More or Less Podcast: "How much water does AI consume?"
BBC Radio 4 | Host: Charlotte MacDonald | Date: March 28, 2026
Episode Focus:
A deep dive into the startling claims about the amount of fresh water consumed by Artificial Intelligence (AI)—and an investigation into what the numbers really mean for the environment and for the future.
Episode Overview
This episode explores how much water AI truly uses globally and untangles some commonly misreported statistics about AI’s water consumption. With the rapid expansion of AI and large language models, public concern has grown over the “invisible” resources required to power and cool AI data centers. The presenters scrutinize alarming figures reported in the media, trace their origins and accuracy, and ask: should we be worried about AI’s thirst for water?
Key Discussion Points & Insights
1. The Origins of Alarming Water Consumption Figures
- Initial Claim:
- Karen Howe in "Empire of AI" writes: AI could consume 1.1 trillion to 1.7 trillion gallons of fresh water yearly by 2027—“half the water annually consumed in the UK” (04:10).
- Conversion: This equals 4.2 to 6.6 trillion liters.
- Issue Highlighted:
- The distinction between water CONSUMED (not returned to the system) vs water WITHDRAWN (temporarily used, some returned afterward).
2. Debunking the Numbers: Consumption vs. Withdrawal
- Nathan Gower explains:
- The 4 to 6 trillion liter figure incorrectly refers to withdrawal, not consumption.
- “So Howe got her figures from a paper…those figures…aren’t for water consumption. They’re…for…water withdrawal.” (03:40)
- Correction:
- Real consumption is only 10% of that: 380 to 600 billion liters per year (04:23).
Notable Quote:
“So the author's stuck the wrong label on the 4 to 6 trillion litre figure. It should be for withdrawal, not consumption.”
— Charlotte MacDonald [04:12]
3. Digging Deeper: Flawed Research Chain
- Underlying Source Issue:
- The original paper used an estimate from researcher Alex de Vries Gao.
- That estimate was not for all AI servers in use, only for those built in 2027.
- Effect:
- Massive underestimation of total electricity use (05:32), leading to flawed water figures.
Notable Quote:
“It’s a bit of a mess.”
— Nathan Gower [05:52]
4. Estimating Actual AI Water Consumption
- Alex de Vries Gao’s Methodology:
- Traced number of AI chips produced, server modules, then actual servers.
- Looked at utilization rates and water used per unit of power (06:13).
Notable Quote:
“I tried to look at the biggest buyers…like Microsoft, Google…how do these companies’ data centers perform in terms of water intensity…used those numbers to translate my power demand estimate into…water consumption estimate.”
— Alex de Vries Gao [06:13]
- Key Figure:
- By late 2025, AI systems were consuming about 750 billion liters of water per year (07:14).
- That’s more than global bottled water consumption (446 billion liters).
Memorable Explanation:
“This is exceeding the level of global bottled water consumption…It could cause a lot of problems if this consumption is concentrated in a single location…But we just don’t know at this time.”
— Alex de Vries Gao [07:30]
5. Where Does the Water Go?
- 90% of AI’s water consumption happens off-site at power stations (from rivers/lakes).
- 10% happens on-site in data centres, often using drinking water (08:26).
- Water Consumption vs. Withdrawal Debate:
- Some experts argue water withdrawal, even if mostly returned, can still impact ecosystems and local supplies.
6. Predicting the Future
- Bottleneck:
- Can tech companies find the power (and water) needed for relentless AI growth?
- Unknowns:
- Future supply chains make precise projections speculative.
- Local impacts may be severe, but global numbers don’t give the full picture (09:53).
Notable Quote:
“This is still going to be adding on top…But again, I can’t say anything about whether it’s going to be possible to find a home for all this equipment.”
— Alex de Vries Gao [09:06]
Timestamps of Important Segments
- 01:16 — Intro, framing the environmental question around AI’s “invisible” resource use.
- 03:05 — Defining water consumption vs. withdrawal.
- 04:23 — Actual water consumption figures clarified.
- 05:40 — How academic errors propagate through media.
- 06:13 — Alex de Vries Gao describes his methodology.
- 07:14 — Staggering “750 billion liter” figure revealed.
- 08:26 — On-site vs. off-site water use explained.
- 09:06 — Challenges in making future predictions.
Notable Quotes & Memorable Moments
- Charlotte MacDonald [04:12]:
“So the author's stuck the wrong label on the 4 to 6 trillion litre figure. It should be for withdrawal, not consumption.”
- Nathan Gower [05:52]:
“It’s a bit of a mess.”
- Alex de Vries Gao [07:30]:
“This is exceeding the level of global bottled water consumption... It could cause a lot of problems if this consumption is concentrated in a single location... But we just don’t know at this time.”
- Alex de Vries Gao [09:06]:
“I can make statements based on…hardware, which…means…the cumulative power demand of AI systems is still going to be rising. This is still going to be adding on top... But again, I can’t say anything about whether it’s going to be possible to find a home for all this equipment.”
Summary Table
| Concept/Statistic | Flawed Figure | Correct Figure | Notable Detail | |:------------------------------------|:----------------------------|:----------------------|:-------------------------------------------------| | Global AI Water “Consumption” (2027)| 4.2–6.6 trillion liters | 380–600 billion liters| Error: Figure was for withdrawal, not consumption| | Actual 2025 AI Water Use | N/A | 750 billion liters | Exceeds global bottled water consumption | | % On-site (data center) | N/A | 10% | Mostly uses drinking water | | % Off-site (power stations) | N/A | 90% | Uses rivers & lakes; location matters |
Conclusion
This episode neatly unravels how a startling statistic—AI will soon “consume half the UK’s water”—got inflated through a series of academic and journalistic misinterpretations. The true figure is dramatically lower (but still significant), centering debate on what metrics (consumption vs withdrawal) truly matter for the environment. The episode closes with uncertainty about AI’s future water demands and location-specific risks, reminding listeners that “huge” global numbers are only part of the story.
