What is the NAR 2026 Data Center Impact Report? It is the National Association of Realtors' first county-level study of how data centers affect surrounding real estate, released September 9, 2026, and its headline finding is that there is no single data center effect on property values. It maps 1,474 facilities across 251 U.S. counties and pairs that census with a member survey covering housing and commercial space. For CRE investors, the message is that the data center adjacency trade is real, highly concentrated, and easy to misprice. For the broader toolkit, see our guide to AI commercial real estate.
Key Takeaways
- NAR mapped 1,474 data centers across 251 counties, but 92% of the more than 3,200 U.S. counties analyzed have none at all.
- Ten counties hold 42% of all mapped facilities, with Loudoun County alone accounting for roughly 14% of the national total.
- Counties with 10 or more data centers show a $431,750 median home value against $174,500 elsewhere, a gap NAR explicitly declines to call causal.
- Commercial findings are far more positive than residential: 50% of agents saw nearby commercial values rise, versus 25% for homes.
- Industrial was the biggest reported beneficiary at 58%, followed by land at 38%, which matches the staging demand thesis but does not prove it.
- Residential electricity rates rose 21.4% from 2020 to 2024 in high concentration counties against 15.7% elsewhere, a direct operating expense signal.
What the NAR Data Center Impact Report Actually Found
The report's central conclusion is a warning against generalizing. "There is no single data center effect," said Lawrence Yun, NAR's chief economist, in the report announcement. "The number of data centers alone does not tell us what will happen to home values, jobs or utility costs." NAR analyzed more than 3,200 counties on home values, employment, electricity costs, and business mix, then surveyed members working in those markets. Thirty-eight percent of respondents reported a data center already in place or in development.
The county-level comparisons are striking. Counties with 10 or more data centers posted median household income near $89,000 against roughly $64,000 elsewhere, 41% bachelor's degree attainment against 22%, and 16% job growth from 2014 to 2024 against 2%. Home values there grew 95% over the past decade against 64% elsewhere.
Those numbers look like a case for buying anything near a hyperscale campus. NAR's own researchers say that is the wrong reading, and understanding why is the most useful thing a CRE investor can take from this report.
The Adjacency Trade Exists in About 1% of U.S. Counties
The concentration data reframes the entire opportunity. Only 1% of U.S. counties have 10 or more data centers, and the top 10 counties hold 42% of all mapped facilities. Loudoun and Prince William counties in Northern Virginia together account for about 19% of the national total. Silicon Valley adds 5%, central Ohio's Franklin and Licking counties another 5%, the Phoenix area 4%, and central Washington 4%.
This matters for pipeline strategy. A national search for "data center adjacent industrial" is not a national search at all. It is a screen across a handful of submarkets that institutional capital has already priced, plus a long tail of counties with one or two facilities where the spillover NAR's survey captured may be far weaker or absent. Site selection discipline here overlaps with the power-first framework in our analysis of the best and worst states for AI data centers.
One usable screen: real estate firms made up 6.4% of businesses in counties with 10 or more data centers against 4.9% in counties with none, a measurable signal of transaction activity concentrating where facilities cluster.
Why the $431,750 Number Is Not a Data Center Effect
The most valuable line in the report is a disclaimer. NAR principal economist Nadia Evangelou, the report's lead author, put it directly: "Our research does not support saying that a data center will automatically lower or raise nearby home values." Yun added that county-level numbers "can't tell us what happens to an individual home next to a facility."
The report states the reason plainly: these counties "were already high-income, highly educated technology hubs before the recent surge in new facilities." Loudoun County, Silicon Valley, and central Ohio were not randomly assigned data centers. They were chosen because they already had fiber, power, transmission access, and educated labor forces, the same attributes that independently drive home values, incomes, and job growth. The $431,750 versus $174,500 gap is at least partly a description of which counties get selected, not a measurement of what happens after selection.
For underwriting, this is the difference between a defensible comp and an expensive mistake. If you are paying a premium for a land or industrial parcel on the theory that a nearby campus will lift it, you need evidence of the mechanism in that submarket, not a national correlation. The practical test is whether you can name the actual demand source: construction staging, equipment storage, contractor office space, or utility infrastructure. Our analysis of how the data center boom spills into warehouse and industrial demand walks through the staging mechanism behind leasing near Meta and Google campuses.
This is where AI tools earn their keep. Feeding county-level comp sets, permit records, and lease abstracts into models like Claude, ChatGPT, or Gemini lets you test whether rent growth near a campus predates the campus. If it does, you are buying a tech-hub comp and calling it a data center comp. CRE investors who want help building that screen can reach out to Avi Hacker, J.D. at The AI Consulting Network.
Commercial and Residential Findings Diverge Sharply
The survey results split cleanly by property type, and the divergence is the report's most actionable finding. Among agents reporting a data center in their market, commercial perceptions ran strongly positive: 50% said nearby commercial property values had increased, including 22% who reported gains above 10%, and 42% said demand for nearby commercial space had increased against just 7% reporting lower demand. Industrial led the property types at 58% reporting increased interest, with land second at 38%.
Residential told a different story. Only 25% reported a positive impact on nearby home values against 22% reporting a negative impact, with roughly a third unsure. On residential demand, perceptions tilted negative: 19% saw increased demand against 26% seeing a decrease. The land competition and neighborhood pushback dynamics behind that split are covered in our piece on data centers versus housing.
The implication is that spillover, where it exists, runs to industrial and land rather than housing. That is consistent with a construction and logistics demand mechanism rather than a general amenity effect, and it argues for underwriting adjacency as a temporary demand pulse with real lease structure risk, not a permanent rerating.
The Operating Expense Signal Most Investors Will Miss
Buried in the utility data is a number that flows straight through to NOI. Residential electricity rates in counties with 10 or more data centers rose 21.4% from 2020 to 2024, against 15.7% elsewhere. Client concerns tracked it: 61% cited energy costs and 56% cited water use.
Commercial rate structures differ from residential, so this is not a direct multifamily or office input. But for any asset where the landlord carries electricity, a sustained 5.7 percentage point spread in rate growth over four years is material. Model it as an expense growth assumption, not a one-time adjustment, and stress it against your exit cap rate. The full 2026 Data Center Impact Report includes downloadable county-level data, and NAR hosts a research summit on data centers and real estate on September 15, 2026 with Yun, Nadia Evangelou, and Terry Clower.
If you are ready to rebuild your expense underwriting around signals like this, The AI Consulting Network specializes in exactly this kind of implementation work.
Frequently Asked Questions
Q: Do data centers increase nearby property values?
A: For commercial property, half of surveyed agents in data center markets said yes, with industrial and land benefiting most. For housing, the evidence is genuinely mixed, with 25% reporting positive effects and 22% negative. NAR explicitly states its research does not support claiming data centers automatically raise or lower nearby values.
Q: Where are U.S. data centers actually concentrated?
A: NAR mapped 1,474 facilities across 251 counties, meaning 92% of U.S. counties have none. Ten counties hold 42% of the total, with Loudoun County alone at roughly 14% and Northern Virginia overall near 19%.
Q: Why does NAR say the home value gap is not proof of a data center effect?
A: Because data centers are sited in counties that already had power, fiber, and educated workforces, the same attributes that independently drive home values and incomes. The $431,750 versus $174,500 gap partly reflects which counties get selected for development rather than what happens after development.
Q: How should CRE investors underwrite data center adjacency?
A: Identify the specific demand mechanism in that submarket, such as construction staging, and verify that rent growth postdates the campus rather than predating it. Treat the demand as potentially temporary, stress utility expense growth, and avoid paying a premium on national correlation alone.