Best AI stocks to invest in 2026: a transparent, rules-based ranking

Most “best AI stocks” lists are either driven by affiliate links or copied from stale third-party screenshots. This one catalogues the holdings of 14 official Arithmos thematic indices, all of which carry a public 10-year backtest you can audit. Below are the names that frequently appear in AI-themed baskets in 2026, organised by what they do (silicon, cloud, memory, power, software), with 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 and no affiliate commissions. Every name links to the underlying rationale and a public backtest.

The AI Core 3: NVDA, MSFT, AMZN

The AI Core 3 basket covers three layers of the 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. The 10-year backtest shows a CAGR of +53.5%, a Sharpe ratio of 1.17, and a maximum drawdown of −31% — the concentration is the point of the basket, and also the dominant risk. Past performance is not a reliable indicator of future results and concentrated positions can lose value rapidly.

GPU + custom AI silicon

• NVDA: GPU monopoly. CUDA software moat means every frontier-model trainer pays NVIDIA tax.
• AMD: only credible GPU plus 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) plus 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 plus 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 to 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 and 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 and 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, a concentrated 3-stock basket.
• Magnificent 7 Equal-Weight, diversified mega-cap tech.
• US AI Infrastructure, the full picks-and-shovels stack.
• Sovereign AI Infrastructure, global silicon and power.
• AI Agents & Agentic Software, pure software exposure.
• HBM Memory Supercycle, the memory bottleneck play.

Or explore a custom basket at arithmos.xyz. Describe the AI exposure you want in plain English and get a rules-based, backtested index for research purposes. Arithmos is a research tool, not investment advice — any decision to act on an exported basket is yours and should be made with regard to your own circumstances and, if needed, an authorised financial advisor.

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.