This article was originally published in the Brand Finance Banking 500 Journal 2026.
Marketing leaders in banking face a familiar challenge: customer expectations keep rising, while the operational complexity behind delivering a simple, reliable experience keeps deepening. Artificial intelligence is now sitting directly in the middle of that ten sion – either as a neat solution or as a painful accelerator of customer expectations, depending on your speed of AI adoption. It is generally accepted that AI is an increasingly routine part of how customers interact with their bank.
Recent research by Tech Mahindra1 shows that almost 70% of banks view customer experience as the most important AI use case, ahead of automation, compliance, and payments.
The latest analysis on consumer behaviour in banking by Brand Finance shows that customer experience and ease of access account for roughly half of consumer consideration when choosing a bank.
Leaders from the banking and financial services industry, from Tech Mahindra, and from Brand Finance convened for a breakfast roundtable held alongside the World Economic Forum in Davos to discuss this very topic. The consensus among industry leaders was clear: AI should be considered in terms of its ability to add value through improved customer experience and unlocked growth, not just operational efficiency.
AI is moving the needle where brands compete most: East, reliability, friction removal
North American banks increasingly view sponsors The most valuable applications of AI in banking to day are not glamorous. They deal with basic issues customers care about:
- getting problems resolved quickly,
- accessing services when needed,
- and having interactions that are smooth rather than confusing.
Industry leaders are seeing this first-hand, during the breakfast meeting we heard about the use of virtual assistants that reduce call centre dependen cy and resolve issues at first contact. These tools af fect real perceptions of reliability and competence. Contrary to the industry narrative, this is not about “delighting” customers – it’s about removing friction. And that is what builds preference.
Brand value is responding to CX improvements - not to AI in isolation
Banks that score strongly on customer experience and ease of access are showing higher brand value growth and better brand strength performance relative to competitors. But the driver is not AI itself. It’s the specific experience outcomes AI enables:
- shorter resolution cycles;
- more predictable outcomes;
- better fraud detection;
- clearer communication;
- and fewer operational dead ends that force customers into call queues or branches.
The lesson for marketers is to stay focused on the customer-facing implications, not the technology. AI that cleans up back-end complexity is helpful, but AI that improves the front-end experience is what moves brand metrics. And AI which doesn’t serve any known purpose, “is just a toy”.
Market trends confirm that AI is a means, not an end. AI is only as valuable as the experience outcomes it enables. Brand value grows when AI removes friction, improves reliability, and simplifies access. Customers don’t reward banks for adopting AI, they reward banks for making banking feel easier, more predictable, and more human." - Roshan Shetty BFSI & Public Sector Head – Americas, Tech Mahindra
The real risk: AI that erodes brand character
A consistent theme in the discussion was the concern around over personalisation and tone. AI can streamline interactions, but it can also remove nuance if not carefully managed. Outputs often sound precise but lack human judgment.
This creates brand risks:
- interactions becoming overly generic;
- interactions are too specific that it feels intrusive;
- and communication that doesn’t match the bank’s established tone.
One participant put it clearly: “AI can’t communicate what our brand stands for – that still comes from people.” This is where marketing leadership matters. AI should amplify, not overwrite, the bank’s identity.
Legacy infrastructure remains a bigger threat to brand than most AI risks
Tech Mahindra’s research suggests it can take around four years for a bank to address legacy system barriers to improved digital CX, and while public discourse often focuses on the risks of AI-adoption, the risk of inaction is overlooked and particularly acute for banks.
Poor integration and outdated infrastructure show up not as IT problems, but as brand problems: slow processes, errors, inconsistent interfaces, or service failures at moments customers consider critical.
Disconnected legacy systems can also prevent marketing leaders from maintaining their desired brand architecture. We have seen a proliferation of offshoot brands for digital bank subsidiaries where the parent brand is unable to name the digital bank the same as its established bank, because mutual branding creates an expectation of greater inter-connectedness in services and systems which the infrastructure ultimately cannot support.
This leads to stretched resources and prevents the Masterbrand from gaining the positive associations of an innovative digital banking platform.
While marketing cannot solve legacy architecture, it can play an influential role by being vocal about the brand consequences of delaying this work.
While marketing cannot solve legacy architecture, it can play an influential role by being vocal about the brand consequences of delaying this work.
The regulatory landscape is changing the pace of innovation
Variations in regulatory expectations are also shaping CX transformation. Industry leaders think that human-in-the-loop requirements in the EU, versus more flexible approaches in parts of Asia, will influence both the pace and nature of change. In markets like the UK, fraud often originates outside the banking system, creating a disconnect between what customers expect and what banks can control.
Marketing leaders need to track this, because regulation will increasingly influence what “good experience” can legally look like.
Three implications for marketing leaders of banks and financial institutions
- Focus AI on the parts of CX that materially influence choice: Speed, clarity, resolution, and ease - these are where AI can have the biggest brand impact today.
- Protect the brand’s tone and judgment: AI outputs should reflect the bank’s personality, not replace it. Marketing must define the quality standards for AI-driven communication.
- Advocate for long-term investment where it matters: Legacy systems, governance models, fraud detection, and data quality all shape CX. CMOs should articulate their brand implications clearly.
- Tech Mahindra: Building the AI-Driven Bank of Tomorrow, Redefining the Future of Banking ↩︎
