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.
References
1. Acemoglu, D., & Restrepo, P. (2016). The Race between Man and Machine: Implications of Technology for Growth, Factor Shares and Employment. NBER Working Paper No. 22252, National Bureau for Economic Research. virginmoneyukplc
2. Acemoglu, D., & Restrepo, P. (2017). Robots and Jobs: Evidence from US Labor Markets. NBER Working Paper No. 23285, National Bureau for Economic Research.
3. Acemoglu, D., & Restrepo, P. (2018). Artificial Intelligence, Automation and Work. NBER Working Papers No. 24196, National Bureau of Economic Research.
4. Arntz, M., Gregory, T., & Zierahn, U. (2016). The Risk of Automation for Jobs in OECD Countries. OECD Social Employment and Migration Working Papers, No. 189, Organisation for Economic Co-Operation and Development.
5. Atkinson, R., & Wu, J. (2017). False Alarmism: Technological Disruption and the U.S. Labor Market, 1850-2015 (pp. 1-28). Information Technology and Innovation Foundation.
6. Berriman, R., & Hawksworth, J. (2017). Will Robots Steal our Jobs? The Potential Impact of Automation on the UK and other Major Economies. PwC UK Economic Outlook. worldbank
7. Bessen, J. (2017). Automation and Jobs: When Technology Boost Employment. Law and Economics Research Paper No. 17-09. Boston University School of Law. tandfonline
8. CEDEFOP (European Centre for the Development of Vocational Training) (n.d.). Automation of Work and Skills. https://www.cedefop.europa.eu/en/events-and-projects/projects/digitalisation-and-future-work/automation-work-and-skills
9. Chiacchio, F., Petropoulos, G., & Pichler, D. (2018). The Impact of Industrial Robots on EU Employment and Wages—A Local Labour Market Approach. Working Papers No. 25186. Bruegel.
10. Chowdhry, A. (2018, September 18). Artificial Intelligence to Create 58 Million New Jobs By 2022, Says Report. Forbes. https://www.forbes.com/sites/amitchowdhry/2018/09/18/artificial-intelligence-to-create-58-million-new-jobs-by-2022-says-report/?sh=1f0b27e24d4b
11. Dauth, W., Findeisen, S., Südekum, J., & Wößner, N. (2017). German Robots the Impact of Industrial Robots on Workers. CEPR Discussion Paper No. 12306, Centre for Economic Policy Research.
12. Deloitte & The Manufacturing Institute (2011). Boiling Point? The Skills Gap in U.S. Manufacturing. http://www.themanufacturinginstitute.org
13. Ejelonu, H. O. (2023). Minimum wage and industrial output nexus in Nigeria: X-raying causation. Kogi Journal of Management, 15(1), 1-15.
14. Ejelonu, H., Okafor, S., Anukwuocha, S. P., & Neubacher, N. (2022). Econometric Evaluation of Urbanization, Unemployment and Incidence of Poverty Paradox In Nigeria: An Autoregressive Distributed Lag Model Estimation Approach (September 5, 2022). Available at SSRN: https://ssrn.com/abstract=4210539 or http://dx.doi.org/10.2139/ssrn.4210539
15. Ejelonu, H.O. and Okafor, S.O. (2022). Implications of foreign capital inflows on Manufacturing Sector in Third World countries: A Nigerian experience. International Journal of Accounting, Finance and Risk Management, 7(4), 140-149.
16. Frey, C. B., & Osborne, M. A. (2017). The Future of Employment: How Susceptible Are Jobs to Computerisation? Technological Forecasting and Social Change, 114, 254-280.
17. Gartner (2017, December 13). Gartner Says By 2020, Artificial Intelligence Will Create More Jobs than It Eliminates. https://www.gartner.com/en/newsroom/press-releases/2017-12-13-gartner-says-by-2020-artificial-intelligence-will-create-more-jobs-than-it-eliminates
18. Graetz, G., & Michaels, G. (2015). Robots at Work. Discussion Paper No. 1335, CEP.
19. Manyika, J., & Sneader, K. (2018, June 1). AI, Automation, and the Future of Work: Ten Things to Solve for. McKinsey Global Institute. https://www.mckinsey.com/featured-insights/future-of-work/ai-automation-and-the-future-of-work-ten-things-to-solve-for#
20. Mckinsey Global Institute (2017, December 6). Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation. https://www.mckinsey.com/~/media/McKinsey/Industries/Public%20and%20Social%20Sector /Our%20Insights/What%20the%20future%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/MGI-Jobs-Lost-Jobs-Gained-Report-December-6-2017.pdf
21. Oladokun, B. D., Osahon Igbinovia, M., Orubebe, E. D., & Olatunbosun, I. E. (2025). Exploring Academic Librarians’ Perception towards Artificial Intelligence in Nigerian Polytechnics. EthAIca, 4, 438. https://doi.org/10.56294/ai2025438
22. Olatunbosun, I. E., & Olatunbosun, A. R. (2025a). Artificial Intelligence and Risk Management in Financial Institutions: Evidence from the UK Banking Sector. EthAIca: Journal of Ethics, AI and Critical Analysis, (4), 436.
23. Olatunbosun, I. E., & Olatunbosun, A. R. (2025b). Artificial Intelligence for Fraud Detection and Portfolio Optimization: Insights from UK Financial Institutions. EthAIca, 4, 437. https://doi.org/10.56294/ai2025437
24. World Economic Forum (2018). The Future of Jobs Report 2018. World Economic Forum. http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf gov
25. Zeira, J. (1998). Workers, Machines, and Economic Growth. Quarterly Journal of Economics, 113, 1091-1117.
26. Zinser, M., Sirkin, H., & Rose, J. R. (2015, September 23). The Robotics Revolution: The Next Great Leap in Manufacturing. Boston Consulting Group. https://www.bcg.com/publications/2015/lean-manufacturing-innovation-robotics-revolution-next-great-leap-manufacturing.
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