Across the April 2024–roughly October 2025 window Jason pointed to (“five quarter ten”), there is no evidence that the effective cost of white‑collar knowledge work broadly fell by about 90% (to 10% of its prior level) due to AI.

Evidence from firm- and task-level studies:

• A Stanford/MIT field experiment on a large customer-support operation found that giving agents a generative‑AI assistant raised productivity about 14% on average (up to ~35% for the least‑skilled), implying on the order of a ~10–25% effective labor‑cost reduction for that task, not 90%. (cnbc.com)
• A synthesis by the Penn Wharton Budget Model, summarizing multiple real‑world gen‑AI deployments, reports task‑level labor cost savings in the 10–55% range, with an average of roughly 25%, and projects those savings might rise toward 40% over coming decades—still far from a 90% reduction. (budgetmodel.wharton.upenn.edu)
• A controlled experiment with ~750 BCG consultants using GPT‑4 showed about 40% performance improvement on certain knowledge‑work tasks, again implying substantial but nowhere‑near‑10x cost improvements, and only for specific task types, not all white‑collar work. (bcg.com)

Adoption and average impact across workers:

• A Federal Reserve Bank of St. Louis study using late‑2024 survey data finds that only about 21.8% of U.S. workers used generative AI in the previous week; among those users, reported time savings averaged 5.4% of work hours, and when averaged over all workers, the gain was only 1.4% of total hours—orders of magnitude away from a 90% cost collapse. (stlouisfed.org)
• PwC’s 2025 Global Workforce survey reports that as of 2025 only 14% of workers use gen‑AI daily, with about half of workers having used AI at all in the prior 12 months, underscoring that intensive AI leverage is still limited to a minority of the workforce. (pwc.com)

Macro productivity data:

• U.S. nonfarm business labor productivity—a broad proxy for output per hour—rose 1.2% in 2023 and then around 2–3% in 2024, far from the ~900% jump in efficiency that would accompany a 90% drop in effective labor cost for most white‑collar work. (bls.gov)

Taken together, current evidence suggests:

• Generative AI has produced meaningful but incremental productivity and cost gains for many knowledge‑work tasks (often in the 10–50% range in controlled or early‑adopter settings).
• Adoption and intensity of use remain partial, so economy‑wide effects on white‑collar knowledge work costs are modest, not transformative at 10x scale.
• By the end of the roughly 1–2.5 year window from April 2023, neither micro‑level studies nor macro statistics support a ~90% reduction in the effective cost of knowledge work.

Because the prediction was both quantitatively extreme (90% drop) and time‑bound to a window that has now passed, and available data show much smaller, partial gains, the prediction is best classified as wrong.