New research from investment bank Morgan Stanley has revealed that the United Kingdom is experiencing more significant job losses due to artificial intelligence than other major global economies, despite reporting substantial productivity improvements.
Net Job Losses Outpace Productivity Gains
The comprehensive study, which surveyed companies across five key industries that have been using AI for at least one year, found British businesses reported an average 11.5% increase in productivity thanks to artificial intelligence implementation. However, this productivity boost has come at a cost to employment figures.
British companies reported that AI had resulted in net job losses over the past twelve months, with employment down by 8% - the highest rate among leading economies including the United States, Japan, Germany and Australia. This contrasts with the United States, where businesses reported similar productivity gains but managed to create more jobs than they eliminated through AI adoption.
Widespread Concern Among UK Workforce
Separate research from international recruitment company Randstad indicates that more than a quarter of British workers now fear their jobs could disappear completely within the next five years due to artificial intelligence advancements. This concern is particularly pronounced among younger workers, with Generation Z employees showing the highest levels of anxiety about AI's impact and their ability to adapt to changing workplace requirements.
Baby boomers - those born between 1946 and 1964 who are approaching the end of their careers - demonstrated greater confidence in their job security and adaptability to technological changes.
Early-Career Positions Most Vulnerable
The Morgan Stanley research identified that UK businesses are most likely to eliminate early-career positions requiring two to five years of experience when implementing AI systems. This trend raises significant concerns about entry-level opportunities for younger workers entering the job market.
London Mayor Sadiq Khan recently highlighted these concerns in his annual Mansion House speech, warning that artificial intelligence could destroy swathes of jobs in the capital and potentially "usher in a new era of mass unemployment." Khan emphasised that London finds itself "at the sharpest edge of change" due to its heavy reliance on white-collar workers across finance, creative industries, and professional services including legal, accounting, consulting and marketing sectors.
Broader Economic Pressures Compound AI Impact
The research suggests UK workers are being hit particularly hard by the rise of artificial intelligence as higher business costs and increased taxes simultaneously weigh on the job market. Unemployment has reached a four-year high, with rises in the minimum wage and employer national insurance contributions creating additional pressure on hiring decisions.
Mayor Khan argued that "we have a moral, social and economic duty to act" to ensure new employment opportunities are created to replace those disappearing due to technological advancement, with entry-level and junior positions identified as the most vulnerable.
Global Calls for Intervention
The concerns extend beyond the UK, with Jamie Dimon, chief executive of US banking giant JP Morgan, telling the World Economic Forum in Davos that governments and businesses must intervene to support workers whose roles are displaced by artificial intelligence technology. Dimon warned that failure to address these employment challenges could risk civil unrest as technological transformation accelerates across global economies.
The Morgan Stanley study surveyed companies across five specific industries:
- Consumer staples and retail
- Real estate
- Transport
- Healthcare equipment
- Automotive sector
This research, shared with Bloomberg, provides crucial insights into how different economies are responding to artificial intelligence implementation and highlights the particular challenges facing the United Kingdom as it navigates this technological transformation while maintaining employment stability.
