According to Forbes, the traditional technology adoption hierarchy where retailers lead and banks follow years later is collapsing. UK high street banks now conduct almost 90% of customer interactions digitally, while large US institutions are rapidly closing the gap despite their dispersed geography. The COVID crisis revealed that problems once considered unworkable could be solved in days, permanently changing the sector’s operating cadence. Agentic AI systems are now targeting specific bottlenecks like loan processes that still take 40-50 days due to manual reconciliation and legacy systems. As David Murphy of Publicis Sapient notes, banks are now having the same technology conversations as retailers almost simultaneously, representing a striking reversal for an industry once defined by cautious sequencing.
The $60 Billion Anchor
Here’s the thing about banking innovation: it’s always been held back by what’s already there. At many institutions, 60-70% of technology spend still goes toward maintaining outdated systems instead of building new capabilities. That’s an enormous drain on resources that could otherwise fuel transformation. Basically, banks are trying to build Formula 1 cars while towing boat anchors. The traditional build-versus-buy debate is giving way to a more urgent question: what reduces the operational drag of the past the fastest? When you’re spending that much just keeping the lights on, no wonder innovation has historically moved at a glacial pace.
Two Paths, Same Destination
Innovation still looks different depending on which side of the Atlantic you’re on. London’s concentrated financial ecosystem enables alignment and execution at speeds that are difficult to match in the US. American innovation tends to happen in bursts across multiple power centers – it’s messier but often more industry-shaping. Payments might feel smoother in the UK, while experimentation moves faster stateside. But agentic AI is pushing both markets toward a shared trajectory. Banks, insurers, neobanks, and fintech challengers are all confronting the same pressures: modernize infrastructure, collapse friction, and deliver digital experiences that feel instantaneous. The gap is narrowing quickly, which is good news for everyone tired of broken cross-border payment experiences.
The Semantic Solution
The next phase centers on semantic knowledge graphs and architectures designed to unify decades of institutional memory. Think of it as creating a Google Maps for all the bank’s accumulated knowledge and processes. With this foundation, agentic systems can navigate deeply entangled environments and automate processes that once required teams of specialists. This approach accelerates modernization by orders of magnitude because it actually works with the legacy reality rather than pretending banks can start from scratch. Solving legacy system challenges while controlling risk becomes more manageable when you have intelligent systems that understand context and relationships. It’s like giving the AI a master key to the entire organizational memory.
No More Excuses
Agentic AI in banking is no longer theoretical – it’s becoming the new baseline for competitiveness. The sector’s traditional timelines are no longer tolerated by customers, regulators, or shareholders. When 90% of interactions are already digital, the pressure to make those experiences seamless is immense. And with fintech challengers constantly pushing boundaries, established players can’t afford to lag. The structural acceleration that seemed impossible ten years ago is now the minimum requirement. Banks that master agentic AI will collapse processes from weeks to hours. Those that don’t will become the next case studies in digital disruption.
