Barclays bets on AI to cut costs and boost returns

Barclays recorded a 12 % soar in annual revenue for 2025, reporting £9.1 billion in earnings earlier than tax, up from £8.1 billion a 12 months earlier. The financial institution additionally raised its efficiency targets out by 2028, aiming for a return on tangible fairness (RoTE) of greater than 14 %, up from a earlier purpose of above 12 % by 2026. A rising US enterprise and value reductions underpinned this end result, with Barclays citing AI as a key driver of these effectivity features.

At a time when many giant corporations are nonetheless experimenting with AI pilots, Barclays is tying the expertise on to its value construction and revenue outlook. In public statements and investor filings, management positions AI as one of many levers that may assist the financial institution maintain decrease prices and improved returns, particularly as macroeconomic situations shift.

Barclays’ 12 % revenue rise this week issues, not only for its shareholders, however as a result of it displays a pattern that conventional, extremely regulated corporations at the moment are positioning AI as a core a part of operating the enterprise, not one thing stored in separate innovation labs. For corporations outdoors tech, linking AI to measurable outcomes similar to revenue and effectivity marks a shift towards operational use over hype.

Why AI issues for value self-discipline

Barclays has mentioned that expertise similar to AI is a part of its plan to chop prices and make its operations extra environment friendly. That features trimming components of the legacy expertise stack and rethinking the place and the way work occurs. Funding in AI instruments enhances broader value financial savings targets that stretch again a number of years.

For a lot of giant corporations, labour and legacy techniques nonetheless make up a big chunk of working bills. Utilizing AI to automate repetitive duties or streamline knowledge processing can scale back that burden. In Barclays’ case, these efficiencies are a part of the financial institution’s rationale for setting larger efficiency targets, although margins stay underneath stress in components of its enterprise.

It’s essential to be particular about what these efficiencies imply in observe. AI applied sciences, for instance, fashions that help with danger evaluation, customer support workflows, and inner reporting, can scale back the hours workers spend on guide work. That doesn’t all the time imply reducing jobs outright, however it may possibly decrease the general value base, particularly in capabilities which are routine or transaction-driven.

From funding to influence

Investments in AI don’t translate to outcomes in a single day. Barclays’ strategy combines these instruments with structural value discount applications, serving to the financial institution handle bills at a time when income development alone isn’t sufficient to elevate returns to desired ranges.

Barclays’ efficiency targets for 2028 mirror this twin focus. The financial institution’s management has mentioned that its plans embrace returning greater than £15 billion to shareholders between 2026 and 2028, supported by improved effectivity and revenue power.

Usually, corporations discuss expertise funding in imprecise phrases. Barclays’ newest figures make the hyperlink between tech and revenue extra concrete: the 12 % revenue rise was reported in the identical breath because the position of expertise in trimming prices. It’s not the one issue; improved market situations and development within the US additionally helped, nevertheless it’s clearly a part of the narrative that administration is presenting to buyers.

This emphasis on value self-discipline and revenue influence units Barclays aside from corporations that deal with AI as a long-term guess or a future venture. Right here, AI is built-in into ongoing value administration and monetary planning, giving the financial institution a believable pathway to stronger returns within the years forward.

What this implies for legacy corporations

Barclays is way from distinctive in exploring AI for value financial savings and effectivity. Different banks have additionally flagged expertise investments as a part of broader restructuring efforts. However what makes Barclays’ case noteworthy is the size of the technique and the best way it’s tied to measured efficiency targets, not simply experimentation or small-scale pilots.

In conventional industries, particularly ones as regulated as banking, adopting AI is tougher than in tech startups. Companies should navigate compliance, danger, buyer privateness, and legacy techniques that weren’t designed for automation. But Barclays’ public feedback counsel that the financial institution is now comfy sufficient with these instruments to anchor a part of its monetary forecast on them. That indicators a level of maturity in how the establishment operationalises AI.

Barclays isn’t merely constructing remoted AI initiatives; management is weaving expertise into value self-discipline, modernisation of techniques, and long-term planning. That shift issues as a result of it exhibits how legacy corporations, even these with giant, complicated operations, can begin to transfer past pilots and into business-wide use instances that have an effect on the underside line.

For different end-user corporations evaluating AI investments, Barclays presents a working instance: a big, regulated firm can use expertise to assist hit value and profitability targets, not simply to discover new capabilities.

(Picture by Jose Marroquin)

See additionally: Goldman Sachs exams autonomous AI brokers for process-heavy work

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