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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsUrban data centers make sense when being close to customers, businesses, or network infrastructure improves service. They are not automatically the best home for every digital workload: AI training and other compute-heavy tasks can often run farther away if a site has dependable power, telecommunications, and water. For cities, the key question is whether a proposal’s full infrastructure, environmental, and community costs justify its local benefits.
Who needs an urban data center?
Data centers house the servers, storage, and networking equipment behind cloud computing, AI, and other digital services. An urban or metropolitan location can suit companies that need nearby computing capacity, and services where response time matters. The Australian Department of the Prime Minister and Cabinet defines low latency as “the time it takes for a request to receive a response.” Nearby users and strong telecommunications links can help meet those needs.
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But proximity is not a universal requirement. The same Australian consultation paper says AI training and other compute-heavy “deep thinking” applications are less constrained by distance from population centers, provided reliable energy, telecommunications, and water connections are available. Distinguish interactive services, for which response time can matter, from workloads that can be scheduled or run remotely.
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- Customers and businesses: A nearby facility can provide computing services close to the organizations and users that rely on them.
- Network access: High-capacity fiber and connections to multiple networks are essential. A metropolitan area may offer useful connectivity, but the actual capacity and route diversity at a site still need to be checked.
- Latency-sensitive workloads: Applications that need fast responses may benefit from shorter network paths. Whether a particular urban site improves performance depends on its connections and the users it serves.
Those advantages must be weighed against local constraints. A city with limited electricity capacity, scarce water, expensive land, or a slow grid connection may be a worse fit than a more remote location with suitable infrastructure.
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Urban or remote: how to compare potential sites
There is no single best location. Compare the full site conditions rather than treating “urban” and “remote” as proxies for suitability.
| Factor | Urban or near-user site | More remote site | What to establish |
|---|---|---|---|
| Latency and customers | May suit services that benefit from proximity to users and businesses. | May suit workloads, including AI training, that are less sensitive to population proximity. | Which workloads will run there, who they serve, and whether network response time is a binding requirement. |
| Electricity | Existing infrastructure may help, but capacity and connection timing can be limiting. | May have access to power resources, but new transmission or grid upgrades may be needed. | Available capacity, reliability, connection schedule, required upgrades, and who pays for them. |
| Telecommunications | High-capacity fiber may be available, but capacity and route diversity are site-specific. | Can work if reliable, high-capacity connections are available; distance alone does not establish network quality. | Fiber capacity, resilience, and distinct routes to the networks and customers the facility needs. |
| Water and cooling | May compete with households and other users in a constrained supply system. | Still depends on a reliable water source and suitable cooling; remoteness does not remove water impacts. | Source, local scarcity, cooling design, direct water use, and effects during dry or high-demand periods. |
| Land and climate | Land costs and competing uses such as housing may be substantial. | Land may be more available, but construction, environmental constraints, and cooling demand remain relevant. | Land price, alternative uses, local climate, and permitting or environmental restrictions. |
| Community and public services | Residents may experience noise, heat, air pollution, or pressure on public infrastructure. | Local effects still depend on the site, infrastructure, and nearby communities. | Impacts, public-service costs, jobs, local procurement, mitigation, and meaningful community input. |
How much electricity and water do data centers use?
Use national or illustrative figures to understand scale, not to predict a particular city’s demand. Local impacts depend on facility design, operating conditions, the local grid, and the water system.
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- U.S. electricity: Lawrence Berkeley National Laboratory’s 2025 report, as summarized on its current Data Centers page, estimates data centers could account for 9.5–15.3% of total U.S. electricity use by 2030. This is a scenario range, not a certain outcome or a city-level forecast.
- Australian cooling water: A September 2026 consultation paper from Australia’s Department of the Prime Minister and Cabinet estimates data centers used 5.5 gigalitres of water for cooling in 2025, around 0.04% of total Australian industrial water use. It also cites Sydney Water’s forward-looking estimate that data centers could use up to 20% of Sydney’s drinking water by 2035. That is a projection, not observed use.
- Illustrative facility scale: A 2026 U.S. Geological Survey report attributes to the International Energy Agency (2025) an estimate that a 100 MW data center may consume 2 million gallons of water per day. Treat this as an illustrative scale estimate, not a universal figure for facilities of that capacity.
National totals can obscure local pressure. Australia’s consultation paper warns that facilities concentrated in a single supply system can have significant local effects even when their estimated share of national industrial water use is relatively small. Cooling choices also involve tradeoffs: water-based cooling can reduce electricity use while increasing direct water demand. Efficient or closed-loop approaches may reduce consumption, but the appropriate option depends on the site and operating conditions.
What should a city examine before approving a proposal?
Review the proposal as an infrastructure and land-use decision, not only as an investment announcement. Pennsylvania’s Data Center Planning Toolkit is designed for local officials working from initial inquiry through zoning, permitting, and long-term planning. It is a Pennsylvania resource, not a national rule, but its review areas offer a practical checklist.
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- Power: What capacity is available, when can the facility connect, what grid or transmission upgrades are required, and who funds them?
- Water and cooling: Which water source will be used, how does local scarcity affect the proposal, and what are the cooling system’s direct water and electricity demands?
- Network: Are there enough high-capacity fiber connections, with sufficient route diversity and resilience?
- Land use: What land is required, what other uses could it serve, and are housing, agriculture, or municipal priorities affected?
- Environmental and neighborhood effects: What noise, heat, air pollution, and emissions are expected, and what enforceable measures will reduce harm?
- Public costs and benefits: Who pays for infrastructure and service needs? What jobs and local procurement are expected, and how will the city track those commitments?
- Community priorities: How will residents be involved early enough to influence decisions, and how will concerns be addressed through planning and permitting?
What current examples do—and do not—show
Associated Press reporting in June 2026 said C40’s network included about 1,700 data centers in member cities and expected growth above 40% in 50 of those cities. These are figures reported for that network and its member-city definitions, not a count or forecast for all cities. The report also said pending permits in the Phoenix area could double electricity demand if every proposed facility were built. That is a conditional pipeline scenario, not an observed increase in demand.
A separate 2026 U.S. Geological Survey study identified 771 existing AI data centers and more than 3,300 power plants in its study area of Alaska and 11 western U.S. states. It reported that 6% of the AI data centers and 22% of power plants were on or within one mile of Bureau of Land Management lands. The study concerns federal public lands in that region; it does not assess urban sites generally or identify optimal locations. It also says its analysis is not a comprehensive ecological, regulatory, or land-suitability assessment.
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