Rise of Generative Artificial Intelligence in Science
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Abstract (arXiv)
Generative Artificial Intelligence (GenAI, generative AI) has rapidly become available as a tool in scientific research. To explore the use of generative AI in science, we conduct an empirical analysis using OpenAlex. Analyzing GenAI publications and other AI publications from 2017 to 2023, we profile growth patterns, the diffusion of GenAI publications across fields of study, and the geographical spread of scientific research on generative AI. We also investigate team size and international collaborations to explore whether GenAI, as an emerging scientific research area, shows different collaboration patterns compared to other AI technologies. The results indicate that generative AI has experienced rapid growth and increasing presence in scientific publications. The use of GenAI now extends beyond computer science to other scientific research domains. Over the study period, U.S. researchers contributed nearly two-fifths of global GenAI publications. The U.S. is followed by China, with several small and medium-sized advanced economies demonstrating relatively high levels of GenAI deployment in their research publications. Although scientific research overall is becoming increasingly specialized and collaborative, our results suggest that GenAI research groups tend to have slightly smaller team sizes than found in other AI fields. Furthermore, notwithstanding recent geopolitical tensions, GenAI research continues to exhibit levels of international collaboration comparable to other AI technologies.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 12 of its 60 references that are in the map. First posted on arXiv 30 Dec 2024.
Builds on
12 of 60 references.
References · 12
- 2017Attention Is All You Needcited by 59,932
- 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
- 2022OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and conceptscited by 166
- 2023Generative AIcited by 119
- 2023GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Informationcited by 115
- 2023ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishingcited by 51
- 2022"I think this is the most disruptive technology": Exploring Sentiments of ChatGPT Early Adopters using Twitter Datacited by 32
- 2023The Potential Impact of AI Innovations on U.S. Occupationscited by 5
- 2024AI Knowledge and Reasoning: Emulating Expert Creativity in Scientific Researchcited by 3
- 2023Has China caught up to the US in AI research? An exploration of mimetic isomorphism as a model for late industrializerscited by 2
- 2024The Global AI Vibrancy Toolcited by 2
- 2023Collaboration and topic switches in sciencecited by 1
Built on by
Citing papers per year: 2025: 3; 2026: 2.
5 papers.
- 2025Academic journals' AI policies fail to curb the surge in AI-assisted academic writingcited by 12
- 2025Generative AI and the future of scientometrics: current topics and future questionscited by 1
- 2025Generative AI in Science: Applications, Challenges, and Emerging Questionscited by 1
- 2026Useful for Exploration, Risky for Precision: Evaluating AI Tools in Academic Researchcited by 1
- 2026Scientific exploration, collaboration and labor division in the large language model eracited by 0
- 2026Scientific exploration, collaboration and labor division in the large language model era23 Jul 2026
- 2026Useful for Exploration, Risky for Precision: Evaluating AI Tools in Academic Research11 May 2026
- 2025Academic journals' AI policies fail to curb the surge in AI-assisted academic writing7 Dec 2025
- 2025Generative AI in Science: Applications, Challenges, and Emerging Questions11 Jul 2025
- 2025Generative AI and the future of scientometrics: current topics and future questions1 Jul 2025