Artificial Intelligence: A Monumental Energy Burden for Humanity

 

Artificial Intelligence is often perceived as immaterial, just algorithms and data. In reality, it is deeply physical. It runs on processors, data centers, cooling systems, global networks, and above all, on electricity.

AI stands on three visible pillars: massive datasets, neural networks, and computational power. The fourth pillar is energy. Every model training cycle consumes vast amounts of electricity. Every query from millions, soon billions, of users translates into measurable energy demand. When usage scales globally, consumption scales with it.

Project forward to 2050: if billions interact daily with AI systems, even modest per-interaction energy costs could accumulate into terawatt-hours per year. This excludes infrastructure overhead, cooling, redundancy, and the energy embedded in semiconductor manufacturing. AI is not just software—it is silicon, materials, water, logistics, and constant electrical supply.

Historically, human progress has followed energy transitions: fire, steam, electricity. AI represents a new phase, cognitive electrification. But unlike previous revolutions, it expands instantly at planetary scale. The paradox is clear: AI promises efficiency, yet the infrastructure enabling that efficiency may become a major energy consumer itself.

Artificial Intelligence is not only a technological breakthrough. It is an energy event.

The real question is no longer whether we can build smarter machines.
It is whether we can power them responsibly.

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