SoftBank’s Stargate AI Investment Could Be Grounded by Tariff Worries

SoftBank ’s lofty artificial intelligence ambitions are reportedly colliding with the harsh reality of tariffs.

The Japanese conglomerate’s plan to invest $100 billion in AI infrastructure in the United States has slowed, Bloomberg reported Monday (May 12), as risks related to White House tariffs have hindered financing discussions.

Earlier this year, SoftBank and OpenAI embarked on the Stargate project, an AI infrastructure effort that could cost $500 billion over time.

Months after that announcement, however, SoftBank still hasn’t come up with a project financing template or held detailed discussions with banks, private equity investors and asset managers, the report said.

While there have been preliminary talks with lenders and alternative asset managers, no deals have ensued because financiers are rethinking data centers amid increasing economic volatility and cheaper AI services, according to the report.

The White House’s trade policies have caused investors to shy away from riskier bets amid worries about a recession. Additionally, the appearance of AI models like China’s DeepSeek has raised questions about the long-term profitability of OpenAI-linked projects, per the report.

SoftBank did not respond to PYMNTS’ request for comment.

The news came as OpenAI is dealing with changes. This month, the company backed off plans to convert itself into a for-profit entity . The startup’s restructuring effort still needs the endorsement of Microsoft , its biggest investor. This weekend also saw reports that the two companies are reworking their revenue-sharing agreement .

The Stargate project is one of several AI data center efforts being developed by Big Tech firms.

“AI data centers are fundamentally different because they require specialized hardware and infrastructure to handle the massive parallel processing needed for AI workloads,” Deborah Perry Piscione , co-founder of Work3 Institute , an AI and Web3 advisory firm, told PYMNTS in January. “Traditional data centers focus on storage and basic compute, while AI facilities need dense configurations of GPUs and AI accelerators, like Nvidia’s H100s, designed specifically for the complex matrix calculations that power AI models.”