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29% of 2026 US STEM dissertations show AI writing; those graduates less often stay in academia

Study title: How Heavily Are PhD Students Offloading Their Scientific Writing to AI? Evidence from US STEM PhD Dissertations

Evidence type
Observational studyPreprint, not yet peer reviewed
Sample
n = 226,911
Sources
1 sourcePeer-reviewed
Published
3 min read
Truvace record
TRV-2026-2486cite or check it

Study title: How Heavily Are PhD Students Offloading Their Scientific Writing to AI? Evidence from US STEM PhD Dissertations

A working paper from researchers at Duke and the University of Toronto scanned dissertation abstracts from a near-census of about 226,000 US STEM PhD graduates from 2019 to 2026. AI-generated writing was effectively absent before 2023 and appeared in 1.7% of 2023 dissertations, 5.5% in 2024, 18.8% in 2025 and 29.4% in 2026 (filed through May).

Read the study abstract

Large language models are diffusing rapidly into science, raising concerns that delegating research writing to AI may undermine the development of expertise that scientific training is supposed to build. We measure AI-generated writing in the dissertations of a near-census of US STEM PhD graduates from 2019 to 2026 and link graduates to their subsequent employment. AI writing is absent before 2023, present in 29% of dissertations filed in 2026, and rapidly growing. Use is more common among students from non-Engl…

The problem

A working paper covering about 226,000 US STEM PhD graduates found AI-written abstracts in 29.4% of 2026 dissertations, and US-origin graduates with them were 7.4 percentage points less likely to hold academic jobs in 2026.

In brief

Use differed by background and institution. Among 2026 graduates, 41% of dissertations by students educated in non-English-speaking countries had AI-generated abstracts, against 23% for students from English-speaking countries. At R1 universities the share was 28%, versus 37% at other doctoral institutions.

Graduates whose dissertations contained AI writing were less likely to hold academic jobs in 2026 and more likely to work in industry. The authors stress the link is correlational and that it is too early to say whether AI use weakens research training.

Main points

  1. Detector Pangram flagged only six of roughly 126,000 abstracts filed from 2019 to 2022, implying a false positive rate under 0.01%.
  2. In 2026, AI-generated abstracts were most common in mathematical and computer sciences (36%) and engineering (35%), versus life sciences (26%) and physical sciences (22%).
  3. By field, rates ran from 17% in mathematics and statistics to 48% in computer science and 51% in civil engineering.
  4. Among 2025-26 graduates, 15% of top-ten-ranked programs had AI-generated abstracts, versus 22% at programs ranked 40-50 and 26% at programs ranked 90-100.
  5. Rates were 9% at MIT, 10% at Caltech and 13% at Princeton, compared with 30% or more at the ten highest-rate universities.
  6. Among US-origin graduates of R1 universities, AI-written dissertations went with being 8.0 points more likely to work in industry and 5.4 points more likely to hold non-tenure-track academic posts.
  7. At the current growth rate, the authors project a majority of US STEM dissertations will contain AI-generated content by 2028.

The full story

The sample came from ProQuest Dissertations & Theses Global plus university repositories, matching closely the National Science Foundation's Survey of Earned Doctorates: near-complete coverage in life, physical and mathematical sciences and 85% in engineering. The authors applied the Pangram 3.3.2 detector to all abstracts and to 340 randomly sampled full dissertations to check that abstracts track full-text AI use.

Gaps between language groups widened each year. Non-English-speaking students' rate was 2.8% in 2023 against 0.9% for English-speaking students, 8.3% against 3.7% in 2024, and 28% against 14% in 2025. Within the same doctoral program the gap was 11.7 percentage points in 2025-26, largest for students from Iran (23 points), South Korea (15), China (13) and India (11).

Employment was measured through LinkedIn profiles in 2026 for 2023-2025 graduates of R1 universities, compared within the same university and field. Among US-origin graduates, AI-written dissertations went with a 7.4-point lower chance of academic employment and an 8.0-point higher chance of industry employment, with no difference in government jobs. The differences were much smaller for likely foreign-origin graduates.

The authors say AI use also clusters within programs: a 10-point higher rate among the previous year's graduates of a program went with a 3-point higher chance a student's own writing was AI-generated. They note prior experiments finding generative AI helps disadvantaged writers most, so both benefits and costs may be real.

Sources

1 on file
  1. NBER Working Paperdoi:10.3386/w35859
    Peer-reviewed2026-10-01

Talk it over

Four questions to start onWho carries this cost, and what would have to change to prevent it?

Start with a question

29% of 2026 US STEM dissertations show AI writing; those graduates less often stay in academiahttps://truvace.com/item/how-heavily-are-phd-students-offloading-their-scientific-writing-to-ai-evidence-

  1. Who carries this cost, and what would have to change to prevent it?

    The problem A working paper covering about 226,000 US STEM PhD graduates found AI-written abstracts in 29.4% of 2026 dissertations, and US-origin graduates with them were 7.4 percentage points less likely to hold academic jobs in 2026.

    Answer in the thread

  2. How do we know? What can this kind of evidence show, and what can’t it?

    The evidence This rests on an observational study with a sample of 226,911, from NBER Working Paper. It is a preprint, not yet peer reviewed.

    Answer in the thread

  3. What does it leave open? What else would you want to know before acting on it?

    The record’s own caveat The authors say the employment analysis is correlational, not causal, and could reflect students who do not want research careers writing lower-effort dissertations; the paper also says the evidence cannot resolve whether AI use degrades research preparation.

    Answer in the thread

  4. Have you seen AI used this way where you study, work or live? Did it go the same way?

    Answer in the thread

The questions are the same on every record. The details under them are taken from this record as written.

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