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How Discriminative Artificial Intelligence Drives Scenario Planning: A Systematic Literature Review and Research Agenda

Author

Listed:
  • Laura M. Berensmeier
  • Valentin J. Schmitt
  • Martin G. Moehrle

Abstract

This article explores the potential of discriminative Artificial Intelligence (AI) to enhance scenario planning, a widely used methodology in strategic planning. Like others, scenario planning also faces the challenge of efficiently integrating available information. We address this challenge by investigating two research questions: First, how is discriminative AI currently applied in scenario planning? Second, how could discriminative AI techniques additionally be used to support the stakeholders of scenario planning? A systematic literature review identifies 58 relevant documents that illustrate the application of discriminative AI in several stages of the scenario process. We present six key findings in relation to the purpose of discriminative AI, the data used and the spectrum of topics. We then formulate seven research propositions that serve as a research agenda and highlight further potential for the utilization of discriminative AI. Our contribution to science is that we show how the roles of stakeholders are going to change. For management, we demonstrate the numerous opportunities offered by discriminative AI to improve the quality of scenario planning.

Suggested Citation

  • Laura M. Berensmeier & Valentin J. Schmitt & Martin G. Moehrle, 2025. "How Discriminative Artificial Intelligence Drives Scenario Planning: A Systematic Literature Review and Research Agenda," Futures & Foresight Science, John Wiley & Sons, vol. 7(3), December.
    • Handle: RePEc:wly:fufsci:v:7:y:2025:i:3:n:e70021
    DOI: 10.1002/ffo2.70021
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    References listed on IDEAS

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    1. Elina Hiltunen & Aki‐Mauri Huhtinen, 2024. "Science fiction in military planning—Case allied command transformation and visions of warfare 2036," Futures & Foresight Science, John Wiley & Sons, vol. 6(3), September.
    2. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    3. Minglu Ma & Qiang Wang, 2022. "Assessment and Forecast of Green Total Factor Energy Efficiency in the Yellow River Basin—A Perspective Distinguishing the Upper, Middle and Lower Stream," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    4. Baode Li & Jing Lu & Han Lu & Jing Li, 2023. "Predicting maritime accident consequence scenarios for emergency response decisions using optimization-based decision tree approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 50(1), pages 19-41, January.
    5. Juliana Mio de Souza & Paulo Morgado & Eduarda Marques da Costa & Luiz Fernando de Novaes Vianna, 2023. "Predictive Scenarios of LULC Changes Supporting Public Policies: The Case of Chapecó River Ecological Corridor, Santa Catarina/Brazil," Land, MDPI, vol. 12(1), pages 1-24, January.
    6. Agraw Ali Beshir & Jaemin Song, 2021. "Urbanization and its impact on flood hazard: the case of Addis Ababa, Ethiopia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 1167-1190, October.
    7. Nora Altgilbers & Lothar Walter & Martin G. Moehrle, 2020. "Frugal Invention Candidates As Antecedents Of Frugal Patents — The Role Of Frugal Attributes Analysed In The Medical Engineering Technology," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(06), pages 1-23, August.
    8. Crespo-Vazquez, Jose L. & Carrillo, C. & Diaz-Dorado, E. & Martinez-Lorenzo, Jose A. & Noor-E-Alam, Md., 2018. "A machine learning based stochastic optimization framework for a wind and storage power plant participating in energy pool market," Applied Energy, Elsevier, vol. 232(C), pages 341-357.
    9. Silviu Nate & Yuriy Bilan & Mariia Kurylo & Olena Lyashenko & Piotr Napieralski & Ganna Kharlamova, 2021. "Mineral Policy within the Framework of Limited Critical Resources and a Green Energy Transition," Energies, MDPI, vol. 14(9), pages 1-32, May.
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