IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v35y2025i1d10.1007_s12525-025-00759-x.html
   My bibliography  Save this article

A data-driven use case planning and assessment approach for AI portfolio management

Author

Listed:
  • Frank Bodendorf

    (Friedrich-Alexander-University of Erlangen-Nuremberg)

Abstract

This paper presents a novel data-driven approach to identify and evaluate valuable and feasible AI use cases, following an Action Design Research methodology. The proposed approach comprises a three-step iterative AI use case planning method and an AI use case data model that establishes an AI use case library to gather ideas, document and compare solutions, assess feasibility, and plan implementation. Within this approach, we outline the process of use case planning, involving ideation, scoping, and assessment. The systematic collection and storage of specific use case data foster transparency and the creation of a knowledge base, facilitating data-driven decisions for AI use case portfolio management. This decision-making process is based on key dimensions such as value and feasibility, which are further broken down into sub-dimensions, including strategic value, financial value, data complexity, model complexity, required expertise, integration complexity, and risk classification. To validate the proposed approach, we apply it to real-world scenarios and conduct eight case studies to evaluate its effectiveness and practicality. Our approach enables different business stakeholders to collaborate effectively and create a standardized description and evaluation of AI use cases. This standardization not only ensures consistency and reuse across projects but also enhances the collective understanding and assessment of AI initiatives within and across organizations.

Suggested Citation

  • Frank Bodendorf, 2025. "A data-driven use case planning and assessment approach for AI portfolio management," Electronic Markets, Springer;IIM University of St. Gallen, vol. 35(1), pages 1-17, December.
    • Handle: RePEc:spr:elmark:v:35:y:2025:i:1:d:10.1007_s12525-025-00759-x
    DOI: 10.1007/s12525-025-00759-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-025-00759-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12525-025-00759-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kichan Nam & Christopher S. Dutt & Prakash Chathoth & Abdelkader Daghfous & M. Sajid Khan, 2021. "The adoption of artificial intelligence and robotics in the hotel industry: prospects and challenges," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 553-574, September.
    2. Sturm, Timo & Fecho, Mariska & Buxmann, Peter, 2021. "To Use or Not to Use Artificial Intelligence? A Framework for the Ideation and Evaluation of Problems to Be Solved with Artificial Intelligence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124702, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Scott Thiebes & Sebastian Lins & Ali Sunyaev, 2021. "Trustworthy artificial intelligence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 447-464, June.
    4. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    5. Sturm, Timo & Fecho, Mariska & Buxmann, Peter, 2021. "To Use or Not to Use Artificial Intelligence? A Framework for the Ideation and Evaluation of Problems to Be Solved with Artificial Intelligence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124636, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    2. Eeman Almokdad & Chung Hun Lee, 2024. "Service Robots in the Workplace: Fostering Sustainable Collaboration by Alleviating Perceived Burdensomeness," Sustainability, MDPI, vol. 16(21), pages 1-17, November.
    3. Xi Liu & Yugang He & Renhong Wu, 2024. "Revolutionizing Environmental Sustainability: The Role of Renewable Energy Consumption and Environmental Technologies in OECD Countries," Energies, MDPI, vol. 17(2), pages 1-21, January.
    4. Wilson, Christopher & van der Velden, Maja, 2022. "Sustainable AI: An integrated model to guide public sector decision-making," Technology in Society, Elsevier, vol. 68(C).
    5. Stéphanie Camaréna, 2021. "Engaging with Artificial Intelligence (AI) with a Bottom-Up Approach for the Purpose of Sustainability: Victorian Farmers Market Association, Melbourne Australia," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    6. Jinyi Li & Zhen Liu & Guizhong Han & Peter Demian & Mohamed Osmani, 2024. "The Relationship Between Artificial Intelligence (AI) and Building Information Modeling (BIM) Technologies for Sustainable Building in the Context of Smart Cities," Sustainability, MDPI, vol. 16(24), pages 1-38, December.
    7. Govindan, Kannan & Kannan, Devika & Jørgensen, Thomas Ballegård & Nielsen, Tim Straarup, 2022. "Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    8. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    9. Gianluca MISURACA & Colin van Noordt, 2020. "AI Watch - Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Research Reports JRC120399, Joint Research Centre.
    10. Martins, Flavio Pinheiro & De-León Almaraz, Sofía & Botelho Junior, Amilton Barbosa & Azzaro-Pantel, Catherine & Parikh, Priti, 2024. "Hydrogen and the sustainable development goals: Synergies and trade-offs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    11. Zhao, Qian & Wang, Lu & Stan, Sebastian-Emanuel & Mirza, Nawazish, 2024. "Can artificial intelligence help accelerate the transition to renewable energy?," Energy Economics, Elsevier, vol. 134(C).
    12. Jaros³aw Brodny & Magdalena Tutak, 2023. "The level of implementing sustainable development goal "Industry, innovation and infrastructure" of Agenda 2030 in the European Union countries: Application of MCDM methods," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 47-102, March.
    13. Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
    14. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    15. Sergio Genovesi & Julia Maria Mönig, 2022. "Acknowledging Sustainability in the Framework of Ethical Certification for AI," Sustainability, MDPI, vol. 14(7), pages 1-10, March.
    16. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    17. Sung Jin Kang & Seon Ju Lee & Shijun Cao, 2024. "Linking the UN SDGs and Sustainable Development Progress: The Case of China," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 16(3), pages 371-391, September.
    18. Wang, Weilong & Xiao, Deheng & Wang, Jianlong & Wu, Haitao, 2024. "The cost of pollution in the digital era: Impediments of air pollution on enterprise digital transformation," Energy Economics, Elsevier, vol. 134(C).
    19. Kim, Myung Ja & Hall, C. Michael & Kwon, Ohbyung & Sohn, Kwonsang, 2024. "Space tourism: Value-attitude-behavior theory, artificial intelligence, and sustainability," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    20. ODEH, Joseph PhD, 2024. "Exploring AI Applications to Foster Healthy Shopping Habits in Nigerian Retail," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3s), pages 5382-5393, November.

    More about this item

    Keywords

    AI discovery; AI use case planning; AI portfolio management; Action design research;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • M16 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - International Business Administration

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:elmark:v:35:y:2025:i:1:d:10.1007_s12525-025-00759-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.