Yorkshire Building Society is using artificial intelligence to strip out routine administration and data-gathering so employees can concentrate on the human qualities that matter most to customers. According to Fintech Finance, the Society’s priority is to automate repetitive work without eroding the judgement, empathy and problem-solving skills that build trust.
The approach is being embedded through a strategic collaboration with Infosys to deliver a “mobile-first, data-enabled” modernisation combining cloud, data and AI. Executives say they want to “combine the convenience of digital with the warmth of human interaction”, with AI supporting faster services and workforce reskilling.
Independent analysis suggests the gains could be significant. McKinsey Global Institute estimates generative AI and automation could free up 27–30 per cent of hours worked in Europe and the US by 2030, mainly by replacing repetitive tasks such as elementary data collection and processing. The expectation is occupational change rather than mass job losses, with reskilling needed to redeploy staff into higher-value roles.
Consultants and practitioners outline how to achieve this. Deloitte Digital advises banks to set clear AI objectives, use it to inform rather than replace human judgement, give staff better data for richer conversations, and be transparent about deployment. American Banker reporting points to contact-centre uses such as call summarisation, agent coaching and AI assistants that cut administrative work and give agents more time for complex interactions.
A practical playbook emerges: automate heavy, repetitive workloads; redesign roles to move staff into customer-facing or analytical positions; retain human oversight for decisions that require context or empathy; and ensure governance and transparency so customers and regulators understand how AI is used.
Commentators warn of reputational risk if technology undermines service quality. An American Banker opinion piece urged banks to ensure AI augments, not dehumanises, customer contact, and to invest in retraining while keeping accountability close.
Where deployed well, AI-enabled tools have delivered faster transfers, fewer repetitive exchanges and better customer records. Staff benefit from more varied work and clearer career pathways; customers get quicker service and more attentive human intervention.
For the UK, the challenge is to turn pilots into scalable programmes that set a global standard for human-centred AI in finance. That will require large-scale training investment, partnerships between financial institutions and technology firms, and regulation that supports innovation while protecting consumers. The Yorkshire Building Society–Infosys deal is one example of how that balance can be struck.
If banks keep human value at the centre, the next phase of AI adoption could deliver faster, more personalised and more humane services — an area in which the UK has the potential to lead.
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