The Hidden Cost of AI: Why Every Click Adds Up

By: Ruby Jennings

The Hidden Cost of AI: Why Every Click Adds Up

Recycling one plastic bottle won’t change the world. Let’s be honest—it barely makes a dent. But if we all thought that way, we’d be drowning in plastic. One bottle turns into billions, and suddenly, the small stuff isn’t so small after all.

The same logic applies to artificial intelligence. Running a single AI-powered search or generating one AI image doesn’t exactly send smoke into the sky. The carbon footprint of a single query? Practically nothing. But the impact scales fast when millions of people do it every day.

Behind every AI-generated response is a data center—a warehouse full of high-powered computers running 24/7, storing, processing, and transmitting data. These massive facilities require huge amounts of electricity to operate and even more to keep the equipment from overheating. The cooling systems alone use enormous amounts of water and energy. According to the International Energy Agency (IEA), one large data center consumes as 

much electricity as it takes to power 400,000 electric cars. That’s 

the hidden energy cost behind every AI-generated image, chatbot response, and recommendation algorithm.

The AI Arms Race: A $300 Billion Bet on the Future

The Magnificent Seven (Apple, Microsoft, Alphabet/Google, Amazon, Meta, Nvidia, and Tesla) are in a massive AI spending race. In 2025 alone:

    •    Amazon plans to invest over $100 billion in AI-driven cloud services.

    •    Microsoft is spending $80 billion to expand its Azure AI infrastructure.

    •    Google is committing $75 billion to scale its AI computing power.

    •    Meta is allocating $40 billion to upgrade its AI capabilities.

That’s $300 billion in AI infrastructure spending—and that’s just from four companies. Nvidia, Tesla, and Apple are also making major AI investments.

But here’s the thing: AI uses far more electricity than traditional computing. A standard Google search already takes energy, but asking OpenAI’s ChatGPT to generate an answer requires nearly 10 times as much electricity. That’s because AI training and inference rely on GPUs (graphics processing units), which are far more power-hungry than regular CPUs.

Alberta’s Role: A Canadian AI Powerhouse

Even my home country, Canada, is getting in on the action. Alberta, known for its oil and gas industry, is now pivoting to AI infrastructure. The province is marketing itself as North America’s top destination for AI data centers, thanks to:

    •    Cheap energy (mostly natural gas).

    •    A cold climate (reducing the need for artificial cooling).

    •    A business-friendly tax structure.

While Alberta’s strategy makes sense economically, it also raises important questions. Should we be expanding AI infrastructure without considering sustainability? Will these AI-driven energy demands lock us into more fossil fuel dependence?

Is AI Really Green?

Tech companies are aware of the problem. Amazon, Microsoft, and Google have announced plans to tap into nuclear energy to help power their U.S. data centers. They’ve also invested in wind, solar, and alternative energy projects to offset AI’s growing carbon footprint.

But in the short term, most data centers still rely on fossil fuels. The power that keeps AI running still mostly comes from the existing electricity grid, which is overwhelmingly powered by coal, natural gas, and oil—the primary cause of global warming.

This means the same companies pushing AI forward are also making it harder to meet global climate goals. AI might be innovative, but its rapid expansion is forcing us to confront a tough question:

So… What Do We Do About It?

If we want to stop plastics from piling up in landfills, we have two main choices: recycle what we use or stop using so much in the first place (by banning or boycotting single-use plastics).

When it comes to AI, the same two-pronged approach applies:

    1    Push for AI to Be Powered Sustainably (The "Recycle" Strategy)

We don’t have to stop using AI altogether—just like we don’t have to ban all plastic. But we should demand cleaner AI infrastructure, just like we demanded better recycling programs.

◦    Hold Tech Companies Accountable – Right now, AI is growing faster than our ability to power it sustainably. We should demand transparency from AI companies. How much of their energy is renewable? Are they using offsets or actual clean energy?

 ◦    Push for Smarter AI Energy Policies – Imagine if AI companies were required to match every watt of electricity they used with renewable energy production. If OpenAI, Google, or Microsoft had to power their AI models entirely with clean energy, they’d be forced to innovate faster.

    2    Be a Conscious AI Consumer (The "Reduce Single-Use" Strategy)

If we want to stop single-use plastics, we don’t just recycle—we switch to reusable alternatives. AI works the same way: we don’t need to cut it out, but we can use it more responsibly.

◦    Think Before You Generate – AI models are fun to play with, but generating 100 images "just because" has a real energy cost. Do you need to run every search or use AI for everything?