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Artificial Intelligence and Machine Learning in Environmental Authorities: Potentials, Challenges and Recommendations for Action—Results of Qualitative Research

In: Advances and New Trends in Environmental Informatics

Author

Listed:
  • Eva Wein

    (Hochschule für Technik und Wirtschaft (HTW))

  • Frank Fuchs-Kittowski

    (Hochschule für Technik und Wirtschaft (HTW)
    Fraunhofer FOKUS)

  • Andreas Abecker

    (Disy Informationssysteme GmbH)

Abstract

This paper examines the potential and challenges of using artificial intelligence (AI) and machine learning (ML) in German environmental authorities. In view of the increasing amount of environmentally relevant data, the importance of AI to support environmental measures is emphasized. Despite increasing interest, the application of AI in environmental authorities has hardly been researched so far. The aim is to shed light on the current state of AI integration by analysing success factors and challenges and deriving recommendations for action. Methodologically, the study is based on qualitative expert interviews using the “MTO model” (human-technology-organization).

Suggested Citation

  • Eva Wein & Frank Fuchs-Kittowski & Andreas Abecker, 2026. "Artificial Intelligence and Machine Learning in Environmental Authorities: Potentials, Challenges and Recommendations for Action—Results of Qualitative Research," Progress in IS, in: Volker Wohlgemuth & Stefan Naumann & Grit Behrens & Anna Zagorski & Maximilian Höb (ed.), Advances and New Trends in Environmental Informatics, pages 91-108, Springer.
    • Handle: RePEc:spr:prochp:978-3-032-22726-3_6
    DOI: 10.1007/978-3-032-22726-3_6
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