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AI ambidexterity and the Adaptive transformation capability in healthcare: a single case study

  • Jordan Cassidy Sanijo

    Student thesis: Master's Thesis

    Abstract

    Societal changes, both current and anticipated, are widening the gap between the demand for and supply of healthcare services. Technology is expected to play a crucial role in addressing this disparity. However, the increasing complexity of the healthcare environment challenges organizations’ underdeveloped capabilities to adapt effectively to these changes. It is therefore essential for healthcare organizations to develop the capacity to reconfigure resources and continue creating value in care delivery.
    This study explores how artificial intelligence (AI) contributes to the development of adaptive transformational capability (ATC) in healthcare organizations. The central research question examines the routine and innovative use of AI and its role in driving ATC development.
    A single case study was conducted within a MedTech organization. Data were collected through semi-structured interviews, analyzed in relation to existing literature, and interpreted from a technical perspective. The findings reveal that routine and innovative AI usage enhances leader alignment, facilitates resource reconfiguration, promotes technical agility, and fosters a culture of innovation.
    Key recommendations include engaging in frequent and systematic stakeholder collaboration, exploring the boundaries of current capabilities, and prioritizing technical agility. Finally, organizations must empower employees to experiment with AI, creating an environment that embraces and fosters innovation.
    Date of Award31 Jan 2025
    Original languageEnglish
    SupervisorRogier van de Wetering (Examiner) & Khoi Nguyen (Co-assessor)

    Keywords

    • AI ambidexterity
    • adaptive transformation capability
    • routine AI usage
    • innovatie AI usage

    Master's Degree

    • Master Business Process management & IT (BPMIT)

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