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

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.

Authors

Publication Details

Journal
Lancaster EPrints (Lancaster University)
Published
2026-06-30
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Aline Seepma, James Faulconbridge, Cara Molyneux, Frida Pemer et al.
Lancaster EPrints (Lancaster University)
Ethics and Social Impacts of AI
article

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

Aline Seepma, James Faulconbridge, Cara Molyneux, Frida Pemer, Tale Skjølsvik, Tale Skjolsvik, Kasper Trolle Elmholdt
article en

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.

Lancaster EPrints (Lancaster University)
Economic and Social Research Council
Openalex Percentile: Top 100%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.