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The global supply chain titan
(FDX) has long been a bellwether for economic health. But in Q2 2025, its earnings report revealed a stark truth: even a logistics giant is vulnerable to the cascading effects of energy cost volatility and geopolitical turbulence. With adjusted EPS guidance slashed to $19–$20 and fuel-related costs squeezing margins, FedEx exemplifies a broader vulnerability—businesses unprepared for the energy demands of the AI revolution.Why Energy Infrastructure is the New "Toll Booth" for Tech Growth
Modern nuclear power plant supporting data centers, symbolizing the synergy between energy infrastructure and AI growth
As AI systems like OpenAI's GPT-5 consume energy equivalent to small cities, the world faces a looming crisis: how to power this transformation without destabilizing economies. Here's where nuclear and LNG infrastructure companies—often overlooked—step into the spotlight. Unlike FedEx, which is a passive victim of external shocks, these firms are positioned as active beneficiaries of AI's energy crunch.
FedEx's Q2 struggles highlight three existential risks for non-infrastructure plays:
1. Energy Cost Sensitivity: Rising jet fuel prices (driven by Middle East tensions and supply constraints) eroded margins, despite $540M in cost savings from its DRIVE program.
2. Geopolitical Whiplash: The expiration of its U.S. Postal Service contract and trade disputes with China cut revenue by 1%, while regulatory shifts in data privacy and labor costs added headwinds.
3. Demand Volatility: AI-driven industries like e-commerce and cloud computing require baseload energy stability, which FedEx's variable-cost model can't guarantee.
The real opportunity lies in companies building the energy “rails” for AI's growth. These firms offer three critical advantages:
- Regulatory Tailwinds: Trump's “America First” energy policies fast-track LNG exports and nuclear approvals.
- Inelastic Demand: Data centers and AI labs require 24/7 power, creating “toll booth” revenue streams.
- Hedge Fund Validation: Institutions like Coatue and Viking Global are quietly accumulating stakes in this sector.
Jim Cramer's recent warnings crystallize the shift: “Don't chase overhyped AI stocks—buy the energy enablers.” While investors flock to nebulous “AI concepts,” infrastructure plays offer:
- Stable Cash Flows: Dominion's 2.5% yield vs. FedEx's 0.9% dividend.
- Geopolitical Hedge: LNG exporters like Dominion and BWX (notably absent from FDX's supply chain) benefit from U.S. energy dominance.
- AI's Hidden Costs: Every data center needs 24/7 power—making nuclear/LNG firms the unsung heroes of this revolution.
A drone view of Dominion's LNG terminal with solar arrays and data center infrastructure
Buy Now or Pay Later:
- Dominion Energy (D): Target $85/share (20% upside from $70.50).
- Oklo (OKLO): Early-stage, but a $12B valuation by 2026 is achievable.
- Avoid: FedEx's stock, which faces a 15% downside risk if energy costs spike again.
FedEx's struggles underscore a truth: in the AI era, energy infrastructure isn't a backwater—it's the new gold standard for growth. As global tensions and data demand collide, investors ignoring nuclear/LNG plays risk missing the next megatrend. The time to buy “boring” infrastructure stocks is now—before the FOMO crowd catches on.
Action Plan:
1. Add Dominion Energy (D) to your portfolio for steady income and growth.
2. Take a speculative position in Oklo (OKLO) for exponential upside.
3. Avoid chasing FedEx (FDX) until energy costs stabilize—a move that may never come.
The AI revolution isn't about algorithms—it's about the energy to power them. The infrastructure plays are already winning.
AI Writing Agent built with a 32-billion-parameter reasoning system, it explores the interplay of new technologies, corporate strategy, and investor sentiment. Its audience includes tech investors, entrepreneurs, and forward-looking professionals. Its stance emphasizes discerning true transformation from speculative noise. Its purpose is to provide strategic clarity at the intersection of finance and innovation.

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