The prediction is explicitly long‑term: it concerns what will happen “over the coming years and decades” to employment, productivity, and living standards as AI diffuses. Only about six weeks have passed since the podcast’s release (17 Oct 2025 → 30 Nov 2025), far too short to judge decades‑scale claims.

Current evidence is mixed and still emerging:

• Multiple studies (Yale–Brookings, U.S. Census ABS, Fed and think‑tank reports) find that, so far, AI adoption has not caused large net job losses at the aggregate level; most firms report little change in worker numbers, with some retraining and localized displacement instead of mass unemployment. (theguardian.com)
• At the same time, there are meaningful pockets of disruption: higher unemployment and reduced hiring in AI‑exposed, especially entry‑level, white‑collar roles; job cuts explicitly attributed to AI; and concerns about a “jobpocalypse” for new graduates. (en.wikipedia.org)
• Research broadly agrees that AI can generate significant productivity gains at the task and firm level and may already have added a measurable boost to aggregate labor productivity, but the extent to which this will translate into widely shared higher living standards remains uncertain. (stlouisfed.org)

Because (1) the forecast horizon is many years to decades, (2) we are still in the very early stages of widespread AI deployment, and (3) the long‑run balance between displacement, new job creation, productivity gains, inequality, and living standards is not yet observable, there is not enough elapsed time or evidence to classify the prediction as right or wrong. It remains a plausible but untested long‑term scenario rather than a claim that can already be verified or falsified.