For decades, industrial site selection followed a familiar hierarchy. Companies looked for available land, transportation access, workforce, tax incentives, and proximity to customers or suppliers. Utilities mattered, of course, but power was often evaluated as one item on a broader checklist. If a site had sufficient service or a credible utility upgrade plan, the project could usually move forward.

That assumption is becoming harder to defend.

For power-intensive industries, the central site selection question is no longer simply whether electricity can be delivered. It is whether a site sits inside an energy ecosystem capable of supporting reliable operations, future expansion, and cost control over time. That is a different question, and it points toward a different model of industrial development.

The cost of waiting for power is now a strategic risk. Lawrence Berkeley National Laboratory’s interconnection queue tracking shows that the median timeline from interconnection request to commercial operation has stretched to more than four years for recent projects, up from less than two years in the early 2000s. Projects that do move forward may also face significant upgrade costs. The next generation of competitive sites may not look like traditional industrial parks. They may look more like energy parks.

An energy park is more than co-location, such as a data center built next to a power plant. Co-located generation is typically a one-to-one arrangement: one large load positioned near one generation asset, often to bypass grid constraints or reduce interconnection risk.

An energy park is more integrated. It combines multiple generation resources, storage, large industrial loads, and a shared interconnection strategy into a coordinated energy system. In the strongest versions, it may include access to natural gas, renewables, batteries, substations, transmission, industrial water, fiber, and land for phased growth.

Put simply, co-location answers one question: Where can this project get power now?

An energy park answers a larger one: How can this site continue to grow as energy demand, reliability needs, and infrastructure constraints change?

That distinction is becoming increasingly important for corporate real estate leaders, manufacturers, logistics operators, and site selection consultants. AI data centers may have forced the issue first, but they are not the only users affected by the shift.

Advanced manufacturing, semiconductor fabrication, robotics, hydrogen, cold storage, and large-scale logistics facilities are all becoming more energy-intensive. Many of these industries also require high uptime, stable power quality, and the ability to expand without restarting a multiyear utility process.

For site selectors, this means the evaluation framework needs to change. A powered site is not simply a parcel with utility service. It is a location with energy optionality, which can take several forms.

A site near existing transmission and substations may offer faster access to grid capacity. A site near high-capacity natural gas infrastructure may support on-site generation or backup fuel strategies. A site with room for solar, storage, and future generation may support phased growth. A site connected to an industrial microgrid or energy park may reduce exposure to congestion, queue delays, and single-source reliability risk.

None of these attributes guarantees success, but together they create a fundamentally different risk profile than a traditional greenfield parcel waiting on future upgrades.

This is why the emerging energy park model is important. It gives developers and end users a way to evaluate sites as energy systems, not just real estate.

The model is still in its early stages, but examples are beginning to emerge. The National Academies has described energy parks as integrated hubs that co-locate generation, storage, and large-scale loads such as data centers and advanced manufacturing at a single point of interconnection.

The appeal is practical: By locating supply and demand together, energy parks can reduce the need for new long-distance transmission and create a more coordinated path for bringing large loads online.

Hitachi and X Labs recently announced plans to collaborate on energy parks for AI data centers in North America, describing the model as a way to deliver gigawatt-scale power as a service and reduce power procurement constraints.

While that example is focused on AI infrastructure, the underlying model is broader. It shows how energy, industrial demand, and development strategy are beginning to merge.

Manufacturing examples point in the same direction. Hyundai Motor Group has announced plans for a major innovation hub in South Korea that combines robotics, AI, hydrogen energy, solar power, and smart city solutions.

The exact structure is different from a U.S. industrial park, but the signal is relevant: Advanced industrial companies are increasingly thinking about computing, manufacturing, and energy infrastructure together rather than as separate planning categories.

The takeaway is that energy infrastructure should move much earlier in the site selection process.

A conventional site selection process might ask whether a utility can serve the project. A more advanced process asks different questions.

What generation resources are already nearby? Is there access to a firm fuel supply? How constrained is the local transmission system? Can the site add behind-the-meter power or storage over time? Are there multiple energy sources, or is the facility dependent on one constrained node? Can future expansion be supported without triggering another long interconnection study? Does the surrounding infrastructure help manage reliability risk, or does it simply shift that risk to the operator?

These questions matter because power availability is no longer only an operating cost issue. It is now tied to project timing, resilience, customer commitments, and long-term competitiveness.

A manufacturer that loses production because of unreliable energy does not simply pay a higher utility bill. It risks missed orders, damaged equipment, delayed shipments, and lost strategic capacity. A logistics operator that cannot electrify or automate on schedule may fall behind competitors. A semiconductor or robotics facility that cannot secure stable, expandable power may never reach full production.

One point of contention developers should note: AI did not prove that the energy park model will work economically. In many cases, the economics remain challenging.

What AI did prove is that the cost of relying on conventional infrastructure is not currently sustainable. That lesson will not remain confined to data centers as energy-intensive industries increasingly compete for limited resources.

Whether the long-term economics make sense will not take a back seat to the cost of staying in the game.

The industrial parks of the 20th century were built around transportation. Rail access, highways, ports, and proximity to labor shaped where factories and logistics hubs grew.

Those factors still matter, but the next generation of industrial growth will increasingly be shaped by energy architecture.

Companies that understand this new dynamic will not simply ask where they can build. They will ask where the surrounding energy ecosystem gives them the greatest ability to operate, grow, and adapt.