OpenAI CEO Sam Altman is pushing back against environmental concerns about artificial intelligence, asserting that the water consumption of 38,000 ChatGPT queries is equivalent to the water required to grow a single California almond. Speaking on the Sources podcast with tech journalist Alex Heath, Altman acknowledged the metric was recalled from memory and could vary slightly, but maintained it accurately reflects the minimal real-world water usage of modern AI workloads compared to common agricultural practices.

Why Is AI Water Consumption Such a Hot Topic?

As artificial intelligence systems scale globally, concerns about their environmental footprint have intensified. Data centers that power AI models like ChatGPT require significant cooling infrastructure, and water is a critical component of that cooling process. Critics worry that as AI adoption accelerates, the cumulative water demand could strain already-stressed water supplies, particularly in regions like California that face chronic drought conditions. Altman's comments suggest the industry believes these concerns are overblown.

Altman argued that widely circulated concerns regarding data center water intensity rely on outdated cooling infrastructure and fail to reflect modern facility design. He noted that contemporary hyperscale data centers operate with closed-loop systems that require water volumes comparable to standard commercial office buildings for everyday plumbing. The OpenAI chief described popular perceptions of high per-query water consumption as empirically flawed and resistant to public correction, pointing to internal baseline estimates that place an average ChatGPT prompt's direct water footprint at approximately 0.32 milliliters, or about 0.000085 gallons.

What Do Environmental Researchers Say About These Claims?

Environmental researchers and policy experts caution that precise calculations remain difficult due to a lack of standardized corporate disclosures regarding cooling mechanisms, regional water sources, and indirectly consumed power grid water. The debate has gained regulatory momentum in California, where state lawmakers are considering transparency measures to mandate detailed data center utility reporting.

In response to heightened environmental scrutiny, major cloud providers have highlighted efficiency gains. Amazon reported a 2 percent decline in global data center water usage to 2.5 billion gallons in 2025, and Microsoft cited up to a 90 percent water-efficiency improvement over its legacy facilities. These numbers suggest the industry is moving toward more sustainable practices, though questions remain about whether improvements are keeping pace with AI's explosive growth.

How to Evaluate AI Environmental Impact Claims

• Request Detailed Disclosures: Ask companies for specific data on cooling mechanisms, water sources (recycled versus freshwater), and regional water stress factors rather than accepting aggregate statistics.
• Compare Apples to Apples: When companies cite efficiency improvements, verify whether they are comparing new facilities to legacy systems or measuring absolute water consumption versus per-unit metrics.
• Consider Indirect Water Use: Evaluate not just direct cooling water but also the water consumed by power plants that generate electricity for data centers, which can be substantial.
• Monitor Regulatory Developments: Track state and federal transparency mandates, as these will likely force more standardized and verifiable environmental reporting from tech companies.

The disagreement between Altman and environmental experts highlights a broader tension in the AI industry. While companies like OpenAI argue their operations are efficient and their environmental impact is minimal, independent researchers point out that without standardized reporting and third-party verification, it is difficult to assess the true scale of AI's water footprint. California's push for transparency measures suggests regulators are taking these concerns seriously, even if industry leaders downplay them.

Altman's almond comparison is memorable but also illustrative of how the debate often hinges on framing. A single query using 0.32 milliliters of water sounds trivial; 38,000 queries using the equivalent of one almond's worth of water also sounds reasonable. But with billions of ChatGPT queries running daily across the globe, the cumulative impact becomes harder to dismiss. The real question is not whether individual queries consume significant water, but whether the aggregate demand from AI systems will strain water supplies in water-stressed regions.

As AI infrastructure continues to expand, the conversation around environmental impact will likely intensify. Altman's public comments suggest OpenAI is confident in its efficiency metrics, but the company's willingness to engage with the debate, even defensively, indicates that environmental concerns are no longer a fringe issue in Silicon Valley. Whether his reassurances satisfy regulators and environmental advocates remains to be seen.