Abstract
As artificial intelligence (AI) technologies become increasingly prevalent in workplace environments, significant knowledge gaps remain about their impact in practice. Most employment research still relies on theoretical predictions rather than real-world implementation data, while wellbeing studies often capture perceptions rather than examining lived workplace experiences with AI systems. Despite widespread organizational adoption, understanding AI’s influence on employment patterns and employee wellbeing has become critical for organizations, policymakers, and society. Addressing this need, the research investigates AI’s impact on employment, workplace transformation, and employee wellbeing in contemporary UK organizations using a mixed-methods approach.The study employed concurrent quantitative and qualitative investigations addressing five key objectives: examining AI investment effects on employment outcomes across UK industries; exploring workplace transformation mechanisms; investigating impacts on employee health and wellbeing; developing theoretical frameworks for understanding AI-wellbeing relationships; and providing evidence-based implementation recommendations. The quantitative analysis utilized longitudinal data spanning 16 UK industries from 2010-2023, employing multiple econometric approaches including mixed-effects modelling and Granger causality testing to establish causal relationships. The qualitative investigation adopted a phenomenological approach, conducting semi-structured interviews with 30 participants across four sectors: healthcare, education, logistics, and professional service.
The findings challenge simplistic technological unemployment narratives by revealing that AI's employment effects are highly heterogeneous and context-dependent. While initial analysis showed negative associations, rigorous causal inference methods revealed non-significant relationships at the aggregate level, with five service-oriented sectors demonstrating significant positive employment relationships. The qualitative investigation revealed AI's impact through four workplace transformations: process acceleration and enhancement, fundamental process transformation, reshaping of professional roles and relationships, and intensification of monitoring and accountability. Employee wellbeing effects manifested through dual impacts on mental health, work-life balance, physical health, and cognitive processing. The research contributes two novel theoretical frameworks: the AI-Wellbeing Framework and an adapted Job Demands-Resources model. It also offers the first in-depth UK-specific analysis that combines actual AI investment data with direct employee experiences. This research demonstrates that successful AI adoption requires deliberate attention to human factors alongside technological considerations, informing the future of work and contributing to UN Sustainable Development Goal 8's decent work objectives by providing insights for organizations, policymakers, and researchers navigating AI-integrated work environments.
| Date of Award | 6 Dec 2025 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | Xiaoxian Zhu (Supervisor) & Sina Joneidy (Supervisor) |