UK Finance: AI Spend to Hit Record Levels in 2025

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UK Finance: AI Spend to Hit Record Levels in 2025
UK Finance’s joint research with Accenture reveals financial firms will allocate 16% of technology budgets to AI as automation accelerates

Britain's financial services sector is accelerating its adoption of generative artificial intelligence, with institutions planning to increase investment to 16% of technology budgets by 2025, up from 12% this year, according to new research published today by UK Finance and Accenture.

The joint study, titled ‘Generative AI in Action: Opportunities & Risk Management in Financial Services’, reveals a sector taking measured steps toward automation while maintaining strict risk controls. 

UK Finance, Accenture

UK Finance identifies seven core areas where generative AI – technology that can create new content based on training data – is delivering measurable value.

"The sector has many years of experience in safely deploying innovative technology," says Jana Mackintosh, Managing Director of Payments and Innovation at UK Finance. "This positions it well to harness the potential of generative AI while maintaining robust controls."

Figure Three: Perceived barriers to scaling generative AI

Measured Progress

The analysis presents three detailed case studies demonstrating early implementation success. 

UK Finance's research shows how a financial institution reduced customer complaint handling times by 30-50% through AI-assisted case management. 

The system resulted in improved customer experience and employee satisfaction, with case managers reporting more time for high-value customer interactions.

A second case study demonstrates how an organisation achieved a 90% reduction in Know Your Customer processing times through AI-assisted document analysis. 

According to UK Finance, this system operated within a private cloud environment, using secure APIs to communicate with a closed Large Language Model (LLM), with all data encrypted at rest and in transit.

The third case study reveals how a financial services firm implemented a multi-agent AI system for software development. The technology accelerated progress through large-scale data migration from on-premises to cloud infrastructure, reducing development cycles by more than 50%.

Looking Forward

These implementations are driving broader adoption across the sector. Accenture and UK Finance’s research shows 38% of financial institutions have developed comprehensive AI roadmaps, incorporating multiple initiatives focused on value, feasibility and risk appetite.

Figure two: Generative AI solution components

“We are seeing examples of generative AI deployments driving real adoption and efficiencies,” says Peter Hairs, Managing Director of Financial Services at Accenture UK. “At the same time, firms are increasingly aware of the limitations, risks and uncertainties.”

Peter Hairs, Managing Director of Financial Services at Accenture UK

UK Finance's analysis highlights how financial institutions are adapting existing risk management frameworks to address challenges unique to generative AI. 

The study identifies three primary risk categories: reliability of outputs, data privacy and security, and third-party considerations. It documents firms implementing automated fact-checking systems, data privacy filters, and continuous monitoring protocols.

On the regulatory front, the research details how the UK's approach is evolving through a principles-based framework. 

The Financial Conduct Authority (FCA) and Bank of England (BoE) have confirmed they will supervise AI within existing regulatory structures, while the Information Commissioner's Office is updating its guidance on AI and data protection.

The BoE has specifically noted challenges around model explainability and transparency.

Figure four: Key developments in UK and EU AI regulation

The joint research details widespread adoption across business functions. In customer service, UK Finance finds AI tools are drafting responses to queries and analysing complaints, with particular attention to vulnerability indicators. 

This focus aligns with FCA data showing that 47% of customers display characteristics of vulnerability.

In compliance functions, UK Finance documents firms using AI to process regulatory documents and validate adherence to rules. 

For software development, the research highlights applications in requirements analysis, code conversion and system testing.

Accenture's economic modelling projects productivity gains exceeding 30% across different segments, with potential cost savings of £12.7bn (US$15.8bn) in banking, £9.7bn (US$12.07bn) in capital markets and £3.4bn (US$4.2bn) in insurance. 

“We are seeing examples of generative AI deployments driving real adoption and efficiencies”

Peter Hairs, Managing Director of Financial Services at Accenture UK

Independent research from Google indicates ROI satisfaction ranging from 75% to 86% across different organisation sizes.

Security considerations feature prominently in the UK Finance findings. Its analysis shows firms implementing limited data retention policies for sensitive data, strict access controls and data minimisation principles. 

Many organisations have established central AI oversight teams with specific processes for third-party risk management.

Jana Mackintosh: Balancing two co-pilots – AI and humans

Jana Mackintosh, Managing Director for Payments and Innovation at UK Finance, analyses the January 2025 report and what is means for AI’s role in the UK’s financial services sector.

Jana Mackintosh, Managing Director for Payments and Innovation at UK Finance

Earlier this month Sir Keir Starmer lauded AI as the “ultimate force for change and national renewal”, as he laid out plans to create new AI growth zones across the country. 

With the technology advancing fast we need careful consideration about how we can all get the best out of its potential.  

There is particular interest in generative AI which can create new content, and the financial services sector has been exploring ways of using it over the past few years 

In a new report, we tried to cut through some of the hype and looking at how generative AI is actually being used. What we found was firms are moving beyond experimentation, with AI now being used for things like fraud detection, enhancing customer engagement and streamlining compliance efforts.   

Equally we found a cautious approach is being taken given the potential risks and wide range of regulations.  Firms have been focusing on areas that involve active human oversight or where the risks are low.  ​​​​​​​

"Just as we train AI models, we need to ensure we upskill humans"

Jana Mackintosh, Managing Director for Payments and Innovation at UK Finance

Despite these growing pains, generative AI’s potential is undeniable. The sector is just scratching the surface, focusing on comparatively simple, lower-risk applications for now, but the future holds real promise and opportunity. The overriding challenge is to continue innovating while maintaining control.  

Generative AI brings with it familiar risks but sometimes with a novel angle. Starting with the familiar – there are issues with data quality, bias risk and integration into existing internal systems.

However, generative AI has other issues – for example, ensuring accuracy is a consideration when human beings do analysis, but this technology has an added tendency to instead prioritise fluency and plausibility.  As such, controls need to be updated to keep pace.  

In practice we will always need a balance between the two co-pilots: AI and humans.

Just as we train AI models, we need to ensure we upskill humans. How much human intervention is needed, when and what skills the humans intervening need to minimise false negatives, false positives or other risks will need to be worked out.

The UK regulators’ long tradition of working with market participants in regulatory sandboxes could prove to be invaluable here.   

To capitalise on generative AI’s potential, the financial sector must also retain public trust. This means being upfront about how the technology is used, building customer confidence, and educating employees about its strengths and limitations.

"The financial sector’s measured approach to generative AI is an example of innovation done right"

Jana Mackintosh, Managing Director for Payments and Innovation at UK Finance

Collaboration across the industry will also be key. Firms, regulators, and tech providers need to work together to establish best practices, clarify regulatory expectations, and ensure everyone is on the same page.  

The financial sector’s measured approach to generative AI is an example of innovation done right. By embracing the technology carefully, firms are showing that it’s possible to innovate while safeguarding customers and complying with regulations. 

The path forward won’t be without challenges, but with continued collaboration and smart investments, generative AI can deliver on its promise to reshape financial services for the better.  ​​​​​​​


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