Aker ASA announced its participation in Nscale Global Holdings Ltd.’s Series B funding round with a $285mn commitment, positioning itself among the company’s largest shareholders. The $1.1bn raise will support Nscale’s development of sovereign-grade infrastructure for industrial-scale artificial intelligence.
A strategic equity acquisition for Aker
Aker’s investment includes both a cash contribution and the transfer of part of its land portfolio in Narvik, Norway, to a joint venture established with Nscale. In return, Aker now holds a 9.3% fully diluted equity stake in Nscale. A conditional clause tied to a potential initial public offering could raise this stake to 12.2%.
Aker and Nscale are currently finalising the details of their joint venture, expected to close in the fourth quarter. The two parties will each own 50% of the entity, created through capital and asset contributions. The entirety of Aker’s Narvik land assets will be integrated into the venture, which will host Nscale’s future industrial infrastructure.
Growth exposure linked to AI infrastructure
Nscale’s model is based on a GPU-first architecture designed to support increasing computational demands for sovereign artificial intelligence systems. The funds raised will accelerate the rollout of infrastructure in strategic locations.
Øyvind Eriksen, President and Chief Executive Officer of Aker ASA, will join Nscale’s Board of Directors. The joint venture is structured to allow Aker’s stake to be converted into Nscale shares at a future IPO, providing a potential long-term value creation mechanism for the Norwegian conglomerate.
Industrial clients already secured
Nscale has already secured its first industrial clients for the joint venture, including technology groups OpenAI and Microsoft. Their presence in the client portfolio supports Nscale’s objective to deliver high-performance, data-intensive services in a sovereign infrastructure environment.
The oversubscribed funding round reflects growing investor interest in digital infrastructure that meets regulatory and energy efficiency demands associated with large-scale AI deployment.
