Best Practices
Understanding AI Energy Impact
Key facts about AI energy consumption and why efficiency matters.
4 min readUpdated Feb 1, 2026
Understanding AI Energy Impact
Key facts about AI energy consumption.
The Numbers
| Metric | Value | Source |
|---|---|---|
| AI query vs search | 10× energy | TechTarget |
| Data center CO₂ (2025) | 79.7M tonnes | Euronews |
| US data center water (2023) | 17B gallons | Pew Research |
| Global demand by 2030 | 945 TWh | IEA |
Why It Matters
- Data centers use 4%+ of US electricity
- AI is the fastest-growing compute category
- Energy costs are passed to consumers
- Environmental impact compounds globally
What You Can Do
Individuals:
- Use AI intentionally, not habitually
- Choose efficient tools when possible
- Batch requests to reduce overhead
Organizations:
- Audit AI usage patterns
- Implement caching and optimization
- Choose appropriate model sizes
- Set usage policies and limits