Microsoft is planning to significantly expand its data center capacity to around 38 gigawatts (GW) by 2032, according to a report by Bloomberg News. Currently, the company has about 12GW of capacity, with approximately 2GW dedicated to AI-specific chips. This AI-specific capacity is expected to make up about one-third of the planned 38GW by 2032.
If Microsoft achieves this reported capacity mix, it would mean that around 12.7GW of the total 38GW would be focused on AI-specific chips. This represents a substantial increase from the current 2GW of AI-specific capacity. Microsoft has not confirmed the reported 38GW target publicly.
In its fiscal fourth quarter, Microsoft added 1GW of data center capacity and is on track to double its overall capacity within two years. The company added 31 data centers across five continents during the quarter, with Azure and other cloud services revenue growing by 43% year-on-year.
Microsoft’s Fairwater AI data center design utilizes a network that connects hundreds of thousands of Nvidia GPUs across its Azure AI infrastructure. The company is also deploying its own AI silicon alongside accelerators from companies like Nvidia and AMD.
The reported expansion from 12GW to 38GW would add approximately 26GW to Microsoft’s current data center footprint. The company is already developing a 2GW data center campus in Pecos, Texas, which is expected to be one of the largest capacity additions in its history.
Microsoft has also made significant investments in renewable energy, contracting 40GW of new capacity across 26 countries since 2020. The company has reached its goal of matching its annual global electricity consumption with renewable energy.
Infrastructure spending remains a key part of Microsoft’s investment program, with capital expenditure reaching $41 billion in the fiscal fourth quarter. The company expects capital expenditure of about $175 billion for calendar 2026.
Overall, Microsoft’s plans for expanding its data center capacity and investing in renewable energy demonstrate its commitment to meeting the growing demands of AI infrastructure while also prioritizing sustainability and efficiency.
