HSBC to Cut Wealth Jobs as AI Takes on Customer Service

HSBC plans to cut half of its management and specialist roles in wealth management and reduce its number of human financial advisers by 70% as it expands artificial intelligence in customer services.

The reductions will affect HSBC UK’s wealth management business and are expected to take effect at the end of October. People familiar with the plans said AI will handle more customer interactions and support digital products and services.

HSBC described the changes as part of an effort to provide “more digitally enabled products and journeys” and respond to changing customer needs. The bank identified HSBC UK as an established wealth management and premium banking provider.

The cuts follow HSBC’s July announcement that it would establish an AI centre of excellence in Singapore and hire 100 AI specialists. One of the centre’s initial tasks will be applying AI to conversations during customers’ wealth management journeys.

HSBC appointed its first chief AI officer in March. In June, it agreed with Google Cloud to develop more than 200 AI use cases across the bank over two years. The projects are expected to generate hundreds of millions of pounds in revenue and efficiency gains. HSBC plans to prioritise initiatives with an estimated value of more than $100 million.

The bank has about 600 applications running on Google Cloud. It ranked 11th in a global banking assessment of AI adoption, making it the highest-ranked UK bank in that assessment.

Lloyds Banking Group is also changing its workforce as it invests in AI. The bank plans to train all 67,000 employees to use AI through its AI Academy and has created 300 roles focused on agentic AI. The roles include data scientists, engineers, responsible AI specialists and AI product managers.

Nordea, which employs about 30,000 people, plans to reduce its workforce by 1,500 over the next two years. The Nordic bank has budgeted €190 million in restructuring costs. Its 2030 strategy includes using technology, data and AI to standardise processes, reduce the number of platforms and applications, modernise older systems and increase engineering productivity.