Ciby Yohannan is a financial services expert at PA Consulting.
An average of 53 bank branches have closed every month since January 2015, according to new research – a clear reminder of how rapidly the UK’s financial landscape is shifting. As traditional high street banking changes, digital channels have become the primary way that Britons manage their money.
For building societies, this moment represents both a challenge and a crossroads. Building societies have long differentiated themselves through trust, mutuality, and strong personal relationships with their members. This human-centric model has been a cornerstone of their success for over a century.
But the environment around them is evolving fast. Customer expectations – particularly among younger digital natives – are increasingly shaped by seamless, always-on digital experiences offered by neo-banks and digital-first challengers. Against this backdrop, the question for building societies is no longer whether to modernise – but how to do so without diluting the human-centred values that define them.
Perhaps surprisingly, artificial intelligence (AI) can play a pivotal role in achieving this balance. The conversation around AI often gravitates towards cost reduction and job substitution. But AI’s real value for building societies lies in augmenting – not replacing – the human expertise at their core.
AI can strip friction out of everyday processes, such as automating document checks, triaging enquiries, and accelerating mortgage and savings journeys. These are the tasks that quietly consume time but don’t visibly add much value for members. By taking some of these exercises off humans’ plates, AI can give building society teams the freedom to focus more on meaningful, relationship-driven engagement.
Crucially, AI also has the potential to deepen personalisation in a way that strengthens members’ trust. Even simple machine learning models can spot emerging life events, shifts in financial behaviour, or early signs of vulnerability, such as illness or divorce.
When used ethically and transparently, these insights shouldn’t cause firms to push products. Rather, they should prompt timely, human-led interventions – guidance, reassurance, and proactive support at moments that matter. This could look like a member receiving a gentle call from a branch colleague after AI spots early signs of financial stress – offering reassurance, budgeting guidance, or flexible payment options before the situation escalates. It’s a model that enhances service, protects members, and reinforces the core mutual values that set building societies apart.
The research confirms that this is what members are seeking. Customers recognise many of AI’s benefits in banking and building societies, according to our survey of 2,000 customers. 42 percent appreciate its 24/7 availability, especially for urgent issues like fraud alerts. Others cite the reduced risk of human error in routine processes (19 percent). Overall, 35 percent of members feel comfortable with AI’s use in financial services, but they want firms to be transparent about how it’s used and still be able to speak to staff who they can connect with on a human level.
So how do firms successfully roll out AI? Unlike larger retail banks, most building societies do not have the scale or budgets to invest in large, experimental AI programmes. However, meaningful progress does not require heavy upfront investment. Targeted, smaller AI use cases – focused on both back-end efficiencies and frontline personalisation – can deliver tangible benefits quickly. The challenge is often less about technology and more about confidence, capability and organisational readiness.
For many societies, this starts with identifying one or two high‑friction processes where AI can remove administrative burden without touching the member relationship. Building societies should ask themselves whether they can automate routine tasks that currently slow colleagues down – such as verifying documents, assessing enquiries, or surfacing the right information at the right moment.
The research also highlights that as member expectations of seamless digital experiences are growing, so too are workforce’s expectations of the tools they will use to augment, automate, and enhance customer experiences. Building society leaders can improve effectiveness by ensuring reliable, role-relevant tools are readily available for staff and easy to use. This impact can be magnified by democratising AI – equipping colleagues with the tools and confidence to develop their own solutions.
In an era where many financial institutions pursue scale through automation, building societies have a different opportunity. By leveraging AI to strengthen – not replace – the human relationships at the heart of their model, they can bridge the digital-human gap. The result is a future-facing firm that meets evolving customer expectations while staying anchored to the values that have underpinned their success for more than a century.
