The AI boom has increased demand exponentially, requiring cutting-edge infrastructure and high-efficiency technology to support grid resilience, ultimately reshaping how the digital future is built.
The AI boom has increased demand exponentially, requiring cutting-edge infrastructure and high-efficiency technology to support grid resilience, ultimately reshaping how the digital future is built.
The more of this stack a company controls, the more capital-intensive it is and the more it influences its costs, performance, and ultimately, its returns.
But it is important to note that this stack is not static—and neither are the companies operating within it.
The Entry Point: Asset-Light DeploymentIn both cases, companies own the machines—but not the infrastructure.
That infrastructure is provided by colocation operators, which supply power, cooling, and physical space to run compute at scale. Historically, this has been viewed as a supporting function. Increasingly, it is becoming one of the most important parts of the business.
Colocation is no longer just about hosting machines—it is about monetizing power and infrastructure.
That same structure is now emerging in AI.
In that sense, colocation is no longer just the entry point to the stack.
It is becoming a bridge between two industries—connecting energy, infrastructure, and compute demand in a single, evolving system.
Controlling InfrastructureAs companies move up the stack, the next step is owning the physical environment itself.
At this stage, companies are no longer just deploying hardware. Instead of relying on third-party hosting, operators build or acquire their own facilities, including data centers, substations, and cooling systems.
This shift changes operations significantly. Infrastructure ownership allows operators to control power costs, optimize performance, and reduce dependency on external providers.
But increasingly, the value of infrastructure is not just in the buildings—it is in the power connections attached to them.
That dynamic is now playing out across industrial assets that were once considered obsolete, allowing for companies to turn underutilized facilities into powerful engines for growth
Many of these sites faced shutdown due to the gradual offshoring of high-paying industry jobs to other countries. But they share one critical feature: they are already connected to the energy grid at scale.
That interconnection—often the hardest and slowest part of building new infrastructure—has suddenly become a valuable asset in its own right.
In this environment, owning infrastructure is no longer just about controlling operations. It is about securing access to energy systems that can handle increasing demand while supporting overall resilience.
Bring Your Own PowerBut even that pool of grid-connected infrastructure is limited.
The number of industrial sites with existing high-capacity interconnections is finite, and much of it has already been identified or repurposed by major industries. As consumer demand for computing accelerates—particularly from AI—the scale of power required necessitates solutions to maintain grid resilience while deploying new technological solutions.
In other words, the constraint is no longer just where infrastructure exists. It is whether the energy grid itself can keep up. That pressure is now forcing a broader shift.
Across major power markets, operators are confronting a new reality: connecting large loads to the grid is becoming more complex and increasingly uncertain. Consequently, regulators are beginning to revisit how large energy users are integrated into the system.
In regions like PJM and ERCOT, grid operators have already started to adjust their frameworks in response to surging demand from data centers and other high-load users. New rules and proposals are emerging to govern how large-load data centers connect to the grid, how costs are allocated, and how reliability is maintained amid rapidly growing demand.
To address these challenges, a growing number of operators are moving beyond the grid altogether.
This “bring your own power” model transforms electricity from a cost center into a strategic advantage. It allows operators to stabilize pricing, ensure availability, and align compute capacity with energy supply.
Full Vertical IntegrationFor some operators, even taking ownership of power is not the final step.
At the highest end of the spectrum, companies can control nearly every component of the compute system: power generation, infrastructure, hardware deployment, and even chip design.
At the same time, Bitdeer is extending horizontally into AI processing. The company has begun deploying its own GPU infrastructure for AI cloud services while exploring high-performance computing colocation opportunities with tenants.
By operationalizing each layer of the stack, operators can optimize performance end-to-end, reduce exposure to external constraints, and define their own capacity limits.
While few companies fully occupy this position today, the direction of travel is clear. The closer operators move toward full integration, the more they transform from users of key energy and digital infrastructure into builders of it.
Same Stack, Different PositionsWhat emerges from this comparison is not a story of two separate industries, but of one shared system with multiple points of participation.
In the next installment, we will take this one step further: How these models are beginning to converge—and what that means for the future of energy, compute, and capital.
