AI’s Two‑Speed Progress

Updated: 2025.10.06 15D ago 3 sources
AI looks saturated on many easy, visible tasks (e.g., basic Q&A), so users won’t see dramatic gains there soon. Meanwhile, AI is advancing on hard problems (biosciences, advanced math), but translating those wins into everyday benefits will be slow because of clinical trials, regulation, and adoption frictions. — This frame explains why 'AI disappoints' narratives will proliferate despite real advances, and it steers policy toward fixing deployment bottlenecks rather than doubting capability progress.

Sources

AI adoption rates look weak — but current data hides a bigger story
Ross Pomeroy 2025.10.06 70% relevant
It frames a near‑term 'plateau' in enterprise chatbot use alongside a shift toward agentic systems, aligning with the two‑speed thesis (visible tasks saturated, deeper shifts coming more slowly).
AI Use At Large Companies Is In Decline, Census Bureau Says
BeauHD 2025.09.12 60% relevant
Census BTOS data showing large‑firm adoption dipping while hype and hard‑problem capabilities advance fits the 'two‑speed' notion—visible user benefits stall even as frontier progress continues.
How to think about AI progress
Tyler Cowen 2025.09.11 100% relevant
Cowen: 'progress already is extreme' on easy tasks while bioscience/math gains will be delayed by FDA processes and vaccine hesitancy.
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