rose 25% in the last year alone, driven by the data center buildout. Here are real, sourced numbers, then what they mean for AILE.
AI in general
0.24 Wh
Energy for one typical AI prompt
Google's measured median text prompt, about nine seconds of TV, and 33x less energy than a year earlier. Independent estimates land close (Epoch AI, about 0.3 Wh). Long, reasoning, and video prompts cost far more.
Source: Google0.26 mL
On-site water for one typical prompt
Google's measured median, about five drops of cooling water. That counts on-site water only: across US data centers, the water consumed generating their electricity is about 12x what they evaporate on site (Berkeley Lab). The boundary you count is the whole debate.
Source: Google945 TWh
Where data center electricity is headed by 2030
Up from about 415 TWh in 2024, roughly 1.5% of world electricity, heading toward nearly 3% by 2030, about Japan's total use today. AI is the main driver. IEA.
Source: IEA
AILE specifically
Pending
AILE's own monthly AI plus hosting footprint
We have not measured it yet. We publish the figure and method at launch, then update it quarterly.
Estimate, pending verification
100%
Of our measured footprint, our pledge to fund for removal
The commitment, not a current claim. It goes live the moment we launch and start measuring.
Estimate, pending verification
One prompt
What one prompt costs, and what it adds up to
AILE is a learning app, so let us teach this instead of sloganeering. One AI prompt is tiny. Multiply it by how often we all prompt, and it gets real. Both are true. Inside AILE there is a whole free course on this, AI and the Planet, that teaches you to read these numbers, boundaries and all.
- Energy
- 0.24Wh
- Water
- 0.26mL
- Carbon
- 0.03g CO2
In plain terms: Less than nine seconds of watching TV.
How to read this. Based on Google's measured median AI text prompt (0.24 Wh, 0.26 mL on-site water, 0.03 g CO2e), scaled linearly. Medians hide a lot: long, reasoning, and video prompts cost far more, and counting the water and carbon behind the electricity raises every number. This is to build intuition, not to alarm or downplay. Source.
Commitments
Our commitments, with dates
Not vague intentions. A real plan, tied to clear moments, that we report on every quarter, even when the numbers are not flattering.
- Live now
In place now
Reduce first
We cut the footprint at the source before we offset a single gram.
- Pick the smallest model that does the job well, not the biggest by default.
- Cache and reuse results so we are not recomputing the same lesson.
- Right-size compute and run on lower-carbon hosting regions.
- At launch
First measured footprint and removal receipt within 30 days of launch
Measure and clean up what we use
We measure our AI and hosting emissions and fund high-quality removal.
- Estimate emissions from our real usage, with a published method.
- Fund vetted, permanent carbon removal, not the cheapest credits we can find.
- Show the number and the receipts, even when they are small.
- At launch
Before our first dollar of revenue
1% of revenue, pledged
From our first dollar of revenue, 1% goes to environmental nonprofits.
- A formal, audited pledge, not a vague promise.
- It scales honestly: more revenue means more given, automatically.
- Applied from launch, the moment AILE earns anything.
- At launch
Within our first year
Verified restoration
We fund monitored nature restoration, and we call it restoration, not a magic offset.
- A real partner with on-the-ground monitoring, chosen and named at launch.
- Photo and GPS receipts for what our support funds.
- Framed honestly: restoration is good on its own, not a license to pollute.
- Ongoing
Every quarter, in public
Report in the open
We publish an updated footprint and what we funded, even when the numbers are not flattering.
- A standing quarterly update, not a one-time splash.
- Bad quarters get published too.
What we won't do
What we will not do
The fastest way to look like greenwashing is to make claims you cannot back. So here is what we promise to avoid.
- No vague buzzwords like eco-friendly or green AI with nothing behind them.
- No cheap junk offsets bought just to slap carbon neutral on the page.
- No claim we cannot show you a receipt or a source for.
- No hiding bad numbers. We publish updates even when they are not flattering.
A footnote
Even this page has a footprint
This page uses AI-generated imagery, which took energy and water to make, like everything else in AI. We estimate it and cover it the same way we cover the rest: measure, reduce, and fund removal. These images are artistic, not photos of real projects. When we fund real restoration, you will see the real photos.
Receipts
Receipts and cadence
We are early and pre-launch, so this is honest about where things stand. We review and update these commitments every quarter.
Status, as of July 2026
Pre-launch. Reduce and measurement practices are in place now. Offsetting, the 1% pledge, and a restoration partner are chosen, funded, and named here at launch.
Next review: October 2026.
- Carbon removal partner (to be named at launch)Named at launch
- Restoration partner (to be named at launch)Named at launch
- Revenue pledge (to be named at launch)Named at launch
Sources and method
The AI-in-general figures above are published numbers from primary sources, linked below with dates. Boundaries differ between them: on-site versus full supply chain, market-based versus location-based carbon, median versus average. We name the boundary instead of mixing numbers, and where credible sources disagree, we say so. Most of the industry still publishes nothing: ten of thirteen major AI developers disclosed zero environmental data in the 2025 Foundation Model Transparency Index. AILE's own footprint is not measured yet, so we show no made-up number for it. We publish our method and our real figures at launch, then update quarterly.
- Google: Measuring the environmental impact of AI inference (Aug 2025)
- Google: Measuring the Environmental Impact of Delivering AI, research paper (Aug 2025)
- Epoch AI: How much energy does ChatGPT use? (Feb 2025)
- UC Riverside: Making AI Less Thirsty, Ren et al. (2023, Communications of the ACM 2025)
- Berkeley Lab: 2024 United States Data Center Energy Usage Report (Dec 2024)
- IEA: Energy and AI, World Energy Outlook Special Report (Apr 2025)
- Google: 2026 Environmental Report (Jun 2026)
- Microsoft: 2026 Environmental Sustainability Report (Jul 2026)
- Mistral AI: first full lifecycle analysis of a large language model (Jul 2025)
- Masanet et al.: Recalibrating global data center energy-use estimates, Science (2020)
- Stanford CRFM: The 2025 Foundation Model Transparency Index (Dec 2025)
- AILE's own footprint method (published at launch)