How can AI enhance trust in building societies?

Today’s building societies look very different from the grassroots cooperatives born during the Industrial Revolution. They’re digital, dynamic, and have millions of members. But they face a swathe of challenges – from regulation to resourcing – all while competing with agile FinTechs and large retail banks.

Many building societies and banks already use AI to improve service delivery, modernising services through personalisation, better fraud detection, and tailored support. But our research shows that customer opinions on AI are deeply divided. Some building society members are using AI happily within their building society’s services, while others don’t even know it exists.

Through the adoption of advanced AI tools, building societies can create even more relevant, personal, member-led experiences. How? By demystifying AI, closing the generational gap, and offering equitable options.

Demystify AI for building society customers

AI has a reputation, and it isn’t always good. Fears around black box autonomous systems persist. While there are different shades of AI for specific use cases, many of these systems are tarred with the same brush. But if people don’t know why, how, when, and where a tool is used, and see the benefits for themselves, how can they trust it?

In our research with banks and building societies (launching in full in autumn 2025), less than a third (29 percent) of building society members say they understand how their branch uses AI in its services. Tellingly, the remaining 71 percent aren’t sure or don’t know. Customers of traditional retail banks feel the same – 30 percent state they understand how AI is used, but the remainder are unsure or unaware. These findings indicate a distinct lack of knowledge which can only be fixed by clear, regular communication on what AI is, which problems it can solve, and how. Demonstrating the benefit to customers is key to gaining their trust.

The chance of information overload is slim. Just nine percent of all respondents say too much information is shared about AI. In fact, a third of all respondents don’t think enough information is provided around how AI is used in services, and roughly the same proportion (27 percent) share this view concerning data use. So, there’s a need for building societies to articulate the application and advantages of AI – a job that starts with leaders and can be disseminated throughout the organisation through AI champions, notices, and updates to customer service training.

Rethink the generational gap

When asked about their interactions with AI tools, three-fifths of building society members say they’ve interacted with an AI-powered assistant through their digital platform. This is encouraging – AI is designed to recognise patterns and suggest the best course of action to reach a given goal.

However, the likelihood of interaction depends significantly on age. Only 19 percent of members aged 65 and above have interacted with an AI-powered assistant through their digital platform. For those aged 18 to 34, the percentage of those who have interacted with an AI assistant rises to 62 percent. On a surface reading, it isn’t surprising that younger people are more likely to say they’ve interacted with AI, because they’re digital natives. However, our results also show that members aged 65 and above are happy to use digital services. So, there’s a need to enhance and craft human-centred AI for older audiences, with segmented learning in appropriate language and formats for specific age groups.

Augment staff, improve customer service

Despite perceptions that ‘it’s better to speak to a human’, AI can help to personalise human interactions depending on their requirements. Imagine the effectiveness of an employee with information about a certain customer’s data, versus an employee with an AI assistant that can help the customer to reach their savings goals. It’s a no-brainer.

Agentic AI is already enabling smaller and mid-sized banks to embed AI without large implementation costs. Organisations are starting to build credit agents, for example, which apply dynamic context-based (not static rule-based) risk scoring and reduce customer wait times. The Financial Conduct Authority has opened up sandbox environments for financial services firms to experiment with AI, offering better access to data, expertise, and regulations, and supporting the creation of context-sensitive solutions.

Communication – and reassurance – can help to build members’ relationships with new tools, cultivating the same level of trust that ironically exists for invisible back-end CRM systems.

Personalise the offering

When it comes to comfort levels with AI’s application in banking services, members’ opinions are equally split. One third feel comfortable, one third feel uncomfortable, and the remaining third are neutral. This segmentation highlights the nuanced views of members while pinpointing key focus areas for decision-makers. First, build on existing comfort levels. Second, address the causes of resistance. Third, encourage members to get ‘off of the fence’. How? Through reassurance, transparency, and incentivisation.

Building societies are often used by families, with many generations of people at various stages of their financial lives. As part of closing the generation gap, and building comfort in general, building societies need to offer equitable AI-enriched features. Traditional banking products based on predefined personas can’t meet new dynamic customer demand for hyper-personalisation. Providing customers with access to AI-enabled solutions will capture customers’ personal circumstances and history while offering tailored recommendations. For instance, a branch employee might use AI to help customers with a complex query about their historic savings accounts. Or a young professional who’s saving for a house might be able to self-select an AI add-on that flags their necessary versus unnecessary spend, aiding financial literacy.

Using AI can also help identify vulnerable customers, both in automated call centre processes (via voice and sentiment technologies), and in conversations with customer service staff. AI can then suggest and guide alternative interactions with the individual’s specific needs in mind. These use cases are already being adopted across the industry. AI use cases for improved customer experience increase exponentially when bundled with real-time data, personalised engagement engines, and seamless integration into core banking and service platforms.

In all cases, the use of AI needs to be advertised clearly, along with the expected benefits. Members should be able to see the benefits for themselves; either through a seamless interaction with an AI agent, or an opt-in AI-enabled feature that could improve their financial position over time. Waiting for the perfect strategy will limit progress; while trying out solutions can achieve significant advantages.

Investing in AI

AI can transform the future of building societies by offering hyper-personalisation, tailored services, and an in-depth understanding of members at the micro and macro level. By experimenting with AI in an ethical, open way, building society branches can grow for the future while staying true to their human-centric roots. It’s up to decision-makers to decide which role AI will play – underutilised assistant, or trusted advisor.