The Energy Cost of Artificial Intelligence

A comprehensive analysis of methodologies, applications, and sustainability challenges in AI data centers. Global electricity demand is projected to double to 945 TWh by 2030.

Global Demand 2030

945 TWh

+127%from 2024 baseline

Avg PUE

1.5

Industry averageTarget: <1.2 (High Efficiency)

Inference Load

60%

Of total lifecycle energyDominates training costs

Grid Risk

HIGH

Capacity gap wideningInfrastructure lag: 5-10 yrs

Pink Hydrogen ROI Model

Project financial performance for Nuclear-Thermal Coupled Electrolysis

INVESTOR TOOL

SMR Reactor Cost ($M)$500M

SOEC Electrolyzer Cost ($M)$150M

H2 Market Price ($/kg)$4.5

Production Rate (tons/day)50t

Total CAPEX$650M

Est. Annual Revenue$82.1M

Payback Period

> 10 Years

10-Year IRR

N/A

Net Profit (10y)

$-251M

Global Consumption Projections

Electricity consumption by region (TWh)

Ashburn, VA

Dublin, IE

Singapore

Frankfurt

Tokyo

Silicon Valley

London

Mumbai

LIVE_MONITOR: ACTIVE

Lifecycle Energy

Contribution by stage (%)

Insight: Inference dominates lifecycle energy at 60% despite low per-query consumption due to massive scale.

Cooling Tech

Explore liquid and immersion cooling solutions that can reduce cooling energy by up to 50%.

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Sustainability

Investigate renewable integration, nuclear power strategies, and carbon emission mitigation.

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Hardware

Analyze the evolution of AI accelerators and the shift towards "Intelligence per Watt" metrics.

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