Barclays posted £9.1 billion in pre-tax profit for 2025 — up
13% — and CEO C.S. Venkatakrishnan used the results
announcement to
outline an AI-driven efficiency programme
targeting £2 billion in gross savings by 2028. Fraud detection,
client analytics, internal process automation. Fifty thousand
staff getting Microsoft Copilot, doubling in early 2026. Dozens
of London roles relocated to India. A £1 billion share buyback
and £800 million dividend to round things off. The shareholders
are happy. The spreadsheet is immaculate.
I don't doubt the savings are real. Every bank running these
numbers is finding the same thing — operations roles that
involve documents, repeatable steps, and defined rules are
precisely where large language models excel.
Wells Fargo is already budgeting for higher severance
in anticipation of a smaller 2026 workforce. JPMorgan reports
6% productivity gains in AI-adopting divisions, with operations
roles projected to hit 40-50%. Goldman Sachs has folded AI
workflow redesign directly into its headcount planning. This
isn't speculative anymore. The back offices are getting thinner.
What bothers me is the framing. "Efficiency" is doing a lot of
heavy lifting in these announcements. When Barclays says it
will "harness new technology to improve efficiency and build
segment-leading businesses," what that means in practice is
fewer people answering phones, fewer people reviewing
transactions, fewer people in the building. The GenAI colleague
assistant that "instantly provides colleagues with the
information needed to support customers" is, by design, an
argument for needing fewer colleagues. The call handling times
go down. Then the headcount follows.
The banking industry's own estimates are stark. Citigroup found
that 54% of financial jobs have high automation potential —
more than any other sector. McKinsey projects up to 20% net
cost reductions across the industry. Yet 76% of banks say
they'll increase tech headcount because of agentic AI. The
jobs don't disappear. They migrate — from the person who knew
the process to the person who maintains the model that replaced
the process. Whether that's a net positive depends entirely on
which side of the migration you're standing on.
Barclays will likely hit its targets. The efficiency savings
will materialise. The return on tangible equity will climb
toward that 14% goal. The question nobody at the investor
presentation is asking — because it isn't their question to
ask — is what a bank actually is when you've automated the
parts where humans used to make judgement calls about other
humans. A fraud model is faster than a fraud analyst. It's
also completely indifferent to context, to the phone call where
someone explains they've just been scammed and needs a person,
not a pipeline, to understand what happened.
Two billion pounds is a lot of understanding to optimise away.
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