AI capitalism and the environmental cost we're not talking about

When intelligence becomes an industry, what gets sacrificed?

There's a curious silence in the public conversation about AI. We talk endlessly about capability, efficiency, transformation - but almost never about the incentives shaping this technology, or the environmental footprint powering it.

And yet, these two forces are quietly defining the trajectory of the AI era.

Artificial intelligence is being built inside a capitalist system that rewards scale, speed, and dominance. When those incentives collide with a technology as powerful as AI, we shouldn't be surprised when ethical considerations get pushed aside.

At the same time, the environmental cost of building and running these systems is profound and rarely acknowledged. Intelligence, it turns out, is resource-heavy.

The moral tension inside AI companies

AI companies are not neutral actors. They respond to pressures from investors, markets, and competitive threats. Even with the best intentions, the gravitational pull of profit can slowly shift priorities, often without anyone noticing.

This is what Emad Mostaque refers to as the "revenue evil curve". A gradual slide where the demands of commercial success begin to override the responsibility to serve the public good.

Companies start with noble missions. Then they chase market share. Then they protect their position. Then they defend their data, their algorithms, their models, their moat.

Transparency becomes a risk. Open dialogue becomes a threat. Ethical caution becomes "slowing down."

And because intelligence is centralising rapidly, the power of these companies grows even as their incentives narrow.

This is economics. And economics shapes the future as much as technology does.

The environmental footprint we rarely discuss

There is nothing lightweight about AI's environmental impact. Training large models consumes staggering amounts of energy. Running them at scale requires continuous compute, water-intense cooling systems, rare minerals, and enormous physical infrastructure.

Each interaction feels small but the system behind it is anything but.

If AI continues to grow without environmental accountability, we could find ourselves in a strange position: relying on intelligence systems that accelerate the climate crisis they're supposed to help solve.

This is the ethical blind spot of the AI movement and one we can't afford to ignore.

What ethical leadership demands

Leaders must begin asking:

• What incentives drive the tools we're adopting?

• What environmental cost sits behind them?

• What trade-offs are we silently accepting?

Ethical AI requires a shift from extraction to regeneration. From "how fast can we scale?" to "how responsibility can we sustain?"

The future of intelligence should not come at the expense of the planet or the people it exists to support.

If we want AI to uplift society, it must also honour the world we live in.