Equinix, a leader in global data center infrastructure, has announced a groundbreaking $15 billion joint venture with Singapore’s wealth fund GIC and the Canada Pension Plan Investment Board. This strategic move aims to significantly upgrade Equinix’s xScale data centers, predominantly in the U.S. These centers are tailored to support intensive AI workloads, marking a substantial leap from the existing $8 billion investment allocated across Europe and Asia.
Currently, xScale data centers cater predominantly to Europe and Asia, with plans to extend operations to the United States. Despite the current infrastructure delivering more than 725 MW of power across over 35 facilities in APAC, Europe, and North America, the fresh $15 billion investment will boost U.S.-based xScale buildouts, enhancing over 1.5 gigawatts of new capacity.
The CEO and President of Equinix, Adaire Fox-Martin, emphasizes, “As the world’s leading companies build out their infrastructure to support key workloads such as artificial intelligence, they require the combination of large-scale data center footprints optimized for AI training and interconnection nodes for the most efficient inferencing.”
In the realm of AI, data centers are known for their vast energy demands. Equinix is conscious of this, focusing on sustainability within their xScale centers. By 2022, data centers consumed about 460 terawatt-hours, accounting for nearly 2% of global electricity usage. Recognizing this, Equinix commits to 100% renewable energy usage by 2030.
The company has also pledged sustainable practices in digital infrastructure construction. Striving towards environmental responsibility, all xScale data centers are designed to meet LEED certification or its regional equivalents.
The joint venture’s ownership structure sees Equinix retaining a 25% stake, while GIC and CPP Investments each hold 37.5% equity interests. This collaboration not only enhances Equinix’s infrastructure capacity, but it also underscores a commitment to green energy and sustainable expansion, meeting the data demands of future technologies like AI head-on.
