Vertiv sits directly in the critical path of AI data-center cooling and power delivery.
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AI data centers need more switchgear, power distribution, and electrical infrastructure, which plays directly into Eaton's strengths.
AI data centers increase demand for grid equipment, gas turbines, electrification, and power services.
AI load growth requires transmission, substation, and grid-hardening work.
| Metric | VRT | ETN | GEV | PWR |
|---|---|---|---|---|
| Price | $302.87 | $391.39 | $940.66 | $707.74 |
| 1D Change | +1.68% | -0.57% | +3.74% | +3.58% |
| Market Cap | $116.34B | $151.98B | $252.77B | $106.20B |
| Enterprise Value | $117.10B | $173.10B | $247.90B | $112.26B |
| Trailing P/E | 75.9 | 38.3 | 27.5 | 96.8 |
| Forward P/E | 34.2 | 24.9 | 38.4 | 43.0 |
| Price / Sales | 10.7 | 5.3 | 6.4 | 3.5 |
| EV / Revenue | 10.8 | 6.1 | 6.3 | 3.7 |
| Revenue Growth | 30.1% | 16.8% | 16.3% | 26.3% |
| Earnings Growth | 135.7% | -9.4% | 1816.5% | 51.0% |
| Gross Margin | 37.2% | 37.1% | 20.3% | 15.1% |
| Operating Margin | 16.4% | 16.1% | 5.5% | 4.2% |
| Net Margin | 14.4% | 14.0% | 23.8% | 3.7% |
| ROE | 45.1% | 20.8% | 75.7% | 13.5% |
| Free Cash Flow | $1.96B | $2.65B | $9.32B | $1.04B |
| FCF Margin | 18.1% | 9.3% | 23.7% | 3.4% |
| Debt / Equity | 0.77x | 1.10x | 0.25x | 0.69x |
| Current Ratio | 1.49x | 1.19x | 0.89x | 1.14x |
| Dividend Yield | 8.00% | 112.00% | 21.00% | 6.00% |
| Next Earnings | Jul 29, 2026 | Aug 04, 2026 | Jul 22, 2026 | Jul 30, 2026 |
| Quarterly Revenue | $2.65B | $7.45B | $9.34B | $7.87B |
| Revenue QoQ | -8.0% | +5.6% | -14.8% | +0.4% |
| Quarterly Net Income | $390.1M | $866.0M | $4.75B | $220.6M |
| Net Income QoQ | -12.5% | -23.5% | +29.5% | -30.1% |
VRT thesis lens
Data-center cooling + power
Why it could benefit
- Vertiv sits directly in the critical path of AI data-center cooling and power delivery.
- As rack densities rise, thermal management becomes as important as the chips themselves.
- The company can benefit whether the bottleneck is cooling, backup power, or rack-level electrical design.
Moat / edge
- Specialized data-center thermal and power know-how.
- Installed base and service relationships.
- Positioning in a fast-growing but technically demanding niche.
What to watch
- Backlog quality and conversion.
- Margins as the product mix shifts toward higher-density AI infrastructure.
- Speed of liquid-cooling adoption.
Key risks
- The stock can be sensitive to order timing and expectations.
- Execution matters when demand ramps quickly.
ETN thesis lens
Grid-to-rack power equipment
Why it could benefit
- AI data centers need more switchgear, power distribution, and electrical infrastructure, which plays directly into Eaton's strengths.
- It benefits from AI even if the winning compute vendor changes.
- This is one of the cleaner ways to own the physical buildout side of the boom.
Moat / edge
- Longstanding position in electrical equipment and distribution.
- Trusted supplier relationships in critical infrastructure.
- Breadth across the power chain.
What to watch
- Data-center order growth and backlog.
- Margin durability as demand stays hot.
- How much AI spending flows into low-voltage and medium-voltage equipment.
Key risks
- A project-driven business can be influenced by timing and mix.
- Any pause in data-center construction can slow growth.
GEV thesis lens
Grid and power equipment
Why it could benefit
- AI data centers increase demand for grid equipment, gas turbines, electrification, and power services.
- GE Vernova gives the dashboard exposure to utility-scale power infrastructure rather than only rack equipment.
- Grid bottlenecks can become as important as GPU availability for new data centers.
Moat / edge
- Large installed base in power generation and grid equipment.
- Service revenue tied to critical infrastructure.
- Exposure to electrification and generation upgrades.
What to watch
- Gas power and grid backlog.
- Margin expansion after separation.
- Data-center-related power demand.
Key risks
- Project execution and warranty issues can hurt margins.
- Policy and utility spending cycles can create volatility.
PWR thesis lens
Grid construction and electrification services
Why it could benefit
- AI load growth requires transmission, substation, and grid-hardening work.
- Quanta is a major contractor for electric power, utility, and energy infrastructure.
- It gives the dashboard exposure to the labor and project layer behind AI power demand.
Moat / edge
- Scale in specialty utility contracting.
- Long relationships with utilities and infrastructure customers.
- Backlog tied to grid modernization and electrification.
What to watch
- Electric power backlog growth.
- Labor availability and project execution.
- Utility capex tied to data-center interconnection.
Key risks
- Weather, labor, and project timing can affect results.
- Infrastructure spending cycles may not map cleanly to AI demand.