AI Infrastructure Investing Hub: Capex Analysis, Risk Screening, and Beneficiary Research
AI infrastructure spending is approaching $500B annually across hyperscalers alone. Our research library covers capex efficiency metrics, depreciation manipulation detection, concentration risk screening, nuclear power for data centers, and supply chain analysis—everything you need to evaluate AI infrastructure investments.
AI Infrastructure Investing Hub
Your central resource for navigating the $500B+ AI infrastructure buildout
AI infrastructure spending is unprecedented in scale and pace. Hyperscalers are investing $370B+ annually, with combined projections approaching $500B by 2026. This creates opportunities—and hidden risks—across the supply chain.
Quick Navigation: Jump to Capex Tracking | Risk Screening | Supply Chain | Nuclear Power | Company Analysis
What You'll Find Here
Our AI infrastructure research library covers:
- Capex Efficiency Framework — Track $370B in hyperscaler spending with 3 key metrics
- Depreciation Manipulation Detection — Identify when companies inflate earnings through accounting
- Concentration Risk Screening — Spot hidden customer and supply chain dependencies
- Supply Chain Analysis — Power generation, equipment makers, data licensing
- Nuclear Power for AI — Utility deal structures, uranium supply chain, and hidden liabilities
- Company Deep Dives — From CAT to Reddit to the Magnificent 7
Featured: AI Capex Tracking Framework
Start here to understand how hyperscalers deploy capital.
Our 3-metric framework monitors AI infrastructure spending quarterly, updated after each earnings report.
How to Track AI Capex Efficiency: 3-Metric Framework
The 3 metrics:
- Capex/Revenue Trend — Is spending growing faster than revenue?
- Capex/Depreciation Ratio — Above 2.5x may signal depreciation manipulation
- Revenue Growth Alignment — Is capex driving proportional growth?
Key findings:
- Amazon has best earnings quality (1.7x ratio, shortened depreciation)
- Google and Meta show concerning ratios (4.3x and 3.5x respectively)
- Michael Burry's $176B depreciation thesis explained
Risk Screening Framework
Data Center Risk Signals
AI Data Center Risk Screen: 4 Signals to Watch
Not all AI beneficiary stocks are equal. This 4-signal framework identifies hidden risks:
- Customer concentration (>10% revenue from single hyperscaler)
- Margin sustainability concerns
- Power availability constraints
- Technology obsolescence risk
Concentration vs Margin Stress Test
AI Beneficiary Stress Test: Concentration vs Margin
When hyperscalers account for a large share of your revenue, you're exposed to:
- Contract renegotiation pressure
- Insourcing risk (hyperscalers building their own)
- Capex cycle dependency
This analysis stress-tests AI beneficiaries for these vulnerabilities.
Supply Chain Analysis
Power Generation
Caterpillar AI Infrastructure: Data Center Power Demand
- CAT's data center segment growing faster than traditional construction
- Diesel generators for backup and peaking power at 1GW+ facilities
- How power constraints are reshaping data center location decisions
ETN vs GEV: The Smarter AI Power Play
- Why Eaton delivers 2x the margin at similar growth with half the execution risk
- GEV trades at 98.9x P/E with 3.57% ROIC vs ETN at 37.3x P/E with 19.09% ROIC
- Multi-company comparison: GEV, ETN, and CAT data center exposure
Fuel Cells
Fuel Cell Stock Quality Divide: BE vs FCEL vs PLUG
- 130-point ROIC spread reveals fundamental quality divide: BE +4.5% vs PLUG -104%
- BE's $288M quarterly Brookfield revenue proves execution; FCEL has $0 quantified data center contracts
- PLUG's "aggressive" accounting rating and $28.1M customer dispute impairments signal distress
- Why 90-day fuel cell deployment beats SMRs' 2029+ timeline for data center operators
Data Licensing
Reddit AI Data Licensing: Revenue Opportunity vs Legal Risk
- Reddit's data licensing revenue from AI training deals
- Legal risks as content creators challenge scraping
- Business model sustainability analysis
Nuclear Power for AI
The nuclear renaissance is being driven by AI data center power demand. Hyperscalers need 24/7 baseload power that's carbon-free for ESG commitments—nuclear is the only scalable solution.
Nuclear Utility Risk Analysis
Nuclear Utility Risk Screen: 3 Filing Red Flags in VST, CEG, and TLN
- Deal structures compared: CEG's 20-year Meta PPA vs TLN's Amazon co-location vs VST's optionality premium
- $510M Moss Landing battery disaster at Vistra—hidden liability in Q3 filing
- 0.9x interest coverage at Talen Energy signals debt stress
- 970bps margin dispersion at Constellation across regions
Uranium Supply Chain
LEU vs CCJ: Why Filing Data Shows Margin Collapse vs Quality Expansion
- LEU's 69% SWU price collapse despite uranium bull market
- CCJ's 530bps margin expansion on contract repricing
- HALEU monopoly positioning: LEU is only US producer of next-gen reactor fuel
- Russia TENEX risk: LEU's license expires 2028—filing disclosure analysis
Small Modular Reactors
OKLO vs SMR: Why the $495M Filing Clue Matters More Than NRC Approval
- $495M paradox: NuScale paid $6.9M per reactor to customers to trigger a non-binding agreement
- NRC moat that wasn't: 18 months post-approval, SMR has one paying customer (100% concentration)
- Cash runway reality: OKLO's $1.18B is uncommitted; SMR has committed future payments
- Investment framework: OKLO = regulatory call option; SMR = execution bet
Company Analysis
Hyperscaler Valuation
Magnificent 7 Valuation Scorecard: December 2025
- Side-by-side valuation metrics for AAPL, MSFT, GOOGL, AMZN, NVDA, META, TSLA
- AI capex intensity comparison
- Which Mag 7 stocks are fairly valued vs stretched
Enterprise AI Platforms
Enterprise AI Earnings Quality: Palantir vs Snowflake
- PLTR's government vs commercial segment analysis
- SNOW's consumption model and cash flow dynamics
- SBC intensity and path to profitability comparison
AI Infrastructure Spending Context
| Company | 2024 Capex | 2025 Capex (Est) | 2026 Guidance | Focus |
|---|---|---|---|---|
| Amazon | $70B+ | $85-90B | Accelerating | AWS, custom silicon |
| Microsoft | $40B+ | $60B+ | Accelerating | Azure, OpenAI partnership |
| $50B+ | $60B+ | Accelerating | Cloud, TPUs, Gemini | |
| Meta | $37B | $71B | $110B (2026) | AI training, Prometheus |
Total hyperscaler AI capex: $366-370B in 2025, approaching $500B in 2026
Key risk: When capex grows faster than revenue for extended periods, either revenue acceleration must follow or returns on invested capital will decline. Track capex/revenue trends quarterly.
How to Use This Research
-
Start with the capex framework — Understand how to track hyperscaler efficiency using our 3-metric system
-
Screen for risks — Apply the 4-signal framework to AI beneficiary stocks
-
Evaluate the supply chain — Understand which companies genuinely benefit vs ride temporary tailwinds
-
Monitor quarterly — AI capex is lumpy; trend matters more than any single quarter
Related Hubs
- ROIC Analysis Hub — Capital efficiency metrics across all sectors
- Earnings Quality Hub — Cash flow and accounting analysis
Related Tools
- Company Screener — Filter by capex intensity and ROIC
- Peer Comparison Tool — Compare hyperscalers side-by-side
- SEC Filing Intelligence — Track capex guidance changes
Keep Learning
This hub is updated as new AI infrastructure research is published. Current coverage: 12 posts across capex, risk screening, nuclear power, fuel cells, and supply chain themes.
Coming soon: Semiconductor supply chain analysis and AI chip maker comparisons.
In This Series (13 articles)
How to Track AI Capex Efficiency: 3-Metric Framework
Learn how to monitor $370B in AI infrastructure spending quarterly with a 3-metric framework. Track capex/revenue trends, depreciation manipulation signals, and growth alignment across Google, Microsoft, Amazon & Meta. Updated December 2025 with Meta's $600B commitment and Michael Burry's depreciation thesis.
AI Data Center Risk Screen: 4 Signals Wall Street Misses (DLR, EQIX, VRT, PWR)
EQIX's capex intensity jumped +8.7pp in 8 quarters. CCI's ROIC collapsed to -12%. ANET's customer concentration is HIGH (Microsoft + Meta). Standard screeners show none of this. Here's our 4-signal framework for screening AI data center infrastructure stocks.
Caterpillar AI Infrastructure: Why E&T Segment Is the Real Growth Story (2025)
While Caterpillar is up +60% YTD, most see it as construction/mining. But CAT's Energy & Transportation segment—which powers AI data centers—is the real growth story at +16.8% YoY with stable 20% margins.
Why ETN Beats GEV: The Smarter AI Power Play (2026)
GE Vernova's Electrification segment grew +32% YoY, but the company trades at 98.9x earnings with a 3.57% ROIC. Eaton's Electrical Americas grew +15% with 30.3% operating margins—twice GEV's margin at half the P/E. MetricDuck data shows why quality beats hype in AI infrastructure.
The Hidden Quality Divide in Fuel Cell Stocks: What ROIC Reveals About BE, FCEL, and PLUG
Three fuel cell companies target AI data center power, but execution quality varies dramatically. Bloom Energy's +4.5% ROIC vs Plug Power's -104% isn't a small difference—it's a fundamental divide between a functioning business and a value destroyer. Our SEC filing analysis reveals warning signs even for the winner.
Reddit's AI Data Licensing: Hidden Revenue and Legal Risk
Reddit is playing both sides of the AI data war: licensing to Google and OpenAI for $130M/year while suing Anthropic and Perplexity. SEC filings reveal 'content licensing agreements' driving 'Other revenue' growth. We analyze the dual strategy, quantify the revenue, and assess the legal risk.
AI Beneficiary Stress Test: Customer Concentration vs Margin Momentum (AVGO, NVDA, ANET, VRT)
AVGO's top 5 customers account for 40% of revenue. NVDA's largest customer is 22%. ANET depends on Microsoft (20%) and Meta (15%). Standard AI stock screens show none of this. Here's our 2-signal framework for stress-testing AI beneficiaries.
Magnificent 7 Valuation Scorecard: December 2025 (Sector-Adjusted Grades)
The Magnificent 7 make up 35% of the S&P 500. But comparing them all using P/E ratios is methodologically flawed—they span 5 distinct business models. Our sector-adjusted scorecard reveals GOOGL as best value (17.4x P/E), TSLA as most overvalued (85% optionality premium), and which stocks actually EARN their premiums.
Enterprise AI Earnings Quality: Palantir (6/10) vs Snowflake (4/10)
Two enterprise AI giants, two very different earnings quality profiles. Palantir (6/10) wins on cash conversion, accounting practices, and litigation risk. Snowflake (4/10) struggles with negative cash conversion (-0.47x) and aggressive software capitalization ($228M). Our 5-pass SEC filing analysis reveals what standard screeners miss.
Nuclear Utility Risk Screen: 3 Filing Red Flags in VST, CEG, and TLN
VST's +321% appreciation prices in nuclear optionality, but ignores a $510M battery fire disaster and antitrust lawsuit. CEG's 'capacity price boom' masks 970bps margin spread between regions. TLN's 0.9x interest coverage means debt service consumes nearly ALL operating income. We analyzed 9 filings to surface what the market overlooks.
LEU vs CCJ 2026: Why Filing Data Shows Margin Collapse vs Quality Expansion
Centrus Energy (LEU) returned 264% in 2025 on the HALEU monopoly thesis. But SEC filings reveal a 69% collapse in core SWU pricing and negative gross profit. Meanwhile, Cameco (CCJ) delivered +88% gross profit growth with 530bps margin expansion.
OKLO vs SMR: Why the $495M Filing Clue Matters More Than NRC Approval
The conventional wisdom says NuScale (SMR) is safer because it has NRC approval. But filing data reveals SMR paid $495M—$6.9M per reactor—to trigger a non-binding customer agreement. OKLO has regulatory uncertainty but uncommitted cash.
Meta's 51% Margin Hides a 20% ROIC Decline. Here's What the 10-K Reveals.
Meta's Family of Apps earns a 51.5% operating margin. Its ROIC is declining at -6.3 points per quarter. Both facts are true simultaneously. The gap between them reveals everything about the largest AI infrastructure bet in advertising history — and the accounting policies designed to make it look cheaper than it is.
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