WireSift
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AI Adoption Tracker · S&P 500 · Q1 2026 · n = 301
28 of 301 report AI monetization. Outside tech, just 4.

A live research project that tracks and analyzes real-time AI adoption disclosure across the S&P 500.

AI Adoption Level
Silent
Exploring
Piloting
Scaling
Monetizing
S&P 500 Overall
n = 299
71
46
56
98
28
Information Technology
n = 49
Communication Services
n = 4
Financials
n = 53
Consumer Discretionary
n = 19
Health Care
n = 29
Utilities
n = 12
Real Estate
n = 25
Industrials
n = 61
Energy
n = 11
Materials
n = 14
Consumer Staples
n = 21
Healthcare
n = 3

Tap any segment to see the companies and their verbatim quotes.

Outside tech, just 4
Only 4 monetizersare non-tech: Equinix and Welltower (data-center-adjacent REITs), Blackstone and S&P Global (data & infrastructure financiers). All tech-adjacent picks-and-shovels.
The silent
71 companies (24%) said nothing about AI on their earnings call. Over half of Consumer Staples were silent (Coca-Cola, Philip Morris, Hershey, General Mills) — and 15 Industrials skipped AI too (UPS, Honeywell, Norfolk Southern, Delta).
WireSift Research · 301 of 503 S&P 500 reported · as of 2026-05-01Editorial: Tesla as Tech (FSD, Optimus, robotaxi); Amazon as Tech (AWS dominates AI commentary); Alphabet as Tech (Cloud, Search, Workspace); Meta as Tech (AI infra, Llama, AR/VR); Alphabet Class A (GOOGL) consolidated into Class C (GOOG).
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AI Supplier Leaderboard · S&P 500 · Q1 2026 · n = 301
NVIDIA leads. OpenAI is not first.

Across 301 S&P 500 earnings calls, NVIDIA — a chip vendor — is the most-named AI partner at 22. OpenAI (21) is tied with Anthropic (21) for second. Google sits at 19.

Tap any supplier to see the companies and the source data.

WireSift Research · 301 of 503 S&P 500 reported · as of 2026-05-01Counts the number of distinct S&P 500 companies that named each supplier on their Q1 2026 earnings call. Top 8 shown.
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The question

Everyone says AI is transformative.
What are companies actually telling investors under oath, and how specific are they?

AI commentary on earnings calls is dense, narrative-heavy, and hard to compare across companies. This project runs every S&P 500 earnings transcript through a structured extraction pipeline, producing a comparable dataset of every AI claim management makes — speaker, role, section, specificity score (1–5), and the verbatim quote.

The dataset answers questions the headlines can't: who is quantifying real AI revenue (vs. forward-looking metrics), what analysts ask that management refuses to answer, and how AI exposure varies sector to sector. Updated as new calls land.

The framework

Three buckets of AI exposure.

Across 301 companies, the AI conversation splits cleanly along the dominant type of exposure: who's supplying the buildout, who's using AI internally, and who's selling AI as part of their product. Each bucket maps to a distinct set of sectors.

customer_demand_signal

Suppliers to the buildout

Selling power, real estate, fuel, and physical materials to the AI buildout. Not building AI — landlording it.

Dominant in
  • Real Estate
  • Energy
  • Utilities
  • Materials
internal_use

Internal productivity

Using AI inside the company for productivity. No AI products to sell. Largely banks, telecom, and packaged-goods companies.

Dominant in
  • Communication Services
  • Consumer Staples
  • Financials
product_embedded · product_standalone

AI in products

AI inside the products being sold to customers — software, medtech, industrial automation. The cohort with the most quantified revenue stories.

Dominant in
  • Information Technology
  • Health Care
  • Industrials
Early findings · Q1 2026

What 301 calls reveal so far.

Each finding is sourced to the underlying transcript. Click into the full report (forthcoming) for verbatim quotes, methodology, and the full per-company breakout.

T1
1 of 23

Of 23 companies disclosing AI revenue, only Broadcom reports it as a GAAP segment — $8.4B, +106% YoY.

Q1 2026
T1
NVIDIA: 22

NVIDIA named as AI partner by 22 S&P 500 companies — alone at the top. OpenAI (21) tied with Anthropic for second.

Q1 2026
T1
1,280

Disclosure gaps — analyst questions management would not quantify.

Q1 2026
T2
“Almost irrelevant”

MSCI's CFO: AI is so embedded across the product line that breakouts are meaningless.

MSCI Q1 2026 call
Methodology · v2.2

Auditable. Cross-validated. Versioned.

  • Single-pass extraction via Claude Sonnet 4.6. Every claim must be backed by a verbatim quote that exists in the source transcript.
  • Cross-model validation on a 10% random sample using Claude Opus 4.6. Aggregate agreement: 80% on substantive judgments.
  • Schema versioned with semver. Old extractions are never deleted; methodology changes are logged in the public changelog.
  • Quality gates run on every extraction — quote integrity, scope coherence, and schema compliance. Flags surface for manual review.
Open methodology — schema and prompts published at github.com/adjdunn/ai-earnings-research
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The chart above updates as new earnings calls land. Each significant finding ships to subscribers first — sourced, sized, and on the record.