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AI for Decision-Making in Connected Business

In: Connected Business

Author

Listed:
  • Naomi Haefner

    (University St. Gallen)

  • Philipp Morf

    (Zühlke Group)

Abstract

With a growing number of connected devices producing exponentially more data, the value of artificial intelligence and machine learning (AI/ML) is increasing rapidly for businesses. We outline the value add of AI/ML for decision-making in firms and present use cases and tools to generate data-driven value. We discuss various implementation challenges and solution approaches. Successfully executing on AI/ML applications hinges on preparing the company, managing the portfolio of projects, using interdisciplinary teams, establishing strong technical foundations, and, importantly, generating trust in AI/ML throughout the system lifecycle.

Suggested Citation

  • Naomi Haefner & Philipp Morf, 2021. "AI for Decision-Making in Connected Business," Springer Books, in: Oliver Gassmann & Fabrizio Ferrandina (ed.), Connected Business, pages 215-231, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-76897-3_12
    DOI: 10.1007/978-3-030-76897-3_12
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    Cited by:

    1. Pietronudo, Maria Cristina & Croidieu, Grégoire & Schiavone, Francesco, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

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