1. Hyperscaler spending is exploding and accelerating. The "hyperscalers" are the giant cloud companies that buy most AI hardware. Per Goldman Sachs (June 2026), Meta, Microsoft, Amazon and Alphabet "collectively plan to allocate $725 billion to capital expenditures in 2026 — up a staggering 77% from last year's already record-breaking $410 billion." Looking further out, Goldman now expects a combined $5.3 trillion of capex for those same four hyperscalers from fiscal 2025 to fiscal 2030 (raised from a $4.5 trillion estimate before Q1 2026 earnings). Individually for 2026, Amazon guided to about $200 billion in capex, Alphabet to $175–190 billion, Meta to $115–135 billion, and Microsoft toward roughly $145–190 billion (depending on calendar vs. fiscal-year framing). The key point for investors: this is a multi-year buildout, and the companies repeatedly say they are "supply-constrained," not "demand-constrained."
2. The "picks and shovels" idea. In the 1849 Gold Rush, the people who reliably made money weren't the miners — they were the ones selling picks, shovels, and jeans. Same idea here: instead of guessing which AI model wins, you can own the companies that sell the tools every AI company must buy.
NVIDIA (NVDA) — The undisputed king. NVIDIA makes the GPUs (graphics chips) that train and run most AI. Per Silicon Analysts (April 2026), "NVIDIA commands approximately 80-90% of the AI accelerator market by revenue as of 2025," with its share peaking near 87% in 2024 and projected to ease toward 75% by 2026 as rivals scale. In its fiscal year 2026 (ended January 2026), revenue hit about $216 billion with net income of about $120 billion, and data center revenue alone was $197 billion. Gross margins are around 75% — extraordinary. Quality: Top-tier. Hugely profitable, tons of cash, dominant moat (its CUDA software locks in developers).
AMD (Advanced Micro Devices, AMD) — The clear #2, though with only about 5–8% of the merchant AI accelerator market. Makes EPYC server CPUs and Instinct AI GPUs (the MI300/MI350 line). Full-year 2025 revenue was a record $34.6 billion, up 34%, with GAAP net income of $4.3 billion. Landed a big deal to supply OpenAI with 6 gigawatts of GPUs. Quality: High. Profitable and growing fast, though far smaller than NVIDIA in AI chips and with lower margins.
Intel (INTC) — The struggling giant. Once dominant in chips, Intel now holds under 1% of the AI accelerator market. It lost money in 2024 and has had a rough stretch, though it returned to a quarterly profit in Q3 2025 (helped by U.S. government funding and a deal where NVIDIA invested $5 billion in Intel stock at $23.28 per share). Quality: Turnaround story / lower quality. Weakest balance sheet and profitability of the big three; more speculative.
Also worth mentioning — TSMC (Taiwan Semiconductor, TSM) — The company that actually manufactures the chips. Almost every advanced AI chip (NVIDIA, AMD, Broadcom, even Apple) is physically made by TSMC. In 2025 it earned about $55 billion in net income on $122 billion in revenue, with gross margins near 60%. Quality: Top-tier. The ultimate "picks and shovels" name — it wins regardless of which chip designer wins. Main risk is its location in Taiwan (geopolitical).
AI chips need special high-speed memory called HBM (High Bandwidth Memory). Only three companies make it at scale, and it's sold out well into the future. Bank of America (cited by SK hynix) estimates the 2026 HBM market will reach $54.6 billion, a 58% increase over 2025, and calls 2026 "a supercycle similar to the boom of the 1990s."
SK Hynix (Korea; 000660.KS, also trades over-the-counter as HXSCL) — The HBM leader. Per Counterpoint Research, "SK hynix now has 62% of the HBM chip market supply, Samsung's share fell to 17% in Q2 2025, while US-based Micron holds 21%." It is NVIDIA's main HBM supplier. In 2025 it posted record full-year revenue of ₩97.15 trillion (about $68 billion) and record profit of ₩42.95 trillion (about $30 billion), driven by HBM revenue that "more than doubled year-on-year" — overtaking Samsung in annual operating profit for the first time. Quality: High. The clear winner of the memory supercycle.
Micron (MU) — The only U.S.-based maker, with about 21% HBM share. Fiscal 2025 (ended August 2025) revenue was $37.4 billion with $8.5 billion net income; momentum is huge, with fiscal Q1 2026 revenue of $13.6 billion and $5.2 billion net income. It exited consumer memory (shutting its Crucial brand) to focus on AI. Quality: High and improving. Easiest way for U.S. investors to play HBM directly.
Samsung (Korea; 005930.KS, OTC SSNLF) — The biggest memory maker overall but the laggard in HBM (about 17% share) after quality issues qualifying chips with NVIDIA. Quality: Solid but mixed. Huge, diversified, profitable company, but trailing in the highest-value AI memory.
REITs (Real Estate Investment Trusts) own the actual buildings. They benefit from AI demand and usually pay dividends.
Equinix (EQIX) — The world's interconnection leader with 270+ data centers and 500,000+ connections. Q4 2025 bookings jumped 42% year-over-year; 60% of its largest Q4 deals were AI-driven. Plans to spend $4–5 billion a year through 2029. Quality: High. Profitable, premium franchise, dividend-paying.
Digital Realty (DLR) — Owns the big campuses used to train AI; 300+ data centers. Signed its largest-ever hyperscale lease and grew Q1 2026 revenue 16%. Quality: High. Strong, though carries more hyperscaler concentration.
Iron Mountain (IRM) — Best known for records storage, but its data center business is the growth engine — revenue grew about 30% in 2025 with a 52% profit (EBITDA) margin. Quality: Good, but higher debt. A diversified way in; leverage is on the higher side (about 5x).
The real bottleneck for AI is electricity. Robert Schein, Chief Investment Officer at Blanke Schein Wealth Management, estimates "$1.4 trillion is needed just for AI Data Center Electrification by 2030." (Separately, an April 2026 PowerLines analysis of 51 U.S. investor-owned utilities found planned capex of "at least $1.4 trillion on capital projects through 2030.")
Vertiv (VRT) — Makes the cooling and power systems inside data centers. 2025 revenue about $10.2 billion (up 28%), net income $1.3 billion (up 169%), with orders up 81%. Quality: High. Strong profits, manageable debt, huge backlog.
Eaton (ETN) — Makes the electrical equipment (switchgear, power management) for data centers. CEO Paulo Ruiz Sternadt said on the Q4 2025 call that the backlog "is also over 200% up, and it equates to eleven years of what was built in 2025," with data center orders up about 200% in Q4. 2025 net profit margin was near 15% with strong free cash flow. Quality: Top-tier. Big, stable, dividend-paying industrial.
Constellation Energy (CEG) — The largest U.S. nuclear operator, signing long-term power deals with Meta (a 20-year deal for the full output of its Clinton plant), Microsoft, and CyrusOne. Bought Calpine to become the largest private-sector power producer in the world. Quality: High. Strong cash flows from long-term contracts, though earnings can swing.
Vistra (VST) — Texas-based power producer (gas, nuclear, renewables) signing data center deals. Q3 2025 revenue about $5 billion with 21% operating margins. Quality: Good but volatile. Strong growth, but a higher valuation and more execution risk.
NRG Energy (NRG) — A power producer that was the S&P 500's biggest gainer in 2025. Partnering with GE Vernova and Kiewit to build over 5 gigawatts of gas-fired power for data centers. Quality: Improving. Turned strongly profitable; more of a momentum/turnaround story.
Also worth mentioning — GE Vernova (GEV) — Makes the gas turbines and grid equipment to power data centers, with multi-gigawatt deals (Chevron, NRG, NextEra) and a fast-growing backlog. Quality: High and improving.
AI data centers connect tens of thousands of chips, which requires massive high-speed networking.
Arista Networks (ANET) — The leader in high-speed Ethernet switches for AI data centers; it has overtaken Cisco in data center switching. Full-year 2025 revenue hit $9 billion (up 29%), and it raised its 2026 AI networking target to $3.25 billion. Quality: Top-tier. Very profitable, no debt, strong growth. Note: about 48% of revenue comes from cloud/AI customers, so it's concentrated.
Broadcom (AVGO) — A powerhouse. It makes custom AI chips (XPUs) for Google, Meta, and others, plus the Ethernet switch chips (Tomahawk/Jericho) that nearly every AI network uses. Q1 FY2026 AI revenue guided to $8.2 billion (doubling year-over-year); total AI order backlog about $73 billion. EBITDA margins around 67%. Quality: Top-tier. Hugely profitable, though it carries more debt from acquisitions (like VMware).
Marvell (MRVL) — Provides custom-chip building blocks (high-speed connections) for AWS and Microsoft's in-house chips. Data center grew to about 75% of revenue. Quality: Good. Growing fast on AI, but more dependent on a few customers.
ETFs let beginners own many of these names at once. These focus on hardware/infrastructure, not AI software:
(Tip for the newsletter: ETF assets and top holdings shift over time, so it's worth a quick same-day check on each issuer's official fund page before publishing exact figures.)
For a beginner-friendly newsletter, I'd structure picks in three tiers:
Benchmarks that would change the thesis: Watch hyperscaler capex guidance each quarter — if Microsoft, Amazon, Alphabet, and Meta start cutting capex, the whole "picks and shovels" trade weakens. The 77% jump to $725 billion for 2026 is the green light; a flat or falling number would be the warning sign. Also watch memory prices (a sign of the cycle turning) and any shift in company language from "supply-constrained" to "demand-constrained."