Leading the way
Over the years, finance teams have typically been among the first to use the power of automation to speed up back-office processes, and have often led the way when it comes to the adoption of new and emerging technologies.
It will come as no surprise, then, that AI – and specifically GenAI – is being utilised widely in financial services in 2025. But how exactly is AI being deployed, and how does finance compare to other UK industries when it comes to AI adoption?
Recently released, the influential OneAdvanced Business Trends Report surveyed over 6,000 leaders and professionals from a wide range of UK industry sectors, including health and care, manufacturing, business services, law, IT, housing, central and local government, and finance. The survey was designed to uncover the relationship between UK organisations and the latest technology.
Finance and AI adoption – the numbers
The survey shows that on the topic of AI, the finance industry is at the forefront, with 23% of respondents telling us AI is fully embedded within their operations following comprehensive planning. This is second only to IT (29%), and notably ahead of retail and wholesale (12%), social housing (9%), law (13%), distribution and logistics (8%), and education (9%).
When not part of company-wide strategy, AI is being utilised in specific areas: 26% say that AI is being used independently in certain teams or departments. This compares similarly with distribution and logistics (28%), business services (29%), and law (23%).
Creating a culture of success
Taken together, these numbers put finance ahead of the pack when it comes to AI adoption in the UK (49% compared to 43% in IT) – an impressive feat highlighting an industry unafraid to move with the times.
This lack of fear is also shown by a willingness to start new AI projects: 40% of finance teams have successfully implemented a new AI project in the past 12 months – a figure only beaten by professional services (41%), and IT (71%). And while a certain amount of failure is to be expected (26% in this instance), the fact that the finance industry enjoys such a high level of success when deploying new AI projects suggests a culture that values expertise and careful planning.
How is AI being used in finance departments today?
For finance teams already using AI, the OneAdvanced report highlights various use cases, each requiring different AI solutions to address specific problems. Over one third (36%) of respondents tell us they use AI for a more responsive and intuitive online customer service experience, suggesting a big shift away from legacy chatbots towards generative AI assistants – a clear advantage in a world of ‘always on’ communication.
The same number say they use AI-powered software to spot financial irregularities and safeguard against potential fraud. While technology solutions are helping reduce the number of fraudulent transactions year on year, the numbers remain significant, with losses of nearly £1.2bn in 2023. Using anomaly detection and predictive analysis, AI systems can quickly spot and prevent fraudulent activity.
Another key area is data, specifically data accessibility and data retrieval. Nearly one third (30%) in finance tell us they use AI to help organise data for better accessibility and analysis, while the same number tell us they use AI for the rapid retrieval of data through voice and text queries. This type of advanced automation removes time consuming and burdensome processes, saving countless hours for finance teams looking for productivity gains.
What are the blockers for finance teams and AI adoption?
Of course, there are understandable fears over the use of AI in finance, particularly when it comes to data security. Nearly 4 in 10 (37%) say they are not confident that integrating their current data with external systems will ensure the proper management and security of their data.
Our respondents also express concerns over both expertise, and readiness: 26% say they do not have the necessary skills to move forward with AI implementation, while 28% believe their data is not organised or accurate enough to produce reliable AI outputs.
These blockers, and others, can be overcome with careful planning and auditing. For a 10-step guide on how to successfully implement AI into your organisation, don’t miss our informative blog: How to implement AI in the workplace.
Find out more
To read all the data and insights for yourself, download your copy of the OneAdvanced Finance and Spend Report 24/25 today. Along with AI, discover how the finance industry is faring when it comes to ESG, DE&I, cybersecurity, cloud computing, and more.