A ‘thirsty’ generative AI boom poses a growing problem for Big Tech
Dubai, UNITED ARAB EMIRATES — A global rush for the next wave of generative artificial intelligence is increasing public scrutiny on an often-overlooked but critically important environmental issue: Big Tech’s expanding water footprint.
Tech giants, including the likes of Microsoft and Alphabet-owned Google, have recently reported a substantial upswing in their water consumption and researchers say one of the main culprits is the race to capitalize on the next wave of AI.
Shaolei Ren, a researcher at the University of California, Riverside, published a study in April investigating the resources needed to run buzzy generative AI models, such as OpenAI’s ChatGPT.
Ren and his colleagues found that ChatGPT gulps 500 milliliters of water (roughly the amount of water in a standard 16-ounce bottle) for every 10 to 50 prompts, depending on when and where the AI model is deployed.
Hundreds of millions of monthly users all submitting questions on the popular chatbot quickly illustrates just how “thirsty” AI models can be.
The study’s authors warned that if the growing water footprint of AI models is not sufficiently addressed, the issue could become a major roadblock to the socially responsible and sustainable use of AI in the future.
People take part in a protest called by Uruguay’s Central Union (PIT-CNT) in “defense of water” against the handling of the national authorities with respect to the management of the shortage of drinking water reserves in Montevideo on May 31, 2023.
Eitan Abramovich | Afp | Getty Images
ChatGPT creator OpenAI, part owned by Microsoft, did not respond to a request to comment on the study’s findings.
“In general, the public is getting more knowledgeable and aware of the water issue and if they learn that the Big Tech’s are taking away their water resources and they are not getting enough water, nobody will like it,” Ren told CNBC via videoconference.
“I think we are going to see more clashes over the water usage in the coming years as well, so this type of risk will have to be taken care of by the companies,” he added.
‘A hidden cost’
Data centers are part of the lifeblood of Big Tech — and a lot of water is required to keep the power-hungry servers cool and running smoothly.
For Meta, its these warehouse-scale data centers that generate not only the highest percentage of its water use but also the lion’s share of its energy use and greenhouse gas emissions.
In July, protesters took to the streets of Uruguay’s capital to push back against Google’s plan to build a data center. The proposal sought to use vast quantities of water at a time when the South American country was suffering its worst drought in 74 years.
Google reportedly said at the time the project was still at an exploratory phase and stressed that sustainability remained at the heart of its mission.
With AI, we’re seeing the classic problem with technology in that you have efficiency gains but then you have rebound effects with more energy and more resources being used.
Somya Joshi
Head of division: global agendas, climate and systems at SEI
In Microsoft’s latest environmental sustainability report, the U.S. tech company disclosed that its global water consumption rose by more than a third from 2021 to 2022, climbing to nearly 1.7 billion gallons.
It means that Microsoft’s annual water use would be enough to fill more than 2,500 Olympic-sized swimming pools.
For Google, meanwhile, total water consumption at its data centers and offices came in at 5.6 billion gallons in 2022, a 21% increase on the year before.
Both companies are working to reduce their water footprint and become “water positive” by the end of the decade, meaning that they aim to replenish more water than they use.
It’s notable, however, that their latest water consumption figures were disclosed before the launch of their own respective ChatGPT competitors. The computing power needed to run Microsoft’s Bing Chat and Google Bard could mean significantly higher levels of water use over the coming months.
“With AI, we’re seeing the classic problem with technology in that you have efficiency gains but then you have rebound effects with more energy and more resources being used,” said Somya Joshi, head of division: global agendas, climate and systems at the Stockholm Environment Institute.
“And when it comes to water, we’re seeing an exponential rise in water use just for supplying cooling to some of the machines that are needed, like heavy computation servers, and large-language models using larger and larger amounts of data,” Joshi told CNBC during the COP28 climate summit in the United Arab Emirates.
“So, on one hand, companies are promising to their customers more efficient models … but this comes with a hidden cost when it comes to energy, carbon and water,” she added.
How are tech firms reducing their water footprint?
A spokesperson for Microsoft told CNBC that the company is investing in research to measure the energy and water use and carbon impact of AI, while working on ways to make large systems more efficient.
“AI will be a powerful tool for advancing sustainability solutions, but we need a plentiful clean energy supply globally to power this new technology, which has increased consumption demands,” a spokesperson for Microsoft told CNBC via email.
“We will continue to monitor our emissions, accelerate progress while increasing our use of clean energy to power datacenters, purchasing renewable energy, and other efforts to meet our sustainability goals of being carbon negative, water positive and zero waste by 2030,” they added.
Aerial view of the proposed site of the Meta Platforms Inc. data center outside Talavera de la Reina, Spain, on Monday, July 17, 2023. Meta is planning to build a 1 billion ($1.1 billion) data center which it expects to use about 665 million liters (176 million gallons) of water a year, and up to 195 liters per second during “peak water flow,” according to a technical report.
Paul Hanna | Bloomberg | Getty Images
Separately, a Google spokesperson told CNBC that research shows that while AI computing demand has dramatically increased, the energy needed to power this technology is rising “at a much slower rate than many forecasts have predicted.”
“We are using tested practices to reduce the carbon footprint of workloads by large margins; together these principles can reduce the energy of training a model by up to 100x and emissions by up to 1000x,” the spokesperson said.
“Google data centers are designed, built and operated to maximize efficiency – compared with five years ago, Google now delivers around 5X as much computing power with the same amount of electrical power,” they continued.
“To support the next generation of fundamental advances in AI, our latest TPU v4 [supercomputer] is proven to be one of the fastest, most efficient, and most sustainable ML [machine leanring] infrastructure hubs in the world.”
The VC arms of Google and Nvidia have invested in Swedish vibe coding startup Lovable’s $330 million Series B at a $6.6 billion valuation, the company announced on Thursday.
The news confirms an earlier story from CNBC, which reported on Tuesday that Lovable had raised at that valuation, trebling its valuation from its previous round in July, and that the investors included U.S. VC firms Accel and Khosla Ventures.
CapitalG, one of Google’s VC divisions, and Menlo Ventures led the round. Alongside Accel and Khosla, Nvidia venture arm NVentures, actor Gwyneth Paltrow’s VC firm Kinship Ventures, Salesforce Ventures, Databricks Ventures, Atlassian Ventures, T.Capital, Hubspot Ventures, DST Global, EQT Global, Creandum and Evantic also participated.
The fresh funds take Lovable’s total raised in 2025 to over $500 million.
“Lovable has done something rare: built a product that enterprises and founders both love,” said Laela Sturdy, managing partner at CapitalG in a statement accompanying the announcement.
“The demand we’re seeing from Fortune 500 companies signals a fundamental shift in how software gets built.”
Lovable’s platform uses AI models from providers like OpenAI and Anthropic to help users build apps and websites using text prompts, without technical knowledge of coding.
The startup reported $200 million in annual recurring revenue (ARR) in November, just under a year after achieving $1 million in ARR for the first time. It was founded in 2023 by Anton Osika and Fabian Hedin.
Vibe coding startups have seen big interest from VCs in recent times, as investors bet on their promise of drastically reducing the time it takes to create software and apps.
In the U.S., Anysphere, which created coding tool Cursor, raised $2.3 billion at a $29.3 billion valuation in November. In September, Replit hit a $3 billion price tag after picking up $250 million and Vercel closed a $300 million round at a $9.3 billion valuation.
The Micron logo is seen displayed at the 8th China International Import Expo.
Sheldon Cooper | Lightrocket | Getty Images
Micron Technology‘s stock jumped 15% after the company signaled robust demand for its memory chips and blew away fiscal first-quarter estimates.
During an earnings call with analysts, Micron, which makes memory storage used for computers and artificial intelligence servers, said data center needs have fueled greater demand for its products.
Micron said it expects the total addressable market for high-bandwidth memory to hit $100 billion by 2028, growing at a 40% compounded annual growth rate. Management also upped its capital expenditures guidance to $20 billion from $18 billion.
“We are more than sold out,” said business chief Sumit Sadana. “We have a significant amount of unmet demand in our models and this is just consistent with an environment where the demand is substantially higher than supply for the foreseeable future.
Micron topped Wall Street estimates for the fiscal first quarter and issued blowout guidance.
The company reported adjusted earnings of $4.78 per share on $13.64 billion in revenue, surpassing LSEG estimates for earnings of $3.95 per share and $12.84 billion in sales.
Revenues in the current quarter are expected to hit about $18.70 billion, blowing past the $14.20 billion expected by LSEG. Adjusted earnings are forecast to reach $8.42, versus expectations of $4.78 per share.
JPMorgan upped its price target on the stock following the results, citing the favorable pricing setup, while Bank of America upgraded shares to a buy rating.
Morgan Stanley called the results the best revenue and net income upside in the “history of the U.S. semis industry” outside of Nvidia.
“If AI keeps growing as we expect, we believe that the next 12 months are going to have broader coat tails to the AI trade than just the processor names and memory would be the biggest beneficiary,” analysts wrote.
WATCH: Micron shares spike on better-than-expected quarterly results
Micron year-to-date stock chart.
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