Generative machine learning in professional work and professional service firms : a research agenda

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Authors: James Faulconbridge, Kasper Trolle Elmholdt, Frida Pemer, Aline Pietrix Seepma, Tale Skjølsvik, Cara Molyneux
Cited by: 0

Abstract

This paper addresses the need for an approach to theorizing professional work and professional service firms in the generative machine learning age. We develop an approach using insights from existing literature on digital, algorithmic and artificial intelligence technologies. We seek to extend existing theories whilst also responding to the distinctive characteristics of generative machine learning and the implications for how we theorize change. We argue that an approach is needed focused on emerging and future interdependencies between professionals and generative machine learning, something that implies extending but also reimagining theoretical perspectives on expertise, work and organizations.

Fields of Study & Subjects

Ethics and Social Impacts of AI Digital Economy and Work Transformation AI in Service Interactions

Publication details

Journal / source
Lancaster EPrints (Lancaster University)
Publication date
30 June 2026
Language
EN