LO
Worker adoptionCognitive automation2026-08-11
Language-model use in US federal research proposals rose sharply from 2023 and splits into minimal and substantive use, a PNAS study of confidential and public proposals found
Grant writer / grants officeroccupation page →
Event date / reported
2026-08-11
Evidence stage
Worker adoptionMeasured, large-scale use of a tool for real work, where the decision to use it was the worker's rather than an employer's. It is more than a capability record — the work is real, not a demo — and less than a deployment record, because no employer put it into production, required it, or built a process around it. Weighted `cautious`: `automating` means the machine can do the task AND there are adoption signs, and this is an adoption sign — but usage can be experimental, and much of the measurement comes from a party with a stake, so one record is never enough and two independent ones are. Note who is counting. Vendor telemetry sees this directly and sells the tool, so such a record names that stake in its scope; a statistics agency asking firms whether their workers use AI in tasks sees the same channel with no stake at all, and that is the better source where it exists.
Tasks this bears on
Writing the proposal narrative
Writing the case for support: aims, need, methods, outcomes and why this organisation should be funded.
Being augmented✓ Evidence-backed
Where this applies
United States. Combining confidential NSF and NIH proposal submissions from two large research universities with all public NSF and NIH awards, the study finds language-model use rising sharply from 2023 with a split between minimal and substantive use; higher use is associated with less distinctive projects, and with proposal success at NIH but not at NSF. It measures the researchers who apply, not specialist grant writers.
What this means
AI is already widely used in writing research proposals, and it is making proposals more alike.
What it does not yet show
Researchers' own proposals at two universities plus public awards; specialist grant writers are not measured.
What you can check
Open PubMed record 42579486 and find "LLM use rises sharply beginning in 2023".
Does it change the assessment?
No. The impact index is never moved by a single event. Nor did this record change a layer: all 1 linked judgement above already rested on earlier evidence. This one adds to them.
Source
Qian Y et al. — The rise of large language models and the direction and impact of US federal research funding, PNAS (published 11 August 2026; PubMed 42579486) · verified 2026-10-01 · Claude (VOLO agent) · interpreted 2026-10-01 · Claude (VOLO agent)
Primary source — published by the party that did this, or the authority of record. No co-signature needed.