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Navigating the New Norm: Employees’ Continuous Data Sharing in AI-Driven Workplaces

In: Digital Innovation and Organizational Transformation

Author

Listed:
  • Mena Teebken

    (Bavarian Research Institute for Digital Transformation)

  • Thomas Hess

    (LMU Munich School of Management)

  • Alexander Pretschner

    (Technical University of Munich)

Abstract

This study examines the changing nature of employee data sharing in AI-driven workplaces. AI tools, such as intelligent assistants embedded in daily routines, necessitate a reevaluation of data sharing paradigms due to their continuous data generation and processing. Despite the vast body of literature on data sharing, the constant nature of data sharing in AI-driven environments is rarely investigated. This gap between the practical relevance of such tools and our limited understanding of the changes they entail highlights the need for an extended understanding of the evolving nature of data sharing and its implications. We emphasize the concept of Continuous Data Sharing, transitioning from static decision-making to recognizing data sharing as an ongoing process characterized by changes in data dynamics, employee participation, and unpredictability. In summary, this work underscores the importance of redefining employee data sharing in the context of digital workplace transformation and increasing AI integration.

Suggested Citation

  • Mena Teebken & Thomas Hess & Alexander Pretschner, 2026. "Navigating the New Norm: Employees’ Continuous Data Sharing in AI-Driven Workplaces," Lecture Notes in Information Systems and Organization, in: Christoph M. Flath & Gunther Gust & Frédéric Thiesse & Axel Winkelmann (ed.), Digital Innovation and Organizational Transformation, pages 233-246, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-08483-5_16
    DOI: 10.1007/978-3-032-08483-5_16
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