The Human Edge: Leading through AI in financial services

As AI embeds itself across UK financial services, the point of tension is leadership and vision, not tooling. Building societies face the same strategic question as all firms: how do we align digital capability with human judgement, customer trust, and regulatory expectations? The challenge is not adoption per se, but purposeful integration that delivers resilient outcomes for all.

What we’re seeing on the ground

AI investment is accelerating across all markets, but capability gaps and workforce uncertainty mean deployment often outpaces governance, skills, and operating model maturity. The most successful societies are turning this challenge into an opportunity by dialling up the people agenda at all levels as well as strengthening Boards with Executives and Non-Executives who combine technology expertise with commercial insight and a strong commitment to customer centricity. By doing so, they close capability gaps while positioning themselves to lead with agility, innovation, and trust, ensuring AI delivers tangible value for members and communities.

Strategic integration beats shiny tools

Adopting technology without a clear purpose remains a recipe for churn. The winning pattern is to anchor AI to measurable business problems: reduce cost to serve, shorten mortgage time to offer, improve arrears outcomes, tighten fraud controls, and raise first contact resolution. This requires line leaders who work shoulder to shoulder with data, risk, and IT, fluent enough to interrogate models, adapt processes, and measure value, rather than delegating the hard questions to a project team. Purposeful integration turns AI from a buzzword into a tool that reinforces member trust, strengthens governance, and drives measurable outcomes.

People and capability

Upskilling cannot sit on the HR fringe. Leaders need practical data literacy: understanding how models work, where the data comes from, what could introduce bias, and which metrics demonstrate real benefit. Reskilling should be a powerful act of inclusion, moving colleagues from repetitive tasks into judgment-rich roles such as complex cases, supporting vulnerable customers, and managing complaints.

Organisations that succeed treat change as a social process, combining transparency about what will change and why, listening to concerns, and demonstrating visible sponsorship from the top team. By doing so, they create a culture where people are empowered, capable, and confident in harnessing AI to deliver better outcomes.

Regulatory implications

The regulatory direction is clear, even as specific rules evolve. Consumer Duty requires firms to prove fair outcomes for all customers, especially vulnerable groups, raising expectations around transparency, bias testing, and AI oversight in decisions across sales, servicing, pricing, and collections. SM&CR makes senior leaders personally accountable for data and models, demanding visible oversight, challenge, and action. Model risk management calls for strong governance, inventories, validation, and ongoing performance checks, while operational resilience and third-party risk oversight are critical as AI increasingly relies on cloud and external providers. Data protection rules remain foundational, with strict governance of training and inference data and impact assessments where risks are high.

For Boards and executives, this is not just about compliance but about fostering a culture of accountability, technical confidence, and ethical decision making. Leaders must champion responsible AI, empower teams to raise concerns, and show that strong governance builds trust, protects customers, and strengthens competitive advantage.

Leading through resistance

Resistance to change is human, not irrational. When job security feels uncertain and systems become harder to understand, trust can fade. Great leaders meet this challenge with honesty, clearly communicating what will change, for whom, and when, while inviting participation through pilots and co-design, and showing they are willing to learn alongside their teams. They celebrate curiosity and continuous improvement, building a culture where adaptability is second nature.

The AI revolution in UK financial services will not be won by machines but by leaders who bring together human judgment and digital capability, balancing innovation with wisdom and regulation with ambition. Over the next year, the goal should be to create a culture where technology and people work in harmony, delivering faster, fairer decisions, clearer audit trails, fewer complaints, and better experiences for members and customers.

True success will not be measured by the number of models deployed but by how consistently those models deliver trust, resilience, and lasting value for the people Building Societies exist to serve.

Deborah Cooper and Tom Senchukov. From BSA Blog – October 2025.