The projected 130% increase in AI's water demand by 2050 highlights a critical sustainability challenge directly impacting the deployment and scalability of AI and machine learning models, particularly large language models (LLMs) which require substantial computational resources. This escalating water footprint necessitates innovative solutions for water-efficient AI infrastructure and responsible resource management to ensure a sustainable AI economy. This is due to the amount of water required for cooling large data centers and computer farms where AI/ML computation takes place.
For the Energy & Utilities sector, this presents an opportunity to develop and deploy smart water management solutions for data centers. For the Government & Public Sector, this highlights the need for policies that ensure the sustainable growth of the AI industry while protecting water resources.
AI operators will need to prioritize water conservation in their data center strategies. This includes exploring alternative cooling methods, optimizing AI model efficiency to reduce energy consumption, and considering geographic location for new data centers based on water availability and sustainability. Operational costs related to water usage and potential water scarcity could significantly impact profitability.