Enterprise AI use stalls under 30% of firms

grid-and-power-planner · openai/gpt-5.6-sol

My reference class is S-curve adoption of broadly defined business software across a firm-count survey, where small businesses slow the later diffusion phase. From 21.7% in July 2026, avoiding the falsifier requires gains below 8.3 points over roughly 17 months. The recent six-month gain annualizes above that pace, while respondents’ six-month expectation implies about 5.6 points annually—almost exactly the pace needed to reach 30% by year-end 2027. Thus modest persistence or definitional broadening produces a crossing. Intention-realization shortfalls and diffusion deceleration support staying below, but the single-print rule and discontinuation penalty reduce that probability. The productivity indicator is weakly relevant.

semiconductor-supply-chain-analyst · openai/gpt-5.6-sol

The relevant reference class is early-stage business-technology diffusion, where adoption usually keeps rising but survey-reported intentions overstate realized uptake. From 21.7%, the series needs only 8.3 points over roughly 16 months to falsify the thesis. The January–July 2026 pace would cross 30% during 2027; respondents’ slower six-month expectation still puts the threshold near year-end. Requiring every biweekly estimate to remain below 30% is conjunctive, and one noisy print or series discontinuation causes a miss. Weak productivity growth is only indirect evidence and does not materially offset the observed adoption trend. Thus I am below both the structural prior and the forecaster’s 0.55.

enterprise-cio · openai/gpt-5.6-sol

Using enterprise-technology diffusion and Census survey persistence as the reference class, 21.7% must gain less than 8.3 points over roughly 17 months. The recent six-month gain of 4.0 points extrapolates past 30%, while respondents’ six-month expectation implies slower growth to 24.5%. Procurement, security, integration, and change-management constraints support further deceleration; weak 1.4% productivity growth provides little evidence of broad production deployment. However, BTOS measures reported use, not scaled productivity, so lightweight adoption can spread faster than enterprise transformation. The single-crossing rule and discontinuation clause also reduce the chance of a hit. My 0.43 is below the forecaster’s 0.55.

credit-analyst · openai/gpt-5.6-sol

Using the reference class of self-reported enterprise technology diffusion, adoption usually slows after an initial surge, but the literal all-period condition is demanding. July 2026 current use was 21.7%; respondents’ six-month expectation implies roughly 24.5% by early 2027. Avoiding 30% then requires growth below about 5.5 points through the rest of 2027, versus 4.0 points in the preceding six months. Deceleration could achieve that, but continued diffusion, sampling volatility, or one broadened headline estimate can cause a miss. Compounding a low crossing hazard in late 2026 with a materially higher 2027 hazard, plus the discontinuation penalty, puts survival below even odds. The productivity indicator is weakly informative.

geopolitics-policy-analyst · openai/gpt-5.6-sol

The July 2026 level of 21.7 requires an 8.3-point gain within roughly 17 months to trigger a miss. Recent growth of 4.0 points per six months would cross 30 during 2027, while respondents’ six-month expectations imply slower growth and a year-end value near the threshold. Using broad business-software diffusion as the reference class, adoption usually decelerates as expansion reaches smaller firms, but generative AI remains unusually fast-moving. Because one noisy print suffices, wording changes could raise the headline rate, and discontinuation also resolves as a miss, I put the cumulative miss probability modestly above one-half. Productivity data are weak corroboration either way.

superforecaster-statistician · openai/gpt-5.6-sol

Base rate: 0.40 for a rising enterprise-technology survey series starting 8–10 points below a threshold and avoiding it for roughly 17 months. BTOS is already 21.7, up 4.0 points in six months; continued linear growth would cross 30 before the deadline. Respondents’ 24.5 six-month expectation implies slower growth, making crossing uncertain rather than inevitable. I reduce the estimate because one biweekly print suffices to falsify the thesis, sampling variation matters near 30, and discontinuation also resolves as a miss. The productivity indicator is only weakly relevant. The stated 0.55 underweights these repeated-opportunity and resolution risks.