AI Race Facts.Facts. Not fear.
A clear, sourced look at the data behind America's AI infrastructure — data centers, power consumption, water usage, and how the United States compares with China in the global AI race.
Why This Site Exists
I started building this site because the intense protests against new AI data centers didn't make sense. Other major industries — especially agriculture — use far more water and power, often with significant waste and exports. There appeared to be coordinated opposition, so I began digging into the numbers.
This is what I found:
AI data centers consume a tiny fraction of U.S. water and electricity compared to agriculture, residential use, and traditional power generation. Yet they face outsized resistance while the United States risks falling behind in the global AI race — particularly against China's aggressive buildout of its own infrastructure.
This site presents the facts, with clear sources from government reports and academic research. No hype. No agenda. Just data to help people understand what's really at stake.
Water usage, in context
AI data centers use a tiny fraction of U.S. freshwater. Agriculture and thermoelectric power are orders of magnitude larger — and a meaningful share of agricultural water grows food that is wasted or exported.
Direct water consumption by U.S. data centers in 2023 for cooling.
U.S. agricultural irrigation water in 2023 — about 1,500× data centers.
Share of U.S. food production that is never eaten — and the water that grew it.
Annual U.S. freshwater withdrawals by sector
| Category | Annual Water Use | Notes |
|---|---|---|
| Data Centers (Direct Cooling) | ~17.4 billion gallons | 2023 |
| Agriculture (Irrigation) | ~26.4 trillion gallons | 81 million acre-feet |
| Thermoelectric Power | ~51 trillion gallons | USGS, latest |
| Food Waste Portion | 30–40% of production | Water used for food never eaten |
| Agricultural Exports | ~20% of production | Includes water-intensive crops |
Agriculture withdraws over 1,500× more water than data centers — much of it supporting food that is wasted or exported.
Power usage: the real numbers
Data center electricity demand is growing — but remains a single-digit share of U.S. consumption. Residential and commercial buildings together still dwarf data centers.
U.S. data center electricity consumption — about 4.4% of total U.S. electricity.
Still less than residential + commercial buildings combined.
Used by residential buildings alone — far above all data centers.
U.S. data center electricity consumption (TWh)
AI infrastructure is essential industrial capacity — comparable to power plants and factories. Growth is real, but the share remains modest.
AI energy efficiency: rapid progress
While total demand is rising, the energy required per AI task continues to drop dramatically thanks to better models, hardware, and software optimization.
Energy for a typical text query (e.g. Gemini) — roughly 9 seconds of TV watching.
Performance-per-watt improvement across recent generations of AI accelerators (e.g. Google TPU).
Drop in median prompt energy reported by Google over a single year of model and serving optimization.
Energy per AI query vs. everyday tasks
Hardware efficiency gains: AI accelerator generations
Energy per AI task is falling faster than overall demand is rising in many workloads — efficiency is doing real work alongside new capacity.
US vs China: the global AI buildout
While the U.S. debates new data center capacity, China continues rapid expansion of its own AI infrastructure, grid, and chip supply.
Estimated AI-related data center capacity (TWh equivalent)
China added more new power generation capacity in 2023 than the U.S. has in the last decade.
China's hyperscale data center footprint is growing roughly twice as fast as the U.S.
Winning the AI race requires building the infrastructure — power, water, and compute — today.
Foreign influence & long-term consequences
Ongoing congressional investigations are examining whether China-linked funding has supported U.S. nonprofits opposing AI data centers. The strategic stakes extend well beyond local zoning fights.
House Ways and Means Committee Chairman Jason Smith has stated that Chinese money has been traced to U.S. nonprofits organizing protests against data centers, with the goal of slowing American AI development.[1]
What if China wins the AI race?
- China would likely control the dominant AI chips, models, and software standards for decades.[2]
- Future smartphones, computers, cars, medical equipment, and critical infrastructure worldwide could run on Chinese-controlled technology.[3]
- The U.S. would shift from setting global AI rules to operating within systems shaped by a strategic competitor.[4]
Projected cost & technology landscape if China leads
Many devices could become more affordable due to Chinese manufacturing scale — but at the cost of technological dependency.
| Device category | U.S. / Western price | China-equivalent price | Implications |
|---|---|---|---|
| iPhone 17 (base / Pro) [5] | $799–$1,099+ | ¥4,499–¥6,999 (~$622–$968) | Consumer electronics cheaper globally; reliance on Chinese supply chains and standards. |
| Premium Chinese smartphone (Xiaomi / Huawei flagship) [6] | $700–$1,000+ (imported) | $650–$850 equivalent | Price/performance edge expands; Chinese brands set global benchmarks. |
| Handheld ultrasound [7] | $2,000–$4,000 | $950–$2,500 | Medical devices 40–60% cheaper, improving access but increasing reliance. |
| Patient monitors (hospital-grade) [8] | $5,000–$15,000+ | $1,000–$5,000 equivalent | Production costs 20–60% lower; widespread hospital adoption. |
| Surgical robot (da Vinci-class) [9] | $1.8M–$2.5M + ~$100K–$190K/yr | $200K–$1M (Surgerii, Jingrong) | 60–90% lower upfront + reduced ongoing costs. |
| Automotive FSD / ADAS hardware [10] | Tesla HW4: ~$800–$1,500; 100–150 TOPS | Horizon J6 / XPeng: $300–$800; 560+ TOPS | Higher compute at lower cost; vehicles dependent on Chinese tech stack. |
See references [5]–[10] below for pricing and hardware sources.
The broader long-term picture
Everyday devices, medical equipment, and vehicles become more accessible.[11]
Loss of control over critical AI-driven systems in phones, cars, hospitals, and infrastructure.[12]
National security, data privacy, and innovation leadership shift toward China.[13]
Domestic opposition to infrastructure carries real strategic costs. America must address legitimate local concerns while protecting its ability to lead in AI for generations.
Strategic Risk citations
- [1]U.S. House Committee on Ways and Means — Chairman Jason Smith, public statements and committee hearings on foreign-linked funding of U.S. nonprofits opposing AI data centers (2024–2025).
- [2]Center for Strategic and International Studies (CSIS) — "Full Stack: The Evolution of the U.S.–China AI Rivalry" (2024); Stanford HAI AI Index Report 2024.
- [3]U.S.–China Economic and Security Review Commission — Annual Report to Congress (2023, 2024), sections on AI integration in consumer electronics, autos, and medical devices.
- [4]National Security Commission on Artificial Intelligence — Final Report (2021); Brookings Institution, "Global AI governance and the risk of bifurcation" (2024).
- [5]Apple Inc. — iPhone 17 official U.S. pricing (apple.com, 2026); Apple China store pricing (apple.com.cn, 2026).
- [6]Counterpoint Research — Global Smartphone Premium Market reports (2025); Canalys Smartphone Analysis (2025).
- [7]Grand View Research — Handheld Ultrasound Market Size Report (2024); Mindray, Chison, and SonoStar published price lists; FDA 510(k) device database.
- [8]GlobalData Medical Devices Intelligence — Patient Monitoring Market Report (2024); Mindray and Edan Instruments published product pricing.
- [9]Intuitive Surgical — 2024 Annual Report (10-K), da Vinci system pricing and service revenue; Surgerii Robotics and Jingrong Surgical public pricing disclosures (2025).
- [10]Horizon Robotics — Journey 6 product specifications (2025); Tesla AI Day disclosures on HW4 (2023); Munro & Associates / Nikkei Asia ADAS hardware teardowns (2024–2025).
- [11]McKinsey Global Institute — "The state of AI in 2024"; OECD, "AI, data, and competition" (2024).
- [12]U.S. Department of Defense — 2024 Annual Report on Military and Security Developments Involving the PRC; CISA, "Securing the ICT Supply Chain" (2024).
- [13]Office of the Director of National Intelligence — Annual Threat Assessment of the U.S. Intelligence Community (2024).
Methodology & references
All figures on this site are drawn from U.S. government agencies, national laboratories, and peer-reviewed analyses. Numbers are rounded for clarity.
- Lawrence Berkeley National Laboratory — 2024 U.S. Data Center Energy Usage Report
- U.S. Department of Energy — Data Centers and Energy Reports
- U.S. Geological Survey — Estimated Use of Water in the United States
- USDA NASS — Irrigation and Water Management Survey, 2023
- USDA Economic Research Service — Food Loss and Waste
- International Energy Agency — World Energy Outlook 2024
- U.S. Energy Information Administration — Annual Energy Outlook
- Synergy Research Group — Hyperscale Data Center Tracker