By Aditya Gandhi, VP- Technology, Financial Services, Publicis Sapient
AI is rapidly redefining the foundations of banking, not only in how customers interact with financial institutions, but in how banks themselves operate. As AI moves from assistive tools to decision-making systems, banks face a dual transformation challenge: reimagining customer experience at the point of intent, and re-architecting internal operations around agentic intelligence.
This article is the first in a two-part series. Part 1 focuses on customer experience transformation, examining how generative and conversational AI are reshaping discovery, onboarding, servicing, and payments.
Part 2 will turn inward, focusing on agentic AI and the transformation of bank operations. It will explore how autonomous and semi-autonomous agents can rewire core processes, spanning operations, risk, compliance, technology, and service delivery, driving step-change gains in efficiency, resilience, and speed, while redefining how work gets done inside the bank.
Together, these two perspectives reflect a single reality: sustainable advantage will come from connecting AI-driven customer experiences with agentic, AI-native operating models beneath the surface.
Customer Experience transformed by AI
Over the past three to four decades, banking has undergone multiple waves of technological transformation. The advent of the web marked a major turning point, enabling self-service at scale and reducing dependence on physical branches. Mobile technology then extended this shift, giving customers always-on, global access to banking services.
Despite these advances, the core digital experience has largely remained unchanged. Most banking interfaces are still built around static menus, predefined journeys, and rigid workflows. Customers are expected to adapt to the system, searching through options, navigating complex decision trees, and completing lengthy forms during onboarding or product applications, often with little contextual guidance.
The emergence of Generative Customer Experience (CX) is set to fundamentally disrupt this model. Powered by AI, Generative UX moves away from fixed screens and flows toward dynamic, intent-driven interactions. Instead of users learning how a system works, the system learns who the user is, what they are trying to achieve, and adapts in real time.
For example, rather than presenting multiple product pages and application forms, a generative interface can begin with a simple conversation:
“I want a home loan, but I’m not sure how much I can afford.”
The experience then dynamically assembles the journey, asking only relevant questions, pre-filling known information, explaining trade-offs in plain language, and generating a personalized application flow on the fly. The “UI” becomes fluid, contextual, and purpose-built for the individual.
This shift marks a profound change in expectations. Experiences must now adapt to people—not the other way around. As generative capabilities mature, customers will increasingly expect banking interactions to be intuitive, conversational, and personalized by default, setting a much higher bar for digital experience design.
The Amazon-OpenAI Parallel: Platform Shifts
Amazon’s transformation from an online retailer to the operating infrastructure of commerce permanently altered who owns the customer relationship. Brands that once saw Amazon as a distribution partner slowly realized the cost of convenience: Amazon controlled discovery, pricing pressure, customer data, and loyalty, while sellers became interchangeable fulfillment engines.
OpenAI and ChatGPT are now at the beginning of a similar, but far more consequential, platform shift. ChatGPT is evolving from a conversational interface into an operating system for intent. The layer where customers express needs, evaluate options, and trigger actions. In commerce and banking, this means the primary interface will soon no longer be an app, a website, or even a payment screen, it will be an AI conversation.
In this world, banks face a stark choice. If they remain passive integrators, exposing products and payments via APIs while the AI controls the experience, they risk being relegated to invisible utilities. The AI layer will decide which bank is presented, when, and on what terms, compressing differentiation and pushing institutions into a race to the bottom on cost and reliability.
Payments is where this disruption will surface first.
Consider a customer telling ChatGPT:
“Book this flight and pay in the smartest way.”
The AI evaluates context: cash flow, rewards, FX fees, BNPL eligibility, risk preferences, and executes the payment. The customer never chooses a card, wallet, or bank. The payment decision is abstracted away. If the bank is not natively embedded in that AI decision loop, it becomes a background processor, settling transactions without owning trust, preference, or loyalty.
The strategic implication is profound: distribution will no longer be about channels; it will be about influence at the AI decision layer. Just as brands learned too late that “being on Amazon” was not the same as owning the customer, banks risk discovering that “being integrated with AI” is not the same as being chosen by it.
Leadership teams must now ask harder questions. What proprietary data, intelligence, or trust signals can only our bank provide? How do we shape AI-driven payment decisions rather than merely fulfill them? And how do we ensure that when an AI decides how money moves, our institution is not just compliant, but preferred?
Those who act early can help define the rules of this new operating layer. Those who don’t may find themselves efficiently processing transactions in a world where someone else owns the customer.
Two Essential Paths for Banks
This shift leaves banks with two fundamentally different strategic paths and attempting to straddle both without clarity risks failure at scale.
1. The first is to operate as an integration layer: ensuring products, payments, and capabilities are fully discoverable within emerging AI ecosystems by exposing high-quality APIs, structured data, and real-time decisioning. This path prioritizes reach and relevance but accepts that the brand may be largely invisible, with value captured through volume, efficiency, and balance-sheet strength rather than customer intimacy.
2. The second path is to become a relationship platform: owning the customer interface and acting as a trusted financial agent on the customer’s behalf. Here, banks use generative AI to deliver proprietary, deeply personalized experiences, guiding decisions, optimizing outcomes, and earning trust over time. This approach preserves differentiation and loyalty but requires bold investment in AI-native UX, data intelligence, and operating-model change.
Both paths can succeed, but not equally for every institution. What is no longer viable is avoiding the choice. In an AI-mediated world, banks will either power the experience from behind the scenes, or define it at the point of intent.
Strategic Imperative
AI disruption presents both significant risk and transformative opportunity for banks. To remain relevant, institutions must decide where AI should directly handle customer interactions, how seamlessly their services integrate into AI-driven ecosystems, and how their products and content are surfaced and selected by AI-led discovery and search.
This requires reimagining the bank’s digital assistant across seven critical dimensions: being front and centre at the point of intent, contextual in understanding customer needs, multi-modal across voice, text, and interfaces, agentic in taking action on the customer’s behalf, revenue-generating through intelligent recommendations, open and connected to broader ecosystems, and capable of providing targeted, proactive support.
Done well, these capabilities unlock material business value, elevating customer experience, reducing cost to serve, strengthening long-term relationships, and opening new, diversified revenue streams.
Conclusion
The future of banking will not be decided by who has the best app, the most features, or the largest balance sheet. It will be decided by who shapes decisions at the moment intent is expressed.
In an AI-mediated world, banks will not lose relevance because their products are inferior, but because they are absent when choices are made. Institutions that fail to embed themselves into AI-driven decision loops will find themselves becoming invisible to the customer.
Those that succeed will ensure that when AI acts on a customer’s behalf, it acts with them, not around them.