The AI-extended professional self: user-centric AI integration into professional practice with exemplars from healthcare

Abstract AI technologies are rapidly advancing and have shown potential for providing significant value across a variety of sectors, including healthcare. Much of research has focused on the technologies’ capabilities and pushing their boundaries, with many envisioning AI and AI-enabled robots replacing human labor and humans in the near future. However, in critical domains of professional practice such as healthcare, full replacement is neither realistic nor aimed for, and collaboration between AI and humans is a given for the foreseeable future. This article argues for a shift away from a sole focus on the efficiency and effectiveness of technology, proposing instead that AI-enabled technologies increasingly should learn to adapt to human users considering that healthcare professionals already are overburdened. Rather than contributing to this burden, AI might extend the professional self by anticipating and supporting human needs and intentions. Drawing on a selective meta-synthesis of recent reviews and studies, this article introduces the concept of the AI-extended professional self . This concept suggests a temporary, dynamic integration of human professionals with AI that extends their capabilities with minimal additional burdens regarding training and application. Through three exemplars from healthcare—healthcare consultations, breast cancer screening, and robotic surgery—this article explores how a perspective rooted in the AI-extended professional self might unlock the potential for deeper AI integration into professional practice. Beyond these exemplars, this article calls for interdisciplinary research into the associated potential and challenges, advocating that the burden of AI integration needs to shift from humans to AI-enabled technologies.

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Publication Details

Journal
AI & Society
Published
2025-03-25
DOI
https://doi.org/10.1007/s00146-025-02319-5
Citations
4
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
2.62

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article

The AI-extended professional self: user-centric AI integration into professional practice with exemplars from healthcare

Anna Schneider‐Kamp, Alessandro Godono
4 citations
AI & Society
Artificial Intelligence in Healthcare and Education
2.62
article

The AI-extended professional self: user-centric AI integration into professional practice with exemplars from healthcare

Anna Schneider‐Kamp, Alessandro Godono
article en
4 citations

Abstract

Abstract AI technologies are rapidly advancing and have shown potential for providing significant value across a variety of sectors, including healthcare. Much of research has focused on the technologies’ capabilities and pushing their boundaries, with many envisioning AI and AI-enabled robots replacing human labor and humans in the near future. However, in critical domains of professional practice such as healthcare, full replacement is neither realistic nor aimed for, and collaboration between AI and humans is a given for the foreseeable future. This article argues for a shift away from a sole focus on the efficiency and effectiveness of technology, proposing instead that AI-enabled technologies increasingly should learn to adapt to human users considering that healthcare professionals already are overburdened. Rather than contributing to this burden, AI might extend the professional self by anticipating and supporting human needs and intentions. Drawing on a selective meta-synthesis of recent reviews and studies, this article introduces the concept of the AI-extended professional self . This concept suggests a temporary, dynamic integration of human professionals with AI that extends their capabilities with minimal additional burdens regarding training and application. Through three exemplars from healthcare—healthcare consultations, breast cancer screening, and robotic surgery—this article explores how a perspective rooted in the AI-extended professional self might unlock the potential for deeper AI integration into professional practice. Beyond these exemplars, this article calls for interdisciplinary research into the associated potential and challenges, advocating that the burden of AI integration needs to shift from humans to AI-enabled technologies.

AI & SocietyVol. 40(7)
University of Southern Denmark (DK), University of Turin (IT)
Syddansk Universitet
Openalex Percentile: Top 10%
Artificial Intelligence in Healthcare and Education
2.62
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