AI focus categories tracked
7
In this index
AI Workload Types
Separate training, inference, mixed-use, and general cloud facilities.
AI focus pages turn a broad infrastructure dataset into something more analytically useful by showing which facilities are oriented toward training clusters, inference fleets, or mixed workloads.
Facilities covered
276
80% of full index
Tracked capacity
102.3 GW
Selected MW in this taxonomy
Largest AI focus
Mixed
144 facilities
How To Read This Taxonomy
This taxonomy is one lens on a live dataset covering 346 AI data centers across 64 countries and 225 tracked operators.
What does AI focus add beyond operator and geography?
It distinguishes facilities designed for frontier-model training from those aimed at inference, cloud spillover, or mixed workloads, which changes how readers interpret hardware and power demand.
When is this slice especially useful?
Use it when tracking where dense GPU clusters may emerge, where low-latency inference capacity is being built, or how providers balance AI-specific demand with general cloud infrastructure.
Related Lenses
Cross-check this slice with adjacent taxonomies to see how geography, operator concentration, status, and power sourcing interact.
All AI focus categories
| AI focus | Facilities ↓ | Countries | Capacity | Operational | |
|---|---|---|---|---|---|
| Mixed | 144 | 42 | 63.5 GW | 92 | |
| Inference | 41 | 29 | 5.4 GW | 32 | |
| Training | 39 | 13 | 23.4 GW | 19 | |
| General Cloud | 34 | 24 | 5.2 GW | 16 | |
| HPC / Supercomputing | 8 | 8 | 403.1 MW | 5 | |
| Sovereign AI | 7 | 6 | 4.4 GW | — | |
| Research | 3 | 3 | 68 MW | 3 |
Mixed63.5 GW
144 facilities42 countries92 operational
Inference5.4 GW
41 facilities29 countries32 operational
Training23.4 GW
39 facilities13 countries19 operational
General Cloud5.2 GW
34 facilities24 countries16 operational
HPC / Supercomputing403.1 MW
8 facilities8 countries5 operational
Sovereign AI4.4 GW
7 facilities6 countries
Research68 MW
3 facilities3 countries3 operational
Frequently asked questions
- What does AI focus add beyond operator and geography?
- It distinguishes facilities designed for frontier-model training from those aimed at inference, cloud spillover, or mixed workloads, which changes how readers interpret hardware and power demand.
- When is this slice especially useful?
- Use it when tracking where dense GPU clusters may emerge, where low-latency inference capacity is being built, or how providers balance AI-specific demand with general cloud infrastructure.