Impact of AI Data Centers on Communities

Written by: San Jose CAN
July 15, 2026

The rapid expansion of AI data centers will support advances in medicine, scientific research, and other fields. However, it will also create significant environmental, infrastructure, and community challenges. The extent of these impacts will depend on factors such as the size of the facility, the cooling technology used, local climate, electricity source, and the availability of water.

1. Massive Electricity Consumption

AI data centers consume far more electricity than traditional data centers because AI model training and inference require thousands of GPUs operating continuously.

Potential consequences include:

Higher demand on the electrical grid.
Greater risk of power shortages during peak demand if grid upgrades do not keep pace.
Increased electricity costs in some regions.
Need for new transmission lines and substations.
Increased reliance on natural gas or other fossil-fuel power plants where renewable energy is insufficient.

Many large AI facilities require hundreds of megawatts of electricity. Some proposed campuses exceed one gigawatt, comparable to the electricity demand of a medium-sized city.

2. Extremely High Water Consumption

Many AI data centers use evaporative cooling to remove heat from servers.

Water use varies significantly depending on:

Outside temperature
Humidity
Cooling technology
Workload
Time of year

Large AI data centers can consume millions of gallons of potable water per day in hot weather.

Important facts:

Water that evaporates during cooling generally does not return directly to the local water supply.
Once evaporated, it enters the atmosphere as water vapor and becomes part of the natural hydrologic cycle.
That water is no longer immediately available for local drinking water, agriculture, or reservoirs.

Communities experiencing drought or limited water supplies may face increased competition for drinking water resources.

3. Increased Greenhouse Gas Emissions

Unless powered entirely by carbon-free electricity, AI data centers increase carbon emissions.

Additional emissions come from:

Natural gas generation
Diesel backup generators
Construction
Manufacturing servers and GPUs
Concrete and steel production

Although many companies purchase renewable energy, demand is growing faster than new renewable generation in many regions.

4. Air Pollution

Data centers themselves produce relatively little direct air pollution.

However:

Backup diesel generators emit particulate matter.
Nitrogen oxides contribute to smog.
Carbon monoxide is released.
Carbon dioxide emissions occur during testing and emergency operation.

Some campuses operate dozens of large diesel generators.

5. Noise Pollution

Large facilities operate continuously.

Noise sources include:

Cooling towers
Industrial fans
Chillers
Transformers
Backup generator testing

Nearby residents sometimes report:

Constant humming
Low-frequency vibration
Sleep disturbance
Reduced quality of life

6. Heat Released Into the Environment

Nearly all electricity consumed eventually becomes heat.

Large AI data centers release enormous amounts of waste heat.

Possible impacts include:

Local warming
Increased cooling demand nearby
Urban heat island effects
Higher air temperatures immediately surrounding facilities

Waste heat recovery systems exist but remain relatively uncommon.

7. Heavy Pressure on Local Infrastructure

New AI campuses often require:

Larger electrical substations
New transmission lines
Water system upgrades
Sewer improvements
Road widening
Fiber optic expansion

Much of this infrastructure is paid for through combinations of private investment and public utility upgrades.

8. Land Use Impacts

Modern AI campuses can occupy hundreds of acres.

Potential impacts include:

Loss of open space
Removal of trees
Habitat fragmentation
Increased stormwater runoff
Larger paved surfaces

Construction also generates significant dust and traffic.

9. Limited Permanent Employment

Construction creates many temporary jobs.

However, once operational, most data centers employ relatively few permanent workers compared with their size.

Many facilities operate with:

Engineers
Security staff
Facility technicians
Network specialists

Large campuses often employ only a few dozen to a few hundred full-time workers.

10. Increased Demand for Rare Minerals

AI hardware requires materials including:

Copper
Cobalt
Nickel
Lithium
Rare earth elements

Mining these materials can cause:

Habitat destruction
Water contamination
Large energy consumption
Human rights concerns in some regions

11. Electronic Waste

AI hardware becomes obsolete rapidly.

Servers are replaced every few years.

This generates:

Electronic waste
Metal waste
Plastic waste
Circuit board disposal challenges

Proper recycling is improving but remains incomplete worldwide.

12. Water Supply Conflicts

In drought-prone regions, communities have raised concerns about whether drinking water should be allocated to industrial cooling.

Potential conflicts involve:

Residents
Agriculture
Parks
Schools
Future housing developments

These issues have become more prominent in parts of the western United States.

13. Grid Reliability Concerns

Very large AI facilities can add hundreds of megawatts of demand over a relatively short period.

Utilities may need years to build:

New substations
Additional transmission capacity
New generating facilities

Without adequate planning, rapid load growth can strain electrical systems.

14. Environmental Justice Concerns

Lower-income communities are sometimes disproportionately affected by:

Industrial development
Noise
Traffic
Diesel emissions
Utility infrastructure

These communities may receive fewer direct economic benefits than the burdens they experience.

15. Increased Truck Traffic During Construction

Construction of major campuses can last several years.

This brings:

Heavy equipment
Concrete trucks
Steel deliveries
Large cranes
Increased road congestion
Construction dust

Common Claims That Need Context

“AI data centers use 5 million gallons of water every day.”

This is not true for every AI data center.

The amount depends on:

Facility size
Cooling technology
Climate
Season
AI workload

Some very large campuses may approach or exceed several million gallons per day under certain conditions, while many others use much less.

“Eighty percent of the water evaporates.”

For facilities using evaporative cooling, most of the water consumed is intentionally evaporated as part of the cooling process. The exact percentage varies by cooling system and operating conditions, so there is no universal 80% figure. Water that evaporates leaves the local water system and joins the atmosphere through the natural water cycle rather than flowing back into local reservoirs or pipes.

The Bottom Line

AI data centers can provide important benefits, including supporting scientific research, healthcare, communications, economic development, and advanced computing. At the same time, they can impose substantial local costs if not carefully planned.

The primary concerns supported by current evidence are:

Very high electricity demand.
Potentially large potable water consumption, especially with evaporative cooling.
Increased greenhouse gas emissions where clean energy is unavailable.
Noise and heat generation.
Pressure on electrical, water, and transportation infrastructure.
Limited long-term employment relative to the scale of investment.
Electronic waste and increased demand for critical minerals.
Potential environmental justice and community impacts.

Because these facilities can have long-lasting effects on local resources, many experts recommend that governments require transparent disclosure of projected electricity demand, water consumption, cooling methods, emissions, infrastructure needs, environmental impacts, and long-term mitigation measures before approving new AI data center developments.