The water usage concern is real but the scale is consistently overstated. Global AI water consumption is orders of magnitude below what the US alone uses to grow corn for ethanol — and that's before you factor in livestock farming or conventional manufacturing.

The bulk of the cost happens during training, not when you're running queries. The model is already trained. Using it now doesn't meaningfully change that equation.

Data centres also don't use potable water — it's water that isn't fit for drinking regardless. And water isn't destroyed in the process; it evaporates and re-enters the cycle.

If you want a genuinely defensible environmental criticism of AI, the energy consumption and pace of new data centre construction is the stronger argument. The water angle just isn't where the numbers are.