Generative Artificial Intelligence for Academic Research: Evidence from Guidance Issued for Researchers by Higher Education Institutions in the United States

To address these concerns, many Higher Education Institutions ( HEI s) have released institutional gui dance for researchers . To better understand the guidance that is being provided we report findings from a thematic analysis of guidelines from thirty HEIs in the United States that are classified as R1 or "very high research activity. " We found that guidance provided to researchers: 1) asks them to refer to external sources of information such as funding agencies and publishers to keep updated and use institutional resources for training and education; 2) asks them to understand and learn about specific GenAI attributes that shape research such as predictive modeling, knowledge cutoff date, data provenance, and model limitations, and about ethical concerns such as authorship, attribution, privacy, and intellectual property issues; 3) incl udes instructions on how to acknowledge sources and disclose the use of GenAI, and how to communicate effectively about their GenAI use, and alerts researchers to long term implications such as over reliance on GenAI, legal consequences, and risks to their institutions from GenAI use. Overall, g uidance places the onus of compliance on individual researchers making them accountable for any lapses, thereby increasing their responsibility. Keywords: Generative Artificial Intelligence; Academic Research, Thematic Analysis, Policy and Guidance, Qualitative Data Analysis, Framework 1 Introduction As the use of generative artificial intelligence (GenAI) increases across all facets of society, one area of significant impact is higher education institutions (HEIs). Although the initial scholarship on the use of GenAI within HEIs has focused on teaching and learning (McDonald et al., 202 5; Ali et al., 2025) increasingly, studies are starting to examine how academic research is being impacted by GenAI ( Abernethy, 2024; Lehr, et al., 2024; Lin, 2024; Liu and Jagadish, 2024; Godwin et al., 2024) This shift is in keeping with increased uptake of the use of GenAI for research. GenAI has many potential benefits for researchers across different stages of the research process such as data analysis, creation of content for research dissemination, and as a tool to brainstorm new ideas (Joosten et al., 2024) For instance, Delios et al. (2024) report that almost 30% of scientists are using GenAI as partners in their tasks related to research such as summarizing l iterature review, data analysis, grant writing and assisting with other aspects of manuscript preparation (Morocco - Clarke et al., 2024; Xames and Shefa, 2023). In a 2023 Nature survey of 1600 scientists, 30% acknowledged that they used GenAI to write acade mic papers, conduct literature reviews, and/or develop grant applications (Chawla, 2024).