Ulrike Morgalla, M.Sc.

Articles in Refereed Journals

Chugunova, Marina; Harhoff, Dietmar; Hölzle, Katharina; Kaschub, Verena; Malagimani, Sonal; Morgalla, Ulrike; Rose, Robert (2026). Who Uses AI in Research, and for What? Large-Scale Survey Evidence from Germany, Research Policy, 55 (2). DOI

• The integration of AI into scientific work holds significant potential to accelerate innovation. We surveyed researchers in two leading German research organizations to examine AI adoption, barriers, and perceived impact on research. Researchers are widely using AI tools – often for primary and creative tasks – and many expect the technology to be transformative for research. Effective use appears linked to both hands-on experience and engagement with learning resources. A persistent gender gap in AI use is closely associated with differences in familiarity, suggesting a potential focus for organizational efforts. Legal uncertainty and privacy concerns also emerge as major barriers, with researchers calling for clear, high-level regulatory guidance. Overall, our findings suggest directions where institutional actions might be explored to promote more equitable and effective AI adoption.
• Also published as: Max Planck Institute for Innovation & Competition Research Paper No. 25-11

Discussion Papers

Chugunova, Marina; Harhoff, Dietmar; Hölzle, Katharina; Kaschub, Verena; Malagimani, Sonal; Morgalla, Ulrike; Rose, Robert (2025). Who Uses AI in Research, and for What? Large-scale Survey Evidence from Germany, Max Planck Institute for Innovation & Competition Research Paper, No. 25-11.

• The integration of AI into scientific work holds significant potential to accelerate innovation. We surveyed researchers in two leading German research organizations to examine AI adoption, barriers, and perceived impact on research. Researchers are widely using AI tools-often for primary and creative tasks-and many expect the technology to be transformative for research. Effective use, however, requires training, both through hands-on experience and dedicated learning resources. A persistent gender gap in AI use can largely be explained by differences in familiarity, pointing to a clear opportunity for organizational intervention. Legal uncertainty and privacy concerns also emerge as major barriers, with researchers calling for clear, high-level regulatory guidance. Overall, our findings underscore the importance of institutional action to support equitable and effective AI adoption in research.
• Available at SSRN
• Forthcoming in: Research Policy Volume 55, Issue 2, March 2026, 105381