Artificial intelligence (AI) and the future of work in the professions: case studies of AI applications in the medical imaging practices in the UK

Wu, Yuxuan (2026). Artificial intelligence (AI) and the future of work in the professions: case studies of AI applications in the medical imaging practices in the UK. University of Birmingham. Ph.D.

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Abstract

Recent technological innovations labelled “AI” elicit vigorous debates about their implications for work, including professional work, which was once viewed as immune to such automation. Despite the enthusiasm, many accounts fall into the familiar trap of technological determinism, speculating utopian or dystopian outcomes that hardly reflect reality. In contrast, using a non-deterministic, evidence-based approach, this research examines the situations in UK medical imaging, a domain characterised by rapid innovation, apocalyptic workforce predictions, and increasing AI adoption. The research question addressed is how and why AI products are applied in professional work, and what implications this has for related professions and professionals.

A theoretical framework was developed abductively by synthesising three existing perspectives to reflect the nature of professional work and its relationship with AI. On the one hand, Labour Process Theory (Edwards, 1979; Edwards, 1986; Thompson and Smith, 2024) and the Jurisdiction theory of the professions (Abbott, 1988, 1995) were adopted to establish a two-dimensional conceptualisation of professional work, reflecting the vertical management-worker dynamics that operate on a contested terrain, and the horizontal interprofessional relationships that operate in an ecological system. On the other hand, the Social Shaping of Technology perspective (MacKenzie and Wajcman, 1985, 1999) was adopted to theorise the relationship between professional work and AI as mutually constative, through various pathways and in a complex process.

With reference to this theoretical framework, this research investigated two workplace cases in which AI are applied in the NHS imaging work. Within cases, semi-structured interviews (n=19) were conducted with AI developers, NHS Trust management, and consultant-level professionals, which were complemented by organisational documents and observations. Workplace data were further supplemented by interviews with industry stakeholders (n=16) and published documents from related institutions.

It was found that while AI products were developed to address challenges in professional work, they were also shaped by “social” factors that both facilitated and constrained their development. The adoption of AI products was not always initiated by management, but can also be initiated, led, and highly involved in by professionals. Potential economic benefits were a salient motivation for adoption, although the extent to which these potentials are realised remains questionable. The implementation of AI products was lengthy, nonsequential, and could deviate from the intended purpose.

When in use, only limited (expected) consequences manifest in job quantity: not only is the automation of professional tasks not realised due to technical, regulatory, and institutional constraints, but the scope of possible automation is also too narrow to enable wholesale replacement. In contrast, most (expected) changes are in the content and quality of work. For UK medical imaging, a reconfiguration of professional jurisdictions is more likely than a general deprofessionalisation. The jurisdictional outcomes differ across related professions: while some are accorded opportunities for jurisdictional expansion, others are subject to potential shrinkage. For individual professionals, both positive and negative outcomes are possible, depending on their current roles and work locations. This research also has practical implications for policymakers, NHS/healthcare managers, and healthcare professionals and their representatives.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):