AI, Economics and Environment

18 Jun, 2025

The IT industry is no stranger to hype. From AI to Blockchain to Python, many recent technological trends are celebrated for their innovation—but rarely scrutinized for their energy efficiency or accessibility. Among them, AI stands out—not only for its transformative potential but also for its staggering environmental and social costs.

It’s time we look beyond AI’s effectiveness and benefits and begin seriously examining its environmental footprint and societal trade-offs. If we are to adopt these technologies responsibly, we must ask tough questions about sustainability and equity.

Let’s put things into perspective.

According to various projections, by 2028, AI-specific computing could account for 4.5% of global energy consumption. By 2030, its energy demands may exceed the combined household energy use of the U.S. and Canada. This isn’t just about electricity—AI data centers also require massive amounts of water for cooling, which can severely impact water-scarce regions. In fact, Microsoft’s 2023 efficiency report revealed that newer data centers are becoming more water-intensive, not less.

The environmental burden is only part of the equation. There’s also a growing concern around economic inequality. Much of this AI-driven energy use and technological infrastructure is controlled by just five major tech giants—a trend increasingly referred to as “hyper-consolidated capitalism.” This centralization of resources and influence raises serious questions about competition, economic fairness, and who truly benefits from the AI boom.

Still, the economic efficiencies enabled by AI are difficult to dismiss. Take Microsoft’s ADX H100 system: it costs around $350,000 to deploy, with an annual operating cost of $25,000–$30,000. These high-performance systems run continuously and can execute tasks that would require multiple human workers—often more quickly and at a lower cost. From a business perspective, AI becomes a cost-effective alternative to low-skilled labor, and as technology improves, the cost-to-performance ratio will only become more attractive.

So here’s the paradox: AI accelerates progress and drives efficiency, but at the same time, it deepens inequality and intensifies resource depletion. The trade-offs are becoming increasingly clear.

If we want to move forward with integrity, we need to balance innovation with responsibility. That means questioning not just what AI can do, but what it should do—and who it should serve. Our shared goal must be a sustainable and equitable future, where the benefits of AI are broadly distributed and its environmental costs are kept in check.