Most “best AI stocks” lists are either driven by affiliate links or seven-month-old ChatGPT screenshots. This one comes from the holdings of 14 official Arithmos Research thematic indices, all of which carry a public 10-year backtest you can audit. Below: the names that actually drive the AI economy in 2026, organised by what they do — silicon, cloud, memory, power, software — and links to the indices they power.
How we picked them
Three filters. (1) The company must derive a majority of its 2026 revenue or revenue growth from AI workloads or the infrastructure powering them. (2) It must be US-listed (or an ADR with daily liquidity). (3) It must show up as a top-weight in at least two of our official AI-themed indices. No paywalled picks, no affiliate commissions — every name links to the underlying rationale and a public backtest.
The AI Core 3: NVDA, MSFT, AMZN
If you only own three AI stocks, own these. They cover the full stack: the silicon (NVIDIA), the model + enterprise distribution (Microsoft + OpenAI), and the cloud + Anthropic stake (Amazon). Equal-weighted, this 3-stock basket is the AI Core 3 Index and has returned a 10-year CAGR of +53.5% with a Sharpe ratio of 1.17.
GPU + custom AI silicon
- NVDA — GPU monopoly. CUDA software moat means every frontier-model trainer pays NVIDIA tax.
- AMD — only credible GPU + server-CPU challenger. MI300/MI325 ramping with hyperscalers.
- TSM — sole foundry making leading-edge chips for NVIDIA, AMD, Apple, Broadcom.
- AVGO (Broadcom) — custom AI ASICs (Google TPU, Meta MTIA) + AI cluster networking silicon.
- MRVL — Amazon Trainium custom-silicon partner; 800G optical DSPs.
- ARM — CPU IP inside every smartphone and most data-center ARM servers.
- ASML — EUV lithography monopoly. No advanced chips ship without ASML machines.
- AMAT, LRCX, KLAC — wafer fab equipment oligopoly enabling everything above.
See the Pure Semiconductor Monopoly and AI Infrastructure Max Concentration indices for ready-made baskets.
Hyperscale + cloud
- MSFT — Azure + OpenAI partnership; broadest enterprise AI distribution.
- AMZN — AWS leader; Trainium/Inferentia silicon; Anthropic stake.
- GOOGL — Google Cloud + TPU silicon advantage + Gemini frontier model.
- ORCL — fastest-growing AI training cloud (OCI capacity sold out).
- CRM — Agentforce platform monetising AI agents inside enterprise CRM.
HBM memory supercycle
Memory is the new bottleneck for AI accelerators. HBM3E and HBM4 supply is sold out through 2026.
- MU (Micron) — only US HBM supplier; ramp into NVIDIA Blackwell.
- SK Hynix (via EWY Korea ETF) — largest HBM supplier globally.
- Samsung Electronics (via EWY) — returning to HBM leadership.
Power, cooling, and grid
Hyperscaler data centers are eating 10–20% of US electricity by 2030. The picks-and-shovels of AI power:
- VRT — Vertiv: liquid cooling and power management for AI data centers.
- ETN — Eaton: switchgear and electrical infrastructure.
- CEG — Constellation Energy: largest US nuclear fleet powering hyperscale deals.
- VST — Vistra: Texas IPP with growing data-center contracts.
- GEV — GE Vernova: gas turbines + grid systems.
- PWR — Quanta Services: T&D contractor wiring up AI campuses.
- MOD — Modine: liquid cooling distribution units.
AI software + agents
- PLTR — Palantir AIP: AI-native enterprise + defense software.
- NOW — ServiceNow Now Assist embedded in enterprise workflows.
- CRM — Salesforce Agentforce.
- SNOW — Snowflake: cloud data platform powering AI workloads.
- DDOG — Datadog: LLM observability.
- MDB — MongoDB: standard for AI agent applications.
Risks and what we left out
We deliberately left out:
- Pure-play AI startups not yet public (OpenAI, Anthropic, xAI). You can’t buy them.
- Speculative SPACs with “AI” in the name but no AI revenue.
- China AI names with US delisting risk (BIDU is the closest exception).
- Quantum computing — covered separately in our Quantum Computing Vanguard Index.
Build your own AI stock basket
The fastest path: pick one of these as a starting point.
- AI Core 3 Index — concentrated 3-stock basket.
- Magnificent 7 Equal-Weight — diversified mega-cap tech.
- US AI Infrastructure — full picks-and-shovels stack.
- Sovereign AI Infrastructure — global silicon + power.
- AI Agents & Agentic Software — pure software exposure.
- HBM Memory Supercycle — memory bottleneck play.
Or build your own: arithmos.xyz — describe the AI exposure you want in plain English and get a rules-based index back in seconds.
FAQ
Is NVIDIA still the best AI stock to own?
On a fundamental basis, NVIDIA’s GPU + CUDA moat remains the deepest in the AI economy. But it’s also at peak concentration in most portfolios. Diversifying into AVGO, AMD, and TSM gives similar economics with less single-name risk.
What about smaller AI stocks?
Small-cap AI exposure tends to be very volatile. We cover it via the AI Drug Discovery, Robotaxi & Autonomy, and Edge AI & Inference indices, where small caps make more sense.
How often do these picks change?
We re-screen every official index quarterly. New entrants (e.g. a public listing of Anthropic, if it ever happens) would be reviewed for inclusion at the next rebalance.