- Key insight: Artificial intelligence should be viewed as a catalyst to spark the next evolutionary phase of banking, not a harbinger of doom.
- What's at stake: Banks sit on an abundance of high-value data but poor connectivity between systems often prevents them from turning that data into actionable insight.
- Forward look: If we approach AI as a connectivity solution rather than a workforce threat, we'll not only modernize our infrastructure, but we'll also strengthen the relationships that define our relevancy in a rapidly evolving industry.
Like many of you, I use artificial intelligence in my daily life. Recently, I used it to plan a vacation, sorting through options, mapping an itinerary, and narrowing down restaurants and sites, so I could spend less time on logistics and more time enjoying the experience. In these moments,
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Yet in today's broader macroeconomic environment, AI is often viewed through a very different lens. In banking, many of my peers are concerned that AI is a risk to their traditional operating models, frontline roles and the personal relationships that define our business. Too often, we approach innovation as a subtraction rather than an evolution, assuming that if something new arrives, something familiar must disappear entirely.
But I see it differently. When people label AI a threat, they are often missing the bigger picture: AI isn't a disruption to be feared, but a practical capability that can help us do the hard, behind-the-scenes work better, so bankers can do more of the human work customers actually value.
When it comes to AI, I think the best perspective comes from stepping back and viewing technological innovation in its historical context.
On a spring night in 1907, Manhattan's lamplighters went on strike, leaving 25,000 gaslights dark as electricity threatened their nearly 500-year-old profession. The light bulb brought an end to gas-powered streetlights and with them, the entire lamplighting trade. Electricity ushered in a new era, giving rise to new industries, professions and avenues for growth. While some jobs disappeared, countless others were created.
Fast forward to the early 1990s, as dial-up modems noisily brought the World Wide Web into homes. Business leaders feared the internet would upend existing industries and operating models, and in many ways, it did. Yet as the internet gained widespread adoption, new industries, companies, jobs, and even entire ecosystems of productivity and value emerged.
In both examples, technology ushered in the next phase of our evolution, redeploying and expanding value rather than simply eliminating it. While concern about AI's impact on jobs is understandable, history suggests the bigger story isn't disruption, but value creation across industries, roles and new categories of work we can't fully predict. In banking, the comparable inflection point isn't whether jobs disappear, it's whether we finally overcome the fragmentation that makes it difficult to serve customers seamlessly and operate at scale.
When I think about AI's potential impact on banking, I see it solving a problem we've quietly carried for decades: platform and process fragmentation. And that fragmentation doesn't just slow banks down internally. It shows up as friction for customers: repeated requests for the same information, inconsistent answers across channels and delays when work has to be handed from one system (or team) to another.
Banks are built on processes. Over time, those processes become layered and fragmented through acquisitions, regulatory changes, technology upgrades and shifting customer expectations. The result is often a patchwork of platforms, legacy systems, redundant and cumbersome processes, and siloed data sources.
Federal Reserve Gov. Christopher Waller said Tuesday that central bank researchers using Artificial Intelligence must follow security protocols designed to protect sensitive data.
Banks sit on an abundance of high-value data but poor connectivity between systems often prevents them from turning that data into actionable insight. Information lives in different systems and teams rely on manual reconciliation to mine and stitch together multiple data sources. This inflates infrastructure costs exponentially, and technology bloat becomes normalized. It also makes customer journeys harder to deliver consistently, whether that's resolving a service issue quickly, providing a timely credit decision or giving a client an accurate answer the first time.
Left unaddressed, these challenges prevent banks from creating more engaging and innovative customer experiences and fully realizing internal operational efficiencies. But when properly implemented, AI can synthesize these fragmented systems, align data sources and surface insights in real time. It can automate routine tasks, reduce manual intervention and eliminate redundant processes. The payoff is both operational and human: less background work for employees, and simpler, faster experiences for customers.
The industry's focus on whether AI will replace frontline roles misses the larger opportunity. This isn't about replacing human talent. It's about modernizing infrastructure and enabling employees to do more meaningful work.
But when it comes to banking, there is one line AI will never cross.
Banking, at its core, is built on relationships. And, while AI can connect systems, it cannot build personal relationships. Clients do not choose a bank solely for its infrastructure. They choose a bank based on its ability to help them achieve their own definition of financial success.
AI can synthesize data and generate insights, but it can't sit across a table from a business owner to understand their ambition, challenges or long-term vision. Aspiring homeowners need an expert who can help them navigate complexity to realize the dream of homeownership. Everyday consumers need a trusted banker they can rely on to solve problems as they surface.
These are the moments that matter most to clients. Moments where AI can help, but human connection makes all the difference.
If we approach AI as a connectivity solution rather than a workforce threat, we'll not only modernize our infrastructure, but we'll also strengthen the relationships that define our relevancy in a rapidly evolving industry. More importantly, we can make customer-centricity scalable: fewer friction points, faster answers, and more time for bankers to deliver guidance, support, and solutions when it matters most.
And, in my opinion, that's an opportunity worth pursuing.
