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AI maturity by bucket · S&P 500 Q1 2026 · as of 2026-05-25

2 in 3 non-tech S&P 500 companies aren't past piloting on AI

Q1 2026 earnings calls · share of companies at each AI maturity stage

Techn = 71
Non-techn = 392
Monetizing
Scaling
Piloting
Exploring
Silent
20%40%60%
0%
20%40%60%
% of companies in bucket

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

WireSift Research · S&P 500 Q1 2026 earnings transcripts · n = 71 Tech (incl. reclassifications: AMZN, TSLA, GOOG, META, ABNB, DASH) and 392 Non-tech (all other S&P 500 sectors). Stage taxonomy per WireSift methodology. Both sides normalized to 100% within bucket.
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Key Takeaways
  • 65% of Tech S&P 500 companies say AI is generating attributable revenue. Outside Tech the share is 4%, a 16.9x gap.
  • Tech and Non-tech occupy different ends of the same maturity curve: 93% of Tech is scaling or monetizing, while 64% of Non-tech sits in silent + exploring + piloting.
  • 97 non-tech S&P 500 companies (25%) did not mention AI once on their Q1 2026 earnings call. Only 2 Tech companies were silent.
  • Scaling is the only stage where the two buckets meet: 28% of Tech and 32% of Non-tech. At every other stage one bucket dominates.
  • The "AI is everywhere" framing reads as true in language but holds in fewer than 61 of the S&P 500 companies disclosed under monetization. 46 of those are Tech.

Two different AI economies inside the S&P 500

The chart above is a population pyramid: Tech on the left (in blue), Non-tech on the right (in orange), stages stacked from monetizing at the top to silent at the bottom. The shape of each side IS the finding. Tech mass concentrates on the top two rows; Non-tech mass concentrates on the bottom three. The two buckets are roughly the same size at scaling and diverge everywhere else.

Pre-attentively, this reads as one image with two different curves. Read in isolation, a Tech earnings call sounds like the AI economy is well underway. Read across the S&P 500, the picture is the opposite: 64% of non-Tech companies are still pre-deployment, and a quarter of them never said the word "AI" at all.

The monetization gap

46 of 71 Tech companies disclose AI-attributable revenue (65%). Outside Tech, 15 of 392 do (4%). That is a 16.9x ratio. The headline AI-monetization narrative is real, but the cohort that supports it is small and concentrated. Of the named monetizers outside Tech, most fall into two patterns: AI-infrastructure suppliers whose buildout is driving demand (utilities serving hyperscalers, REITs hosting data centers, infra contractors), and software-adjacent product companies embedding AI features inside an existing subscription (S&P Global, IQVIA, Welltower, Axon, News Corp).

The pre-deployment majority outside Tech

Non-tech distribution: 25% silent (97 companies), 17% exploring (68), 22% piloting (87), 32% scaling (125), 4% monetizing (15). The peak is at scaling, but a thicker left tail than right tail. Silent + exploring is the largest combined segment of the non-tech bar; that share is the audience that AI vendors have not yet converted into anything quantifiable.

Where the two buckets meet

Scaling is the convergence point: 28% Tech vs 32% Non-tech. Both buckets place roughly a third of their companies here. The difference shows up in what comes next. Tech's next move is monetization (65%); the non-tech equivalent share is the next-most-common destination at just 4%. The pipeline narrows sharply going into the revenue stage outside Tech.

Supporting Data

AI maturity distribution within bucket, S&P 500 Q1 2026

StageTechNon-tech
Monetizing65% (46)4% (15)
Scaling28% (20)32% (125)
Piloting1% (1)22% (87)
Exploring3% (2)17% (68)
Silent3% (2)25% (97)
Total71 companies392 companies
Methodology

Stages (silent / exploring / piloting / scaling / monetizing) reflect the highest AI maturity observed across every AI mention on a company's Q1 2026 earnings call. The 'Tech' bucket combines GICS Information Technology with editorial reclassifications (AMZN, TSLA, GOOG, META, ABNB, DASH) whose AI economics are tech economics; 'Non-tech' is every other S&P 500 sector. Both buckets normalized to 100% within bucket so the comparison reads as distribution shape, not absolute counts. Extraction is run by the WireSift AI Adoption Tracker pipeline (Claude Sonnet 4.6, schema v2.1, prompt v2.3); every claim traces to a verbatim quote in the source transcript.

Read the full methodology →

Sources
  • Tier 2S&P 500 Q1 2026 earnings call transcripts · Regulated disclosures, hosted on company IR sites
  • Tier 2SEC filings · 10-Q segment disclosures and GICS sector classifications
  • Tier 2WireSift AI Adoption Tracker extraction pipeline · Schema v2.1, prompt v2.3, Claude Sonnet 4.6, verbatim-quote provenance on every record

Data as of 2026-05-25Embed: https://wiresift.com/embed/tech-vs-nontech