AI-driven workloads are driving up rack densities and thermal loads, making efficient cooling a critical sustainability challenge. With energy, water, and carbon reduction all now key performance metrics, operators need proven strategies to decarbonize without compromising reliability.

This whitepaper quantifies how direct-to-chip liquid cooling can deliver energy savings of up to 60% while also cutting water use by as much as 60%, offering clear design and operational pathways to improve efficiency and enable heat reuse.

Inside, you'll gain insight into:

• Optimizing system design through seven key sustainability levers, from coolant choice to CDU configuration
• Reducing total resource consumption through data-driven operational control and maintenance strategies
• Balancing efficiency gains with risk, reliability, and long-term flexibility for future AI infrastructure