When OpenAI announced its $100 billion Stargate data center initiative with SoftBank earlier this year, it was pitched as the most ambitious infrastructure project in the history of artificial intelligence. But behind the fanfare, the project has encountered a series of operational and logistical challenges that are now serving as cautionary lessons for its chief rival, Anthropic, as the Claude maker plans its own massive infrastructure buildout.
According to The Information, Anthropic executives have been closely studying the early missteps of the Stargate project—from construction delays and power procurement headaches to difficulties coordinating among multiple corporate partners—as the company maps out its own data center strategy. The takeaway for Anthropic’s leadership is straightforward: scale is essential, but execution risk can be just as dangerous as falling behind in the AI arms race.
Stargate’s Growing Pains Become an Industry Case Study
The Stargate project, a joint venture between OpenAI, SoftBank, Oracle, and initially Microsoft, was unveiled at the White House in January 2025 with President Trump’s blessing. The plan called for building a network of massive data centers across the United States, beginning with a facility in Abilene, Texas, designed to house hundreds of thousands of AI chips. The ambition was to secure the compute necessary for training the next generation of frontier AI models—systems that could cost billions of dollars to develop.
But as The Information reported, the project has been beset by complications. Construction timelines have slipped. Securing reliable power—a perennial bottleneck for hyperscale data centers—has proven more difficult than anticipated. And the multi-party corporate structure of the venture has introduced layers of complexity that have slowed decision-making. Microsoft’s evolving role in the partnership has added further uncertainty, as the software giant has simultaneously pursued its own independent data center expansion to support Azure’s AI workloads.
Anthropic’s Infrastructure Ambitions Take Shape
Anthropic, which has raised more than $13 billion in funding and counts Amazon Web Services as its primary cloud partner, is now preparing to make its own substantial investments in compute infrastructure. The company has been weighing whether to build or lease dedicated data center capacity beyond what AWS provides, a strategic decision that would mark a significant shift for a company that has historically relied on cloud partnerships rather than owning physical infrastructure.
People familiar with Anthropic’s planning told The Information that the company’s leadership—including CEO Dario Amodei—views the Stargate experience as a real-time tutorial in what can go wrong when infrastructure ambitions outpace operational readiness. Among the specific lessons Anthropic has drawn: the importance of locking down power purchase agreements well in advance, the risks of overly complex joint venture structures, and the need to maintain tight control over construction timelines by working with experienced data center developers rather than attempting to build from scratch.
The Power Problem That Won’t Go Away
Energy procurement has emerged as perhaps the single greatest constraint on AI infrastructure expansion in the United States. Data centers powering large language model training runs can consume hundreds of megawatts of electricity—equivalent to the power needs of a small city. Utilities in many parts of the country are struggling to keep pace with the surge in demand, and permitting for new generation capacity can take years.
The Stargate project’s difficulties in this area have been well documented. Reports from Reuters and other outlets have detailed how the Abilene site faced challenges securing sufficient power commitments from local utilities, forcing project planners to explore alternative energy sources including natural gas and potentially nuclear power. Anthropic, observing these struggles, has reportedly prioritized energy security as a first-order concern in its infrastructure planning, seeking locations where power availability is already assured or where long-term contracts can be executed quickly.
Amazon’s Role Complicates and Clarifies
Anthropic’s relationship with Amazon adds both advantages and complications to its infrastructure calculus. AWS has committed billions of dollars to Anthropic and serves as the primary platform for deploying Claude models to enterprise customers. Amazon has also been aggressively expanding its own data center footprint, spending tens of billions annually on new facilities worldwide. In theory, this gives Anthropic access to enormous compute resources without the capital expenditure burden of building its own facilities.
But relying entirely on a cloud partner creates dependencies that can become problematic as AI companies scale. OpenAI’s own complicated relationship with Microsoft—which is simultaneously a $13 billion investor, a cloud provider, and increasingly a competitor in AI products—illustrates the tensions that can arise. Anthropic’s leadership is reportedly mindful of these dynamics and is exploring a hybrid approach: continuing to use AWS for inference and deployment while potentially securing dedicated training clusters that give the company more control over its most sensitive and expensive workloads.
The Broader Race for Compute Dominance
The infrastructure challenges facing both OpenAI and Anthropic reflect a broader industry-wide scramble for compute capacity. Google DeepMind, Meta, and xAI—Elon Musk’s AI venture—are all investing tens of billions in data center construction. xAI’s massive facility in Memphis, Tennessee, which came online in late 2024, demonstrated that speed of execution can be a competitive advantage, though it too faced scrutiny over environmental and permitting concerns.
According to recent reporting by Bloomberg, total capital expenditure commitments for AI data centers among the major technology companies now exceed $300 billion through 2027. This spending spree has created fierce competition for everything from Nvidia’s latest GPU chips to qualified construction workers and electrical engineers. The companies that can execute most efficiently on infrastructure—not just those that spend the most—are likely to hold a significant advantage in the race to build more powerful AI systems.
Lessons in Corporate Structure and Governance
One of the more nuanced lessons Anthropic appears to be drawing from the Stargate experience concerns corporate governance and partnership structure. The Stargate joint venture involves multiple parties with overlapping but not always aligned incentives. SoftBank brings capital but has historically favored speed over operational discipline. Oracle provides cloud infrastructure but is a less established player in AI compared to AWS, Azure, or Google Cloud. OpenAI itself is undergoing a complex corporate restructuring, transitioning from a nonprofit to a for-profit entity, which has introduced legal and organizational distractions.
Anthropic, by contrast, has maintained a relatively streamlined corporate structure. While it has multiple investors—including Google, Salesforce, and various venture capital firms in addition to Amazon—its operational decision-making remains concentrated among a small group of executives and researchers. People close to the company say this lean governance model is viewed internally as a strategic asset, one that allows faster pivots and clearer accountability when it comes to infrastructure decisions.
What Comes Next for Both Companies
The coming 12 to 18 months will be critical for both OpenAI and Anthropic as they attempt to translate massive financial commitments into actual operational compute capacity. OpenAI needs the Stargate project to deliver on its promises if it hopes to train the next generation of models that justify its reported $300 billion valuation. Anthropic, meanwhile, must figure out the right balance between relying on Amazon’s infrastructure and building independent capacity that gives it strategic flexibility.
Industry analysts note that the companies face fundamentally different risk profiles. OpenAI has committed to a highly visible, politically charged megaproject that will be judged on whether physical buildings get built on schedule. Anthropic’s approach—quieter, more distributed, and more reliant on existing cloud infrastructure—carries less headline risk but may ultimately limit the company’s ability to access the sheer volume of compute needed for the largest training runs.
What is clear is that the AI industry’s center of gravity is shifting from pure research to industrial-scale execution. The companies that master the unglamorous work of securing power, pouring concrete, and managing supply chains will be the ones best positioned to push the boundaries of what AI systems can do. Anthropic, by studying its rival’s stumbles, is hoping to avoid learning those lessons the hard way.
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