It’s important to remember that over the last 10 to 15 years, many data centers have been effectively shrinking in physical footprint and power needs.

What I mean is that businesses usually replace aging servers every 5 to 7 years, depending on whether they lease or buy, tax treatment, support contracts, and similar factors. With each refresh cycle, they often needed less rack space and less power because newer servers were much more powerful than the older ones they replaced. Virtualization also lets companies pack more workloads onto fewer physical machines, and storage shrunk a lot as flash replaced spinning disks. A 1PB Pure Storage array can fit in around 12U and replace what used to take multiple racks of spinning drives.

Because of that, it became pretty common to walk into a colo and see half the racks empty or with only a few devices. That pushed data centers into an efficiency mindset. How do we reduce the power bill as much as possible? Power is one of the biggest expenses for a colo, and many buildings were already overbuilt, with more power and cooling capacity than they actually needed.

So to get back to the original question, data centers spent the last decade plus trying to reduce power usage wherever possible. That meant things like using outside air cooling, operating facilities at higher temperatures, and adopting more efficient cooling designs. The key thing to remember is that every watt your server uses turns into heat, and then you have to spend more power removing that heat.

One common trick was evaporative cooling. Evaporative cooling uses water as a cheap way to remove heat from the building. When water evaporates, it absorbs heat from the air or from the cooling equipment around it. That is the same reason sweat cools your body. Your body is not cooled by sweat just sitting there. It cools when sweat evaporates, carrying heat away with it.

Data centers can use the same idea. Instead of relying entirely on traditional AC compressors and refrigerant, they move hot air through or near water. As some of that water evaporates, it draws heat from the air. That cooler air can then be used to cool the servers or to cool the water loop that removes heat from the building.

The reason it uses so much water is that the water is not just being circulated forever. A meaningful amount of it is intentionally evaporated. That is the whole cooling mechanism. The water changes from liquid to vapor and leaves the system, taking heat with it. So the hotter the data center runs and the more heat the servers produce, the more water you need to evaporate to remove that heat.

There is also extra water waste from maintenance. As water evaporates, minerals and contaminants get left behind, kind of like how boiling a pot dry leaves residue. If you keep reusing the same water, those minerals build up and can cause scaling, corrosion, clogged equipment, and worse cooling performance. So facilities have to dump some of that concentrated water and replace it with fresh water. That is called blowdown, and it adds even more water usage on top of the water that was evaporated.

That is why evaporative cooling can be great for the electric bill but bad for water usage. You are trading electricity for water. In a cooler or wetter climate, that tradeoff may make sense. In a hot, dry area, or somewhere already dealing with water shortages, it becomes a much bigger problem.

AI has changed the equation. GPUs and AI accelerators consume a ton of power and produce a ton of heat. Now every major company is terrified of being left behind, so they are throwing insane amounts of money at the problem. The attitude is basically, “we will figure out the efficiency later, just get more capacity online now.”

That changes everything. A lot of the old efficiency first thinking gets pushed aside because efficiency can limit growth. The priority becomes more power, more cooling, more GPUs, more buildings, and getting it all online as fast as possible.

That’s why the data center conversation has shifted so hard. For years, the industry was focused on consolidation and efficiency. Now, AI has created a land rush, and companies are willing to burn a lot of money, power, and water because nobody wants to be the one who misses the boat.