Piyatamrong, Thitiwat; (2025) The Fourth Digital Transformation in Organizations; The Shift from Digital to AI through ‘Recontextualizing’ Work and Skills. Doctoral thesis (Ph.D), UCL (University College London).

Text Piyatamrong_10213932_Thesis_id_removed.pdf Access restricted to UCL open access staff until 1 October 2026. Download (4MB)

Abstract

This thesis investigates the preliminary shift from digital to AI transformation, focusing on how work, expertise, and skills are recontextualized within a global engineering consulting firm. Moving beyond treating AI adoption as a linear technological upgrade, the study conceptualizes AI transformation as a recursive, socio-material process shaped by infrastructural design, epistemic practices, and professional engagements. Through the case study of Zenith, the research traces how computational thinking, hybridized workflows, and emerging fusion skills reshape organizational knowledge regimes. Drawing on Zuboff’s (1988) framework of automation and informating, Castells’ (2004) network society, and Moulier-Boutang’s (2012) cognitive capitalism, the thesis constructs a three-fold periodization of technological transformation. This historical framing provides the analytical foundation for interrogating AI as a restructuring force embedded in recursive workflows. Jordan’s (2015) theory of information power – reworked here as recursive structuring – frames how infrastructures and epistemic protocols shape organizational practice. Methodologically, the thesis combines Lury’s (2021) “problem spaces” with a recontextualized “following the object” strategy to trace how AI-related artefacts, routines, and reasoning circulate through project work. Guile’s (2019) concept of recontextualization anchors the analysis of how professional expertise is iteratively adapted through engagement with computational infrastructures. One of the thesis’s key contributions is the introduction of prompt engineering as an intellective and fusion skill. It is reconceptualized as a recursive epistemic technique through which professionals prompt not only AI systems, but also project logics, technical resources, and contextual expertise, rather than confining the concept to GPT use. This shift highlights how prompt engineering enables the coordination of hybrid human-machine workflows and foregrounds it as a mechanism of organizational adaptation. Overall, the thesis advances a socio-material understanding of AI transformation as a recursive process of epistemic reconfiguration, with implications for digital literacy, organizational learning, and professional work in the age of AI.

Download activity - last month

Export as JSONXMLCSV

Download activity - last 12 months

Export as CSVJSONXML

Downloads by country - last 12 months

Export as CSVXMLJSON

Archive Staff Only

View Item