The real test of AI in banking: Making complexity feel simple

When you put a roomful of banking leaders together, you hear a lot about numbers: cost-to-income ratios, efficiency metrics, and capital buffers. At the Financial Times Global Banking Summit in London, where I spoke both on a panel and in a keynote interview about AI in banking, those numbers were the backdrop. But they weren’t the full story. The full story was something more uncomfortable.

Many banks are trying to move at speed on foundations that were never designed for it. Banks are under pressure to deliver returns for stakeholders, prove control for regulators, and provide intuitive experiences for customers. AI is in the middle of all of that.

Banks that will lead in 2026 are the ones that can make their own complexity feel simple to their customers, employees, and regulators. That may sound abstract, but it isn’t. Let me explain.

Banks are competing on unification

At the summit, leaders spoke openly about the urgent need to rebuild their technology foundations. Competitive strength is now defined by how seamlessly a bank operates as one: Can people, data, and systems move in a single flow, instead of across disconnected layers?

Scale in banking is no longer enough to create advantage. Growth, acquisitions, and years of integration have left many banks operating on a patchwork of systems—strong on the balance sheet but slow on change. Consolidation has a new meaning: It involves consolidating systems, not just portfolios.

Standard Chartered and First Abu Dhabi Bank showed what modernisation looks like when simplicity becomes the operational design principle. Rather than layering on fixes or stitching platforms together, both organisations built a single operational backbone that connected their teams, data, and decisions. The results were fewer handoffs, clearer accountability, and the ability to move with more consistency and less effort.

These examples demonstrate that when work flows end to end instead of through disconnected channels, decisions land faster, cost to change decreases, and improvement becomes continuous rather than episodic. This is how modern banks scale—not by expanding their footprint, but by operating as one.

AI is acceleration, people are the engine

Technology spend on its own doesn’t modernise a bank. AI creates value when it reduces friction, removes the manual drag from work, speeds decisions, and amplifies human judgment.

By using AI directly within its processes, one global bank sped up case handling by 45% and reduced escalations by 30%. Routine checks were automated, context was clear, and people spent time resolving issues instead of navigating systems. AI reduced the noise so that employees could focus on higher-value work.

Many proofs of concept remain isolated and ultimately fail to scale, largely because their core processes are disconnected. The banks making progress are redesigning the work, then applying AI where it accelerates flow and raises the quality of decisions.

AI doesn’t transform work until the work itself is transformed. When AI is designed around how work actually gets done and how decisions are made, human judgment becomes the engine, while AI is the accelerant that makes the complex feel simple.

Governance is the baseline for trust

Transformation moves at a different pace on opposite sides of the Atlantic. In the US, innovation often moves first, and governance is secured later. In Europe—and across the wider Europe, Middle East, and Africa (EMEA) landscape—regulatory expectations are heavier, are more fragmented, and sit closer to how work is delivered. Banks operate under multiple jurisdictions, disclosure regimes, and supervisory cultures.

The bar for explainability is high. Ambiguity is narrow. The tolerance for "fix later" is low. In this environment, governance cannot be an oversight function or a late‑stage check. It must be built into the way work happens every day. Transparency, auditability, and resilience are prerequisites. Technology can enable that visibility with one flow of governance, not many parallel interpretations.

This doesn't slow innovation. Rather, it shapes it. Vienna Insurance Group showed what this looks like in practice. By unifying risk and compliance across 50 entities to meet DORA requirements, the organisation achieved a single, clear view that sped up decisions.

Another relevant example beyond banking that I highlighted at the summit is Adobe. Its challenge was not AI capability, but governance at scale. With ServiceNow AI Control Tower in place, the company centralised oversight of AI agents, creating visibility and acceleration.

Governance by design makes scale possible and trust repeatable. And when regulators can clearly see how decisions are made, complexity begins to feel simple.

The only metric that matters is experience

Customers don’t see digital infrastructure. They do, however, feel outcomes: slow handoffs, repeated questions, and unclear steps. Simplicity is the difference between trust and attrition.

The CEO of a leading bank put it simply: the most important number is whether a client’s trajectory is moving up over time. Convenience is the currency of acquisition and retention, and it cuts across generations, from first‑time digital clients to Generation Z customers with zero tolerance for friction.

KPMG research in the UK found that 45% of 18- to 24-year-olds switched banks in the last year, compared with just 4% of those over 65. Younger generations move fast when they feel friction; loyalty can collapse after a single poor experience. Invisible banking, with a fast, intuitive, and effortless experience, is the expectation.

BMO halved complexity and doubled self‑service by reducing case types and unifying channels. Visa took a similar path in disputes, using a single AI‑enabled resolution environment to boost consistency, speed, and transparency.

Better flow inside can create confidence outside. Neobanks proved this by winning on simplicity alone. Now it’s up to traditional banks to treat customer experience as the ultimate test of operational efficiency.

AI leadership shows up at the core

Innovation today happens in weeks, sometimes days. The defining leaders in banking aren’t experimenting at the edges; they’re redesigning the core. They’re taking a platform approach to build a single operational backbone where systems, decisions, and data move together. They simplify before they automate so that AI delivers value across the organisation.

What stood out most from my conversations at the Global Banking Summit was the shared conviction that technology is a strategic necessity. The banks that will compete in the AI era are those that make integration seamless, decisions fast, and complexity invisible to customers and regulators alike. They won’t wait for transformation; they’ll design for it.

Find out how ServiceNow can help you put AI to work for banking.