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If you've noticed more construction crews, more transmission lines, or more "data center coming soon" signs in your area lately, you're not imagining things. AI has turned data centers from a background utility into front-page news, and with that attention comes a lot of questions some fair, some based on outdated assumptions, and a few that are flat-out myths that have taken on a life of their own online.
At Eagle Mountain, we build and operate the edge computing facilities that power modern AI workloads, so we field these questions constantly — from neighbors, local officials, reporters, and prospective customers a like. Below, we break down what a data center actually is, how it affects the community around it, and where the biggest misconceptions come from.
What Exactly Is a Data Center, and Why Do We Need More of Them?
Every app you open, every search you run, every AI model that summarizes a document or generates an image is doing that work somewhere. Not "in the cloud" in some abstract sense — on physical servers, racked in a physical building, connected to physical power and water infrastructure.
That building is a data center. It's the factory floor of the internet, and increasingly, the factory floor of AI itself. Eagle Mountain's edge AI-factories are purpose-built for exactly this kind of workload, placing compute closer to where data is actually generated and used.
As AI adoption accelerates, the demand for computing power is growing faster than almost any infrastructure category in modern history. That's why new facilities are popping up in more places, including regions that haven't historically hosted this kind of infrastructure. More facilities means more of these questions — so let's get into them.
Myth: Data Centers Drive Up Your Electricity Bill
This is probably the single most common concern, and it's an understandable one. Here's the reality: electricity rates are set by utilities and approved by state public utility commissions, not by the companies operating data centers. Operators don't get a vote on what you pay per kilowatt-hour.
What operators do control is how they connect to the grid — and that's where a responsible approach matters. At Eagle Mountain, when we bring a new facility online, we fund the substations, transmission upgrades, and interconnection work required to serve that load. We don't expect existing ratepayers to absorb the cost of our growth.
There's also a bigger-picture point worth making: U.S. electricity demand was largely flat for close to twenty years. That meant utilities had little incentive to modernize aging grid infrastructure. Demand is climbing again now — driven by electrification, EVs, and AI — and that's actually accelerating investment in grid upgrades that benefit everyone connected to it, not just the new facility.
Myth: Data Centers Strain the Grid and Cause Outages
Done right, it's usually the opposite. Utilities plan capacity in phases that match demand growth, and a well-structured data center project comes with coordinated grid investment baked in from day one — new substations, upgraded transmission lines, added regional capacity.
That infrastructure doesn't get torn down once construction wraps. It becomes a permanent part of the regional grid, available to every household and business on it. Modern facilities also build in their own backup power and demand-response capability, which means they can actually reduce strain during peak-usage periods rather than add to it.
Myth: Data Centers Are Loud
Less than most people assume. Cooling systems run continuously, which is where the "loud machine shed" image comes from — but modern facility design has largely solved that problem. Acoustic enclosures, sound barriers, and equipment attenuation are standard practice now, not upgrades. Independent measurements at well-designed sites regularly land in the range of a household refrigerator hum, not the roar people picture.
Facilities are also required to comply with local noise ordinances, and reputable operators commission independent acoustic studies before a site ever goes live not just to check a compliance box, but because being a decent neighbor is part of the job.
Myth: Data Centers Consume Enormous Amounts of Water
This one really comes down to cooling technology, and the technology has changed a lot in the last few years.
Older facilities that relied on evaporative cooling could use meaningful volumes of water on an ongoing basis. Newer facilities — including the ones Eagle Mountain builds — increasingly rely on closed-loop liquid cooling, part of what powers our Store20 storage architecture and broader compute footprint. In a closed-loop system, water is loaded once, sealed into the system, and recirculated continuously. Nothing evaporates. Nothing gets discharged. Day-to-day consumption ends up comparable to — or lower than — a commercial office building of similar size.
There's a one-time fill during construction, and yes, that number sounds large in isolation (a mid-sized closed-loop facility might use an amount roughly equal to a few Olympic pools' worth to fill). But that's a single event, not a recurring draw on the local water supply. Sealed systems don't need to be refilled on a regular basis.
Myth: The Economic Benefits Only Go to the Company
In most of the places where a data center is built, that facility becomes one of the larger taxpayers in the municipality almost immediately funding schools, roads, and local services for decades, not just during construction.
There's also a compounding effect that's easy to underestimate. Look at what happened when railroads and, later, the interstate highway system reached new communities: commerce followed, distribution and supply chains grew up around the new infrastructure, and regional economies expanded well beyond the original investment.
Data center infrastructure follows a similar pattern. A new facility typically means a stronger, more modern grid; faster regional connectivity; and a more resilient digital backbone assets that outlast the facility that triggered them. Businesses evaluating where to expand actively look for exactly those conditions. That's how one facility can end up seeding a broader tech and logistics ecosystem in a region that didn't have one before.
Myth: The Jobs Created Are Just Temporary
Construction employment is real, substantial, and shouldn't be dismissed building a modern facility involves skilled trades, electricians, engineers, and a long list of contractors and suppliers over a multi-year build. But the job story doesn't end when construction wraps.
Ongoing site operations create long-term, skilled technical roles. The expanded tax base funds public services that support the whole local workforce. Grid upgrades make the region more attractive to other large employers — hospitals, manufacturers, universities — who also need reliable power and modern infrastructure. And local vendors who work the initial build often carry those relationships and expertise into future projects.
At Eagle Mountain, we also invest directly in workforce development partnerships with technical schools and apprenticeship-style programs designed to build a local pipeline of AI and infrastructure talent, rather than flying in every specialist from somewhere else.
Myth: The Benefits of a Data Center Go to Just a Few
It's genuinely both a national and a local story, and that's worth sitting with. The AI infrastructure buildout underway right now is a competitiveness question at the national level — which regions build the grid capacity, the connectivity, and the technical workforce to support the next wave of computing and a very local, very concrete question for the specific communities where facilities actually get sited.
The communities that do best out of this shift tend to be the ones that engage early: asking direct questions, requiring real commitments on power, water, noise, and jobs, and holding developers accountable to those commitments. That's not adversarial it's exactly the kind of scrutiny responsible infrastructure development should welcome.
People Also Ask
How much electricity does a typical data center use?
It varies widely by size and purpose, from a few megawatts for a small facility to several hundred megawatts for a large AI trainingcampus. What matters more than the raw number is whether the operator funds itsown grid connection costs, as Eagle Mountain does, so the load doesn't get passed on to other ratepayers.
How close can a data center be built to homes?
Setback distances are set by local zoning and permitting authorities, not the operator. Acoustic studies and noise ordinance compliance are typically required before a facility can be sited near residential areas.
Do data centers pay local property taxes?
Yes. In most jurisdictions, data centers are assessed and taxed like any other commercial property, and given their size and equipmentvalue, they often become one of the larger taxpayers in a county or municipality.
What is closed-loop cooling, and why does it matter?
It's a cooling method where water is sealed into the system once and continuously recirculated rather than evaporated or discharged. It dramatically reduces the ongoing water footprint of a facility compared toolder evaporative cooling designs.
How long does it take to build a data center?
Timelines vary by size and scope, but a large-scale facility typically takes one to three years from permitting to full operation, with construction jobs supporting the local economy throughout that window.
Why are AI data centers different from traditional datacenters?
AI workloads, training and inference require far denser compute, higher-bandwidth networking, and more advanced cooling than traditional enterprise data centers. That's why purpose-built AI infrastructure, like Eagle Mountain's edge compute platform, looks andperforms differently from a legacy facility.
Related Blog Topics
Want to go deeper on any of the themes above? Explore morefrom Eagle Mountain:
- How Edge Computing Reduces AI Latency : why placing compute closer to data matters for real-time inference
- Inside Our GPU Compute Offering : a look at BlinkAI and dedicated GPU infrastructure for training and inference
- Understanding AI Infrastructure Pricing : what drives the cost of compute, storage, and networking at scale
- Where We Operate : a look at Eagle Mountain's edge facility locations and expansion plans
- Meet the Team Behind Eagle Mountain : the leadership driving our approach to responsible AI infrastructure
At Eagle Mountain, we build our edge AI facilities with that transparency in mind: closed-loop cooling by default, grid investment funded by us rather than passed on to neighbors, acoustic design built in from the start, and a real commitment to the communities where we operate not just the customers we serve.
Got a specific question about a facility near you, orcurious how Eagle Mountain approaches AI infrastructure differently? Get in touch with our team — we're happy to talk it through.
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