
Ulrike Morgalla, M.Sc.
Doktorandin und wissenschaftliche Mitarbeiterin
Innovation and Entrepreneurship Research
Net Zero Lab
+49 89 24246-580
ulrike.morgalla(at)ip.mpg.de
Zum Net Zero Lab:
Arbeitsbereiche:
Umwelt- und Ressourcenökonomie, Energieökonomie, Innovationsökonomie, Marktdesign
Wissenschaftlicher Werdegang
Seit 05/2024
Junior Research Fellow am Net Zero Lab (Max Planck Institute für Innovation and Wettbewerb)
Seit 10/2023
Doktorandin und wissenschaftliche Mitarbeiterin am Max-Planck-Institut für Innovation and Wettbewerb (Innovation and Entrepreneurship Research) und der Munich Graduate School of Economics, LMU München
07/2023
Summer School, Barcelona School of Economics (BSE)
09/2022 - 07/2023
Master of Science (M.Sc.) in Economics, London School of Economics
01/2021 - 05/2021
Austauschsemester, University of St Andrews, Schottland
09/2018 - 11/2021
Bachelor of Science (B.Sc.) der Volkswirtschaftslehre, Universität Mannheim
Beruflicher Werdegang
04/2022 - 07/2022
Praktikum, next economy lab, Bonn
01/2022 - 02/2022
Praktikum, ifo Zentrum für Energie, Klima und Ressourcen, ifo Institut, München
10/2019 - 12/2020 und 06/2021 – 11/2021
Studentische Hilfkraft im Market Design, Leibniz Zentrum für Europäische Wirtschaftsforschung (ZEW), Mannheim
Publikationen
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.
(2025).- 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