Meta Platforms this week announced the start of construction on a new data center in Beaver Dam, Wisconsin, its 30th global facility and one tailored specifically for AI workloads.
Located on a site spanning hundreds of acres, the campus is receiving more than $1 billion in investment and is expected to bring more than 100 permanent jobs and over 1,000 construction positions at peak build-out.
The project will incorporate sophisticated technologies including dry-cooling systems designed to drastically reduce water use, and a commitment to restore 570 acres of nearby wetlands and prairie.
The facility aims to operate entirely on 100% renewable energy from the outset. Meta highlighted that this data center is optimized for large-scale compute, high-density racks, and the training of next-generation AI models across its social platforms.
The company sees owning more of its infrastructure as a way to control both cost and performance as the demand for AI grows.
Meta And The AI Infrastructure Race
For Meta, this move reflects a shift from relying solely on external cloud services toward building internally owned, custom-designed compute hubs.
The Wisconsin site joins a broader trend among tech giants who are committing massive capital to support the infrastructure backbone of artificial intelligence.
Unlike past data centers built primarily for web or social traffic, this facility is purpose-built for inference, training and high-volume model execution.
Location also plays a strategic role. Wisconsin offers cooler climate, favourable real-estate and power-grid conditions compared with traditional tech hubs.
This allows Meta to deploy efficient cooling systems and mitigate some of the regulatory and operational risks associated with dense compute builds.
The environmental strategy adds another layer. Dry-cooling reduces reliance on water resources, and the conservation of adjacent land creates a narrative of “infrastructure with responsibility,” offering a potential blueprint for how big-tech builds can engage with local communities and regulators.
Future Forward
The next steps will test Meta’s operational discipline and execution. Key areas to monitor include how quickly the campus becomes operational, whether the compute density meets AI-model requirements, and how the facility manages power and cooling demands.
Further, Meta’s ability to integrate this new infrastructure into its product roadmap, its AI models, applications and services, will determine whether the investment produces measurable returns.
For competitors, Meta’s Wisconsin project raises the bar. As AI models continue to grow in scale and complexity, the underlying compute architecture becomes a critical differentiator.
Success here could inspire similar build-outs by Amazon, Microsoft, Google and other cloud-scale players. This build signals that the next wave of AI isn’t just about algorithms or datasets. I
It’s about the physical machines, buildings, and energy systems that support them. Meta’s Wisconsin data center places the company not just in the AI model race, but in the global infrastructure arms race that underpins it.
