AI Will Reshape Everything — But Who’s Powering It?

Why the Future of Artificial Intelligence Depends on the Future of Energy

Author

RegenBrief.com Editor
June 24, 2025

“We do need energy breakthroughs. We’ll need way more power than we currently have, by a lot. I think we still don’t appreciate the energy needs of this technology.”

— Sam Altman, 2024 interview with Lex Fridman
The real challenge isn’t AI — it’s the infrastructure beneath it.
We’re scaling intelligence at an unprecedented pace. But without matching that with clean, resilient energy systems, we risk building our future on an outdated, fossil-fueled foundation.
AI can drive climate solutions, efficiency, and better decision-making — but only if the energy behind it is as smart as the models themselves.


The Compute Boom Has an Energy Problem

Artificial Intelligence is accelerating global progress — from scientific discovery to productivity, education, and climate modeling.

But this intelligence surge runs on real infrastructure — and energy is its fuel.

  • Training a large AI model like GPT-4 is estimated to use as much electricity as 300 U.S. homes consume in a year.

  • Ongoing daily use of ChatGPT is estimated to draw more electricity than 100,000 U.S. homes.

  • The IEA projects that data centers could consume up to 6–8% of global electricity by 2030, driven largely by AI and digital infrastructure expansion.

AI itself isn’t the problem — the issue is how it’s being scaled:
Fast. Globally. And mostly on fossil-fueled grids.

AI needs
energy alignment, now!

We’re embedding AI across every sector — but few leaders are asking the most critical question:
“What powers the intelligence we’re scaling?”

Here’s what’s being overlooked:

  • AI workloads often default to non-renewable grids in regions with the cheapest power

  • AI data centers use massive amounts of water for cooling — even in drought-stricken areas

  • ESG, sustainability, and net-zero teams are excluded from AI procurement decisions

We can’t afford to repeat the last century’s pattern: progress that scales without planetary accountability.

Let’s compare:

  • ChatGPT’s infrastructure consumes more power daily than the world’s largest offshore wind farm generates

  • Meanwhile, major AI players continue to expand compute without integrated energy modeling

What if we flipped the metric?

  • Energy per insight becomes the KPI

  • AI infrastructure is audited for carbon intensity and grid mix

  • Model training is geofenced to renewable-powered zones

  • Governments tie AI tax incentives to clean-energy sourcing

This isn’t anti-AI. This is pro-future.

Your Move

If you're leading sustainability, technology, procurement, or infrastructure — here’s where to start:

  1. Audit your AI stack — know where your compute is running and what powers it

  2. Include AI workloads in Scope 2/3 reporting — particularly for enterprise SaaS tools

  3. Procure regeneratively — require clean power declarations from vendors and cloud platforms

  4. Raise the bar — advocate for sector-wide benchmarks like carbon-aware AI, water disclosure, and energy-intensity labeling

Signals from the Field

  • 🌐 Sam Altman revealed that each ChatGPT prompt uses approximately 0.34 Wh of electricity and 0.000085 gallons of water — highlighting the urgent need to factor water and energy use into AI deployment decisions.

  • 🖥️ Google DeepMind applied AI to reduce data center cooling energy by up to 40%, proving that AI can be used to optimize infrastructure when designed with intent.

  • 📊 The IEA forecasts that data center electricity demand could reach up to 1,000 TWh annually by 2030 — largely driven by AI. That’s more than most countries consume today.

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