Toward Next-Generation AI Data Centers: Power Delivery Architecture Shifts, Emerging Technologies, and Challenges

Sangwhee Lee; Rafal P. Wojda; Cheol-Hee Jo; Shuntaro Inoue; Pedro Ribeiro; Gui-Jia Su; Mostak Mohammad; Himel Barua; Nishanth Gadiyar; Praveen Kumar; Spencer Cochran; Subho Mukherjee; Whit Vinson; Vandana Rallabandi; Shajjad Chowdhury; Burak Ozpineci

arXiv · 2606.25095

Toward Next-Generation AI Data Centers: Power Delivery Architecture Shifts, Emerging Technologies, and Challenges

Sangwhee Lee·Rafal P. Wojda·Cheol-Hee Jo·Shuntaro Inoue·Pedro Ribeiro·Gui-Jia Su·Mostak Mohammad·Himel Barua·Nishanth Gadiyar·Praveen Kumar·Spencer Cochran·Subho Mukherjee·Whit Vinson·Vandana Rallabandi·Shajjad Chowdhury·Burak Ozpineci

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Abstract

The rapid growth of AI workloads is driving unprecedented increases in data center power demand, current transients, and thermal stress, exposing fundamental limitations in traditional 48 V rack architectures, low-voltage AC distribution, and line-frequency transformer interfaces. This paper reviews the three stages of architectural shifts required to support next-generation AI data centers and identifies three enabling technological building blocks: high-voltage conversion-ratio DC/DC converters, facility-level low-voltage DC distribution, and medium-voltage solid-state transformers. The advantages, technical challenges, and potential solutions associated with each building block are reviewed. Finally, future research directions and open challenges are discussed.

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Sangwhee Lee, Rafal P. Wojda, Cheol-Hee Jo, Shuntaro Inoue, Pedro Ribeiro, Gui-Jia Su, Mostak Mohammad, Himel Barua, Nishanth Gadiyar, Praveen Kumar, Spencer Cochran, Subho Mukherjee, Whit Vinson, Vandana Rallabandi, Shajjad Chowdhury, Burak Ozpineci. 2026-06-23. Toward Next-Generation AI Data Centers: Power Delivery Architecture Shifts, Emerging Technologies, and Challenges. https://arxiv.org/abs/2606.25095

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