Sam Altman, CEO of OpenAI, has pushed back strongly against growing concerns about artificial intelligence’s resource consumption, dismissing claims that ChatGPT uses gallons of water per query as “completely untrue” and “totally insane.”

Speaking on the sidelines of the India AI Impact Summit in an interview with The Indian Express, Altman addressed mounting criticism around the environmental cost of large-scale AI systems, particularly their energy and water usage.

His remarks come at a time when scrutiny of AI infrastructure — especially data centers — is intensifying worldwide.

“No Connection to Reality”: Altman on Water Usage Claims

One of the most widely circulated criticisms online is that each ChatGPT query consumes several gallons of water due to cooling requirements in data centers.

Altman rejected those claims outright.

He described them as having “no connection to reality,” arguing that viral estimates significantly exaggerate how much water is tied to individual AI queries.

Data centers do use water for cooling in some regions, but experts note that usage varies depending on location, cooling systems, and energy sources. The debate has often centered around how to fairly attribute shared infrastructure consumption to individual AI interactions.

Altman’s comments signal frustration with what he sees as misleading or oversimplified narratives around AI’s environmental footprint.

AI Energy Use Is Rising — But So Is Human Consumption

While dismissing the water claims, Altman acknowledged that overall energy use tied to AI systems is increasing.

However, he framed the issue in a broader context.

According to Altman, humans also consume energy to perform tasks — whether it’s driving to work, powering offices, or running personal devices. AI, he suggested, should be viewed similarly: as a tool that requires energy to operate, but one that can also improve efficiency and productivity.

His argument centers on comparison rather than denial. AI systems consume electricity, but so do the traditional processes they may replace.

The Growing AI Infrastructure Debate

As AI adoption accelerates, so does the demand for large-scale computing infrastructure.

Modern AI models rely on:

• Massive data centers
• High-performance GPUs
• Continuous cloud processing
• Advanced cooling systems

This infrastructure consumes significant electricity. In some regions, water-based cooling systems are also used to maintain safe operating temperatures.

Critics argue that as AI models grow more complex, their environmental footprint could become unsustainable without rapid investment in renewable energy.

Supporters counter that AI can help optimize energy grids, reduce inefficiencies in industries, and accelerate climate research — potentially offsetting its own footprint.

Altman’s Call for Cleaner Power

Importantly, Altman did not dismiss concerns about energy entirely. He acknowledged that total AI energy consumption is rising and emphasized the need for cleaner power sources.

He has previously spoken about the importance of advancing nuclear energy, renewables, and other sustainable power technologies to support AI’s growth responsibly.

The core of his position appears to be this: the solution is not to slow AI development, but to accelerate the transition to clean energy infrastructure.

A Broader Narrative Battle Around AI

Altman’s remarks reflect a larger conversation taking place globally. Artificial intelligence is rapidly becoming embedded in everything from education and healthcare to enterprise software and government services.

As adoption expands, so does public scrutiny.

Common concerns include:

• Environmental impact
• Job displacement
• Data privacy
• Ethical decision-making

The environmental angle, particularly water and electricity use, has gained traction on social media, sometimes accompanied by viral but disputed statistics.

By publicly challenging those figures, Altman is attempting to reframe the conversation around measurable data and long-term solutions.

AI’s Efficiency Argument

One of the strongest counterarguments from AI advocates is efficiency.

For example, AI tools can:

• Automate repetitive office tasks
• Optimize logistics and transportation
• Improve manufacturing processes
• Reduce waste in supply chains

If AI reduces the need for physical travel, paper-based systems, or inefficient operations, its net energy impact could be more balanced than critics assume.

The debate, therefore, is not simply about how much energy AI consumes — but whether the benefits outweigh the costs.

The Road Ahead

As governments and regulators examine AI more closely, transparency around energy and water usage is likely to become increasingly important.

Companies building large AI systems may face growing pressure to:

• Disclose environmental metrics
• Invest in renewable energy
• Improve data center efficiency
• Develop less resource-intensive models

Altman’s comments suggest that OpenAI intends to defend its position vigorously while acknowledging the broader need for cleaner infrastructure.

Sam Altman has drawn a firm line against claims that ChatGPT consumes gallons of water per query, calling such assertions “fake” and disconnected from reality. At the same time, he recognizes that AI’s overall energy demands are rising — and argues that cleaner power, not slower innovation, is the answer.

As AI becomes more central to the global economy, the conversation around its environmental footprint is unlikely to fade. The real question may not be whether AI uses energy — but how responsibly that energy is produced and managed.