Data Center Real Estate Markets
Download PDFMahmoudi, Dillon, and Alan Wiig. 2026. Land for AI: Data Center Real Estate Markets. InThe Inner World of Artificial Intelligence, edited by Elham Bahmanteymouri, Mohsen Mohammadzadeh, and Fabio Morreale. CRC Press. doi.org/10.1201/9781003480167
Abstract
The rapid expansion of AI tools like ChatGPT has increased the processing of digital data, necessitating unprecedented growth in data storage and compute infrastructure. This surge in data usage has created a market for data centers supporting AI platforms. Data center Real Estate Investment Trusts (REITs) are becoming significant urban and economic actors, intertwining land, real estate markets, data storage, and access to technology. By leveraging land near major urban markets and continental backbone fiber optic networks, they generate “data rent” and “computational rent” and then reshape cities through financialized land and real estate profits. Based on analysis of industry materials alongside fieldwork in suburban Washington, D.C., this chapter explores the dynamic relationship between urbanization, technology, and finance. Data centers, though often in suburban and rural peripheries, are crucial to urban cores, influencing policy and perpetuating a feedback loop that increases data demand. We argue that the AI economy relies not only on financializing data and compute technologies but also on financializing land via data center real estate. In doing so, it transforms outlying regions into pivotal nodes of digital capitalism, challenging traditional notions of space, property, and value.
Summary
AI does not float in the cloud; it sits on land, behind fences, drawing power, water, and rent from very specific places. This chapter argues that the AI boom is, at its core, a story about land: the rapid expansion of warehouse‑scale data centers that consumes vast tracts of land in peri‑urban areas and ties AI’s abstract promises to concrete geographies of electricity grids, cooling systems, and zoning laws. We show that the explosive growth of AI technologies drives demand for data center capacity, which in turn accelerates the transformation of urban and peripheral landscapes, binding today’s AI economy to the same kinds of spatial reordering and uneven development that characterized earlier waves of industrialization.
To make sense of this transformation, we focus on the financialization of data centers and the rise of specialized data center Real Estate Investment Trusts (REITs) as paradigmatic landlords of the internet. These firms treat their holdings as financial assets rather than purely infrastructural nodes, decoupling the physical facilities from their operational functions and emphasizing their potential for capital appreciation and consistent revenue generation.
| Type of Rent | Source of Value | Spatial Anchor | Key Actors | Example Mechanisms |
|---|---|---|---|---|
| Traditional Rent | Land / space | Urban, residential, retail | Landlords, tenants | Lease agreements, zoning |
| Data Rent | Data storage / transmission | Proximity to networks | REITs, tech firms | Co-location fees, connectivity |
| Computational Rent | Compute power | Near AI / cloud clusters | REITs, cloud providers | GPU leasing, power contracts |
We introduce the concepts of data rent and computational rent to name the specific forms of value extraction that emerge when controlling the storage and transmission of digital information and the processing power necessary for AI platforms, such as LLMs, to function.
Data rent is the value and income generated from controlling the infrastructure that stores and transmits digital information, such as colocation space, bandwidth, and network proximity in data centers.
Computational rent is the value and income generated from controlling access to high‑performance compute resources, such as GPU‑rich data center capacity needed to train and run AI models.
AI’s infrastructural footprint is not just about technical capability but also about who captures the value produced by this expansion, deepening the inequalities embedded in digital capitalism.
Northern Virginia’s Data Center Alley is our key empirical lens, an archetype of how financialized digital infrastructure reshapes peripheral urban geographies. In a small area packed with more than 250 facilities, data centers sit nestled among residential neighborhoods, presenting an aesthetic of industrial fortification (high fences, security checkpoints, and a conspicuous absence of human presence) amid gated communities and manicured landscapes. Fieldwork revealed relentless construction, large swaths of land cleared for further expansion, and a speculative vernacular where signs proclaiming “We Buy Homes” in lower‑income urban neighborhoods are replaced by a different kind of frontier signage: “We Buy Cisco,” pointing to a secondary market in networking hardware.
While the expansion of data centers is framed as an economic win for host communities, the financial rewards flow primarily to REIT shareholders and tech companies rather than to local residents, who live with environmental strain, sensory disruption, and rising land values but see little direct economic benefit.
Across the chapter, we argue that AI urbanism is not about frictionless smart futures but about the extension of digital capitalism into the suburban and rural periphery. Data centers lock capital in place even as data flows globally, creating self‑reinforcing cycles of growth that concentrate infrastructure in select regions while embedding vulnerabilities in local economies tied to volatile tech and financial markets. Infrastructure serves as an asset for distant investors while reshaping the lived experiences of those at the periphery of digital capitalism, turning vast areas into securitized, privately controlled infrastructural spaces that primarily serve corporate clients. The expansion of AI is inseparable from the financialization of the built environment, embedding rent extraction in land, energy, and resources; any serious discussion of AI’s inner workings must therefore grapple with land, power, and the spatial reorganization of urbanization itself.