Logan is an MIT graduate with 5 years of experience in RE finance and development. At Boyer and PEG, he managed major industrial projects and secured institutional capital. He holds a BS from BYU.
For decades, the real estate industry has operated under a singular mantra: location, location, location.
In the traditional sense, this meant visibility, foot traffic, or proximity to supply chains. However, as the global economy shifts toward a digital-first model, a new asset class is rewriting the rules of the physical world. Data centers (the massive, humming warehouses that power everything from social media to artificial intelligence) have turned "location" into a complex calculation of power grids, fiber optic paths, and network density.
For a real estate developer, a data center might look like a standard industrial warehouse from the outside. Yet, the internal logic of these buildings is vastly different. Developing a data center without understanding its technical requirements is a high-stakes gamble.
Traditional industrial sites often lack the specific "digital nutrients" required to sustain a data center, leading to stranded assets or projects that fail to attract the right tenants. To succeed, developers must stop looking at land as just dirt and start seeing it as a portal to the global network.
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The Two Worlds of Digital Real Estate
To navigate this market, developers must first distinguish between two primary types of facilities: Colocation and Hyperscale. These are not just different sizes of buildings; they represent entirely different investment strategies and tenant needs.
Colocation facilities are the "apartment complexes" of the internet. They house servers for multiple tenants who want to be near their customers to ensure fast response times, known as low latency. These facilities are highly sensitive to connectivity.
Research indicates that the presence of an Internet Exchange Point (IXP) (a physical location where different networks connect) massively increases the likelihood of a colocation center being built in a specific area.
In fact, adding just one IXP to a county can increase the probability of a colocation facility’s presence by over 250%. For these tenants, being in a dense urban environment with immediate access to fiber is non-negotiable.
In contrast, Hyperscale facilities are the "private estates" owned by tech giants. These are massive installations, often exceeding 50 megawatts in capacity. Unlike colocation centers, hyperscalers are less tethered to city centers.
They prioritize the cost of operations over the speed of connectivity. They seek vast tracts of land where electricity is cheap and taxes are favorable. As developers move further away from urban cores, the scale of these facilities typically increases because land is cheaper and zoning is less restrictive.
However, even these giants are not immune to the laws of infrastructure; they still require proximity to major fiber routes, often found along highways or railroads.
The rise of Artificial Intelligence (AI) has introduced a new layer of complexity to the development roadmap. AI workloads are generally split into two phases: training and inference.
Understanding this divide is crucial for a developer’s long-term strategy. Training an AI model requires an enormous amount of electricity but does not require an immediate response time. These facilities can be located in remote, rural areas where power is abundant and inexpensive.
Inference, however, is the act of the AI answering a user’s request in real-time. This requires the facility to be close to the user to avoid delays. Therefore, while the "training" facilities may migrate to the outskirts, "inference" facilities will remain anchored to urban centers.
This creates a bifurcated market where developers must choose which part of the AI lifecycle they are building for.
The most significant constraint for any data center project is power. Modern facilities are measured in megawatts, not square feet. Every cent increase in the cost of electricity per kilowatt-hour can significantly reduce the planned capacity of a facility.
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If the cost of power is too high, a 40-megawatt project might be forced to scale down to 20 megawatts just to remain economically viable. For a developer, securing a site with a high-capacity power hookup is often more valuable than the land itself.
Logan is an MIT graduate with 5 years of experience in RE finance and development. At Boyer and PEG, he managed major industrial projects and secured institutional capital. He holds a BS from BYU.
Wirginia Leszczyńska is COO & CSO at DL Invest Group, driving 17+ years of strategic growth, digital transformation, and ESG-led investment to maximize portfolio value in Poland’s property market.
E-Lon is Entralon’s AI analyst — scanning markets, predicting trends, and powering smart insights to help investors and readers stay ahead of the curve.
Civil engineer-architect, co-founder and managing director of Archipelago. Specialised in research-driven architecture for living, care, work and learning, with a focus on user experience, sustainability and circular building economics.
Karsten R. Gerdrup is Director of Analysis at Norges Bank, specializing in monetary policy, macro-financial modeling, and forecasting. An economist with extensive policy experience, he contributes to financial stability and fiscal policy analysis.
Dr Farid Zadeh Bagheri is an entrepreneur and strategist focused on redefining access in real estate through structural insight, technology, and global investment experience.
E-Lon is Entralon’s AI analyst — scanning markets, predicting trends, and powering smart insights to help investors and readers stay ahead of the curve.
Architectural graduate (M.Arch) & PhD researcher in BIM/Digital Twins. With 5+ years of experience in Revit/Lumion, I bridge technical design with innovative tech to enhance the built environment.