Barclays reported a strong set of annual results for 2025, posting a 12% rise in pre-tax profit to £9.1 billion, up from £8.1 billion the previous year. Alongside the improved earnings, the bank raised its long-term performance ambitions, signalling confidence in its strategy as it leans more heavily on artificial intelligence to streamline operations and support returns.
The UK-based lender now aims to deliver a return on tangible equity (RoTE) of more than 14% by 2028. That marks an increase from its previous goal of exceeding 12% by 2026. Growth in its US business and continued cost reductions played a central role in the improved results, with management pointing to AI as a key contributor to efficiency gains.
AI moves from pilot to core strategy
While many large organisations are still testing artificial intelligence through limited pilot projects, Barclays is embedding the technology into its core operating model. In statements to investors, the bank has framed AI not as an experimental tool but as a practical lever for managing costs and strengthening profitability.
That distinction matters. In highly regulated industries like banking, new technology must work within strict compliance, risk, and data privacy frameworks. Barclays’ leadership appears confident that AI can now operate at scale within those constraints, supporting day-to-day functions rather than sitting in isolated innovation teams.
Cutting costs in a challenging environment
Banks continue to face margin pressure in certain areas of their business, making cost discipline a priority. For institutions with complex legacy systems and large workforces, operating expenses can weigh heavily on returns.
Barclays has linked its AI investments to broader efforts to modernise its technology stack and rethink internal workflows. Tools that assist with risk modelling, customer service processes, and internal reporting can reduce the time employees spend on repetitive, manual tasks. In practice, that may not always mean job reductions, but it can help lower the overall cost base and free up staff for higher-value work.
These savings form part of a wider multi-year programme aimed at improving efficiency. The bank’s latest results suggest that technology-driven cost control is starting to show up in measurable financial outcomes.
From investment to measurable impact
Technology spending rarely delivers instant results. Barclays’ progress reflects a combination of AI deployment, structural cost reforms, and favourable business conditions, including stronger performance in the US market.
The bank has also set out plans to return more than £15 billion to shareholders between 2026 and 2028. That target rests on sustained profitability and tighter expense management, both of which are increasingly linked to its technology strategy.
By presenting AI alongside concrete financial metrics, such as profit growth and higher return targets, Barclays is offering investors a clearer picture of how digital transformation connects to the bottom line. It is not the sole driver of performance, but it is clearly embedded in the broader financial plan.
A signal for traditional industries
Barclays is not alone in exploring AI for efficiency gains. Financial institutions around the world are investing in automation and data-driven tools. What stands out here is the scale and the degree to which AI is tied directly to formal performance targets extending several years into the future.
For traditional, heavily regulated companies, moving from experimentation to operational integration can be complex. Legacy systems, compliance requirements, and organisational culture often slow adoption. Barclays’ approach suggests that, with careful implementation, AI can shift from a future-facing concept to a present-day management tool.
The bank’s results show how established institutions can use emerging technology to address immediate financial priorities, such as cost control and return improvement, while still navigating regulatory demands.
The bigger picture
Barclays’ 12% profit increase and upgraded return targets reflect more than a single year of stronger earnings. They highlight a broader shift in how major financial institutions are using artificial intelligence: not as a headline-grabbing innovation, but as a practical component of everyday operations.
As economic conditions continue to evolve, the ability to combine growth with disciplined cost management will remain crucial. For Barclays, AI has become part of that equation, offering a clearer path toward sustained profitability in the years ahead.
