Automation and labour market dynamics in the UK

Abosede Rebecca Olatunbosun and Iyanu Emmanuel Olatunbosun

SAP Netnography, 2025

Abstract: Introduction: The advancement of artificial intelligence (AI) and workplace automation in the twenty-first century has significantly accelerated industrial growth and innovation. These technologies enhance productivity, support profit maximisation, and reduce certain labour-related pressures as machines increasingly perform tasks previously handled by human workers. Given these developments, this study examines how rising automation influences unemployment in the United Kingdom. Methods: The study draws on secondary national data covering robot installation figures, unemployment rates, the national minimum wage, and major economic growth indicators. Descriptive statistics were used to summarise trends, while breakpoint unit root tests assessed structural shifts in the data. A generalised method of moments (GMM) regression model was then employed to estimate the relationship between automation and unemployment. Results: The findings indicate that increased automation is associated with higher unemployment levels in the UK. This result mirrors evidence reported in previous studies conducted in the United States and Germany, suggesting a broader pattern across advanced economies. Conclusion: The study concludes that although automation drives productivity and innovation, it also heightens unemployment risks in the short to medium term. To prevent a potential labour market crisis, strategic workforce reskilling and proactive policy measures are essential.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:cwf:netart:net2025304

DOI: 10.62486/net2025304

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