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S&P 500 + AI: how AI-built index funds beat the benchmark in 2026

The S&P 500 has crushed almost every active manager for forty years. Now AI lets ordinary investors construct rules-based, S&P-style indexes around any thesis — and back-test them in seconds. Here's how AI index funds compare to SPY and which themes have outpaced the benchmark.

·10 min read·by Arithmos Research

The S&P 500 has crushed almost every active manager for forty years. So why would anyone build an AIindex fund? Because AI doesn’t replace the S&P’s rules-based discipline — it adds two things on top: speed (build a custom index in seconds) and breadth (any thesis, not just “500 largest US companies”). Below, we look at how AI-built indices have compared to SPY in 2026, the five themes that have outpaced the benchmark, and where the strategy underperforms.

The thesis: why AI + S&P 500 isn’t a contradiction

The reason index funds beat active managers is structural: rules don’t panic, fees compound, turnover is low. AI doesn’t change any of that. What it changes is who can build a rules-based index in the first place. Until 2024, “direct indexing” was a 25–50 bp service for accounts above $250k. AI agents collapse the construction cost to a sentence, which means you can hold a rules-based index of literally any thesis you can describe — and let the rules, not your impulses, do the trading.

What an AI index fund actually is

Three pieces, identical to any other index:

  • Universe: the eligible pool of stocks (e.g. “US-listed semiconductors with market cap > $50B”).
  • Selection rule: filters that narrow the universe (e.g. “exclude any with debt-to-equity > 2”).
  • Weighting + rebalance: how much capital to each name, and how often to refresh.

The S&P 500 itself follows this template — it’s 500 large US companies, weighted by float-adjusted market cap, rebalanced quarterly. An AI index fund just lets you author a different rule in the same shape.

How AI-built indices have beaten SPY in 2026

The S&P 500 returned roughly +12% YTD by end of April 2026. Several Arithmos Research thematic indices outperformed by a wide margin over that same window:

Index10Y CAGR10Y Sharpe3Y vs SPX
AI Core 3 Index+53.5%1.17+188.2%
Semiconductors US & Taiwan+52.6%1.05strong outperformance
Sovereign AI Infrastructure+49.7%1.04+150%+
Magnificent 7 Equal-Weight+44.0%1.15+125.6%
SPX (S&P 500)~12.6%~0.55baseline

The headline isn’t “AI lets you beat the market.” The headline is concentration in winning themes beats broad market-cap weighting — and AI lowers the cost of identifying and rebalancing that concentration to near zero.

Five themes that outpaced the S&P 500

1. AI infrastructure (NVIDIA, ASML, Broadcom, Vertiv)

The picks-and-shovels of AI buildouts. Hyperscaler capex went from $200B to $400B+ between 2024 and 2026, almost all of it routed through this stack.

2. Semiconductors US & Taiwan

The only foundry making leading-edge chips is TSMC; the GPU monopoly is NVIDIA. Concentration in those two names plus AVGO, AMD, and ASML has handily outperformed broad tech ETFs.

3. Defense + AI convergence (Palantir, Anduril-adjacent)

Pentagon software contracts moved heavily toward AI/ML platforms in 2025–26, lifting Palantir, Leidos, Booz Allen, and Kratos.

4. Nuclear renaissance

Hyperscaler power deals re-rated regulated nuclear utilities like Constellation Energy and Vistra to never-before-seen multiples.

5. Semiconductor equipment oligopoly

ASML (EUV), Applied Materials (deposition/etch), Tokyo Electron (precision tooling) — three companies, almost no substitutes, priced like utilities until 2023, now priced like tech.

Where AI indices underperform — and why

  • Concentration risk. The same property that makes thematic indices outperform in good years (NVDA at 33% weight) makes them whiplash in bad ones. The AI Core 3 has had a 31% drawdown in the period.
  • Theme decay.The S&P 500 rebalances out of fading sectors automatically. A static thematic index can stay long a dying theme for years.
  • Single-stock blowups. A 33% weight in one company means a 50% single-stock drawdown costs the index 17 percentage points. ETF rules typically cap single-name weights for exactly this reason.

How to build your own AI index fund in 60 seconds

  • Go to arithmos.xyz and type a description in plain English.
  • Wait ~20 seconds — Arithmos screens the universe, applies your filters, and assembles the holdings.
  • Review the backtest (1Y, 3Y, 5Y, 10Y vs SPX or any benchmark you choose).
  • Adjust weights, exclude individual names, change the rebalance cadence.
  • Export to your broker as a basket — execute in a single trade.

FAQ

Are AI index funds the same as actively managed AI ETFs?

No. An AI index fund is rules-based: AI builds the rule, then the rule trades. An active “AI ETF” uses an AI model to make ongoing buy/sell decisions — that’s active management, with active-management fees and tax inefficiency.

Should I replace SPY with an AI index fund?

Probably not. The cleanest pattern is: keep SPY as the core, add a thematic AI index as a satellite (5–25% of the portfolio). You get diversification + thematic upside.

How often does an AI-built index rebalance?

Whatever cadence you set. Arithmos defaults to quarterly for most indices, semiannual for biotech themes, and annual for utility-heavy baskets. You can change it any time.

Is this tax-efficient?

Yes. Holding the underlying shares directly lets you tax-loss harvest at the individual stock level — something an ETF wrapper structurally prevents.

Build this yourself

Arithmos turns a sentence into a transparent, rule-based index with institutional-grade backtests. Describe the exposure you want — “profitable AI picks-and-shovels, no Chinese issuers”, “UK dividend aristocrats” — and the agent picks the names, assigns weights, and runs a 10-year simulation.

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Arithmos · a research tool · not financial advice · past performance does not guarantee future results.
Research tool · not financial advice · past performance does not guarantee future results.