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Empirically Exploring the Cause-Effect Relationships of AI Characteristics, Project Management Challenges, and Organizational Change

In: Innovation Through Information Systems

Author

Listed:
  • Christian Engel

    (University of St. Gallen)

  • Philipp Ebel

    (University of St. Gallen)

  • Benjamin Giffen

    (University of St. Gallen)

Abstract

Artificial Intelligence (AI) provides organizations with vast opportunities of deploying AI for competitive advantage such as improving processes, and creating new or enriched products and services. However, the failure rate of projects on implementing AI in organizations is still high, and prevents organizations from fully seizing the potential that AI exhibits. To contribute to closing this gap, we seize the unique opportunity to gain insights from five organizational cases. In particular, we empirically investigate how the unique characteristics of AI – i.e. experimental character, context sensitivity, black box character, and learning requirements – induce challenges into project management, and how these challenges are addressed in organizational (socio-technical) contexts. This shall provide researchers with an empirical and conceptual foundation for investigating the cause-effect relationships between the characteristics of AI, project management, and organizational change. Practitioners can benchmark their own practices against the insights to increase the success rates of future AI implementations.

Suggested Citation

  • Christian Engel & Philipp Ebel & Benjamin Giffen, 2021. "Empirically Exploring the Cause-Effect Relationships of AI Characteristics, Project Management Challenges, and Organizational Change," Lecture Notes in Information Systems and Organization, in: Frederik Ahlemann & Reinhard Schütte & Stefan Stieglitz (ed.), Innovation Through Information Systems, pages 166-181, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-86797-3_12
    DOI: 10.1007/978-3-030-86797-3_12
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