Academic journals’ AI policies fail to curb the surge in AI-assisted academic writing

Checked 30 Sept 2026. Non-commercial or no-derivatives license: full text kept internally; only metadata and abstract are indexed and used.

The rapid integration of generative AI into academic writing has prompted widespread policy responses from journals and publishers. However, the effectiveness of these policies remains unclear. Here, we analyze 5,114 journals and over 5.2 million papers to evaluate the real-world impact of AI usage guidelines. We show that despite 70% of journals adopting AI policies (primarily requiring disclosure), researchers' use of AI writing tools has increased dramatically across disciplines, with no significant difference between journals with or without policies. Non-English-speaking countries, physical sciences, and high-OA journals exhibit the highest growth rates. Crucially, full-text analysis on 164 k scientific publications reveals a striking transparency gap: Of the 75 k papers published since 2023, only 76 (~0.1%) explicitly disclosed AI use. Our findings suggest that current policies have largely failed to promote transparency or restrain AI adoption. We urge a reevaluation of ethical frameworks to foster responsible AI integration in science.

• Disclosure of LLM use is rare: Fortenbach et al. (2026) found no disclosure among ophthalmic publications with outlier scores, and He & Bu (2026) found only 76 of 75 thousand post-2023 papers explicitly disclosed AI use. Trace →
• He & Bu (2026) report that journal AI policies, adopted by 70% of journals and mostly requiring disclosure, made no significant difference to growth in AI writing-tool use. Trace →
• Across independent datasets, AI-assisted writing is almost never disclosed. He & Bu 2026 find that only 76 of 75k post-2023 papers (~0.1%) disclosed AI use. Fortenbach et al. 2026 find no disclosure among any ophthalmology publications with outlier AI-likelihood scores. Trace →
• He & Bu 2026 report that journal AI policies, mostly disclosure requirements, have not curbed adoption. Growth in AI writing-tool use showed no significant difference between journals with and without policies. Trace →
• Estimated LLM uptake varies widely by context. Kobak et al. 2025 find differences across disciplines, countries, and journals, reaching 40% in some subcorpora. He & Bu 2026 find the highest growth in non-English-speaking countries and physical sciences. Lee et al. 2025 cite 6.5% to 16.9% LLM modification of AI-conference peer reviews but no significant evidence in Nature journals. Trace →
• Language support is a recurring rationale for LLM use and may bear on where adoption grows fastest. Kobak et al. 2025 and Bietti & Bangerter 2026 both note help for writing in English. He & Bu 2026 observe the highest growth in non-English-speaking countries. Trace →
• Two large studies independently document a near-total transparency gap: He & Bu 2026 found only about 0.1% of 75,000 post-2023 papers explicitly disclosed AI use, and Fortenbach et al. 2026 found no disclosure in any ophthalmology publication flagged with outlier AI scores. Trace →
• He & Bu 2026 show that journal AI policies have so far been ineffective: although 70% of 5,114 analyzed journals adopted AI policies, mostly requiring disclosure, AI writing-tool use grew dramatically with no significant difference between journals with and without such policies. Trace →
• Kobak et al. 2025 measured LLM use in biomedical writing at an unprecedented scale, analyzing over 15 million PubMed abstracts from 2010–2024 and estimating that at least 13.5% of 2024 abstracts were processed with LLMs, with the lower bound reaching 40% in some subcorpora. Trace →
• He & Bu 2026 find that despite 70% of journals adopting AI policies, researchers' use of AI writing tools has increased dramatically across disciplines, with no significant difference between journals with or without policies. Trace →
• Non-disclosure emerges across studies using different methods: He & Bu 2026 found that of 75,000 papers published since 2023, only 76 (~0.1%) explicitly disclosed AI use, while Fortenbach et al. 2026 found that AI use was not disclosed among any ophthalmology publications with outlier AI-likelihood scores. Trace →
• The language-equity rationale for LLM-assisted writing recurs across papers: Kobak et al. 2025 note that LLMs can help translate to English, Bietti & Bangerter 2026 note that LLMs can support non-native English speakers by reducing linguistic barriers, and He & Bu 2026 find that non-English-speaking countries exhibit the highest growth rates in AI writing tool use. Trace →
• He & Bu 2026 conclude that journal AI policies have largely failed: analyzing 5,114 journals and over 5.2 million papers, they find 70% of journals adopted policies (primarily requiring disclosure), yet AI writing tool use rose with no significant difference between journals with and without policies, and only about 0.1% of papers published since 2023 disclosed AI use. Trace →
• Independent corpora converge on an AI transparency gap: He & Bu 2026 find that among 75,000 papers published since 2023 only 76 (~0.1%) disclosed AI use, while Fortenbach et al. 2026 report that none of the ophthalmology publications with outlier AI-likelihood scores disclosed their AI use. Trace →
• Although AI-assisted writing is now common, disclosure of it is nearly nonexistent: He & Bu 2026 found almost no explicit disclosures in 75,000 recent papers, and Fortenbach et al. 2026 found none at all among ophthalmology publications flagged as likely AI-written. Trace →
• Journal AI policies have so far been ineffective at changing author behavior: He & Bu 2026 show that despite 70% of journals adopting AI policies, mostly requiring disclosure, AI writing tool use grew just as much in journals with policies as in those without. Trace →
• The democratizing promise of LLMs for non-native English writers, acknowledged even by critics such as Bietti & Bangerter 2026, is consistent with He & Bu 2026's large-scale finding that non-English-speaking countries exhibit the highest growth rates in AI-assisted writing. Trace →
• Disclosure is almost entirely absent even where LLM use is detected: He & Bu 2026 found only about 0.1% of post-2023 papers disclosed AI use despite most journals having policies, and Fortenbach et al. 2026 found no disclosure among any publications with outlier scores, indicating current policies fail to promote transparency. Trace →

• Research integrity and LLMs