AI in Banking: Last Thursday, Barclays confirmed it will cut around 5,000 jobs by the end of the year, describing the changes as partly driven by AI. HSBC is reportedly overhauling its UK wealth business around AI, and reports its own results tomorrow. AI in banking has moved from pilot projects to the profit and loss account. Here is what is happening and what it means.

What Barclays announced about AI in banking

Alongside its third-quarter results on 22 October 2026, Barclays said it would cut about 5,000 roles, roughly 5% of its global workforce, by the end of 2026. Around 1,000 have already gone. Chief financial officer Anna Cross said about 60% of the cuts relate to support functions, including software developers.

Barclays described the changes as “organisational simplification and technology change efficiency driven by AI”. It expects more than £1.1 billion of gross efficiency savings in 2027, from a broader programme that is not about AI alone. The bank also said better customer technology had cut call-centre volumes by 10% over the past year.

Chief executive C. S. Venkatakrishnan offered the most quotable line of the week: AI is “the icing on the cake; it’s not the cake”. His point was that banks must first build the systems and processes that let them benefit from AI, something Barclays says it has spent years doing.

Not just Barclays: AI in banking across the UK

Earlier this month, the Financial Times reported that HSBC plans to cut around half of the management and specialist roles in its UK wealth business, and up to around 70% of its financial advisers, as it puts AI at the centre of how it serves affluent clients. HSBC said it was evolving to deliver more digitally enabled products and journeys. It reports third-quarter results on 27 October.

Other lenders are moving in the same direction. In May, Standard Chartered said it would cut more than 7,000 corporate-function roles by 2030 through technology and automation, including AI. Across the wider UK economy, the ONS found that administrative and clerical roles were the most affected by AI adoption, cited by 38% of AI-using firms with 10 or more staff, although only 6% reported a lower headcount as a result.

The pushback against AI in banking

Not everyone is convinced. Unite’s general secretary, Sharon Graham, called Barclays’ approach short-term and said employers should upskill staff and introduce technology with workers rather than imposing it on them. Analysts have also asked whether a smaller workforce will translate into lower costs without hurting growth or service.

AI in banking has a customer dimension too. The Google Cloud outage on 20 October, which disrupted Revolut, Lloyds and HSBC services for hours, was a reminder that as banking becomes more automated and more digital, the resilience of the underlying technology matters more, not less.

AI in banking for every UK business

1. Fix the foundations first

Venkatakrishnan’s “icing, not the cake” comment applies everywhere. AI delivers results when data is clean, systems are connected and processes are simplified. Bolting AI onto messy operations rarely works.

2. Start where volume is high and work is repetitive

Banks are seeing early gains in support functions and contact centres, where tasks are frequent and well defined. Most businesses have equivalents in finance, HR, customer service and IT support.

3. Plan the people side as carefully as the technology

Roles change before they disappear. Map which tasks AI will take on, which new skills are needed and how you will redeploy and retrain staff. Doing this openly protects trust and keeps valuable knowledge in the business.

4. Keep humans where judgement matters

HSBC’s reported model keeps human advice for clients with more complex needs. Decide deliberately where people add the most value, and design AI to support them there.

5. Build resilience into automated services

The more customers depend on digital and AI-driven services, the more an outage hurts. Plan fallback, monitor everything and test recovery regularly.

The bottom line

AI in banking has reached the point where it is reshaping workforces, budgets and customer experience at some of the UK’s largest institutions. The lesson for every other sector is not to rush to cut, but to build the foundations, redesign work thoughtfully and keep resilience at the heart of every automated service.

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