Editorial
Research Report
The AI Transformation 100: Concrete Ideas for Fixing How We Work
Until recently, customer loyalty was a straightforward mathematical equation: consumers spent money, earned points and redeemed them months or years later. But lately, this “delayed gratification” model is breaking down. On average, consumers were enrolled in 19.5 different loyalty programs in 2025, yet only engaged with about half of them. What went wrong?
Loyalty no longer lives in a formal “earn points and wait to redeem them” system. It lives in everyday customer interactions, and is ideally driven by relevant personalization, consistency across channels and genuine emotional connection.
As artificial intelligence reshapes customer relationships and communication, business leaders must recognize that loyalty is now a data-driven but still emotionally grounded experience. In this new era, trust is the ultimate currency.
Table of Contents
- The Shift From Accrued Rewards to Everyday Relevance
- The Double-Edged Sword: 'Good' vs. 'Bad' Personalization
- The Last Mile: CX as the Ultimate Differentiator
- Experience-Driven Insights for Enterprise Leaders
The Shift From Accrued Rewards to Everyday Relevance
Over years of ecommerce optimization, consumers have been conditioned by retailers to expect speed, ease and visible value exactly when they check out. They are no longer willing to wait for an annual redemption event. They want loyalty baked into their daily habits.
We are seeing this play out in financial services. There is a massive strategic shift underway, away from banks/issuers offering credit card rewards and toward rewarding everyday debit transactions and other routine banking behaviors, such as setting up a direct deposit or using digital bill pay. These kinds of rewards can build much stickier, long-term relationships that reward existing ingrained habits, rather than making customers join a program, perform new, possibly unfamiliar actions, then make them wait to earn and redeem points.
However, to successfully embed a brand into a customer's daily life, organizations need to employ deep, contextual personalization. This is where AI enters the picture, bringing both unprecedented power and significant risk.
Related Article: Why AI Agents Are the New Power Players in Online Shopping and Loyalty
The Double-Edged Sword: 'Good' vs. 'Bad' Personalization
When deployed effectively, AI meaningfully strengthens loyalty by supercharging customer data analysis to generate predictive insights and deliver seamless experiences across all channels. McKinsey found that when a bank orchestrates customer interactions from a single, cohesive view, they can double their digital sales, triple cross-sell rates and boost overall customer engagement by 40%.
"Good" personalization feels invisible and supportive. It’s a way to unify the customer experience, with appropriate context and relevance, across every contact the customer has with the bank.
However, the drive to personalize can quickly veer into what could be seen as “bad" personalization when it ignores privacy, bombards the user with disconnected messages across multiple, un-unified channels or simply lacks human nuance. In a nutshell, bad personalization feels creepy. Using behavioral data to streamline how a customer navigates a banking app is helpful but directly messaging them about a specific purchase can feel invasive.
As a 2025 Dentons survey of the financial sector found, over-automation risks eroding trust in a bank entirely: 57% of these organizations believe that a lack of human oversight in AI-assisted processes could lead to critical errors and liability.
The Last Mile: CX as the Ultimate Differentiator
This fear of errors that could be caused by set-it-and-forget-it automation highlights why customer experience and service teams have become the last mile of loyalty. AI excels at handling repetitive, low-risk servicing tasks, but it should not be used to simply deflect customer service issues.
To prevent this, businesses must build human-in-the-loop escalation directly into their customer-facing AI tools, especially for more complex service issues. An AI chatbot can handle basic, repetitive customer service issues, such as handling FAQs, freeing up real people to handle the more complicated issues that arise.
For example, think about a scenario where an AI chatbot detects a customer is getting frustrated. It should be built so that it quickly and seamlessly escalates the chat to a human agent who’s armed with the full context of the interaction. The human layer ultimately contributes to brand perception during these important interactions.
AI can also be used to detect deviations from patterns and signals that can indicate a customer needing human intervention or help. As an example, if there’s a sudden anomaly in a high-wealth VIP client's interactions with a bank — for example, they stop using a premium service they once relied on heavily, or begin to make frequent investment account withdrawals into their checking account — it should trigger an internal alert for a proactive, human-led check-in.
Related Article: AI in Customer Experience: Powerful Use Cases You Shouldn’t Ignore
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Experience-Driven Insights for Enterprise Leaders
We’re past the era where customer loyalty could be “bought” with a point-based system. Today, loyalty is fragile. AI provides the tools to understand and respond to customer needs in real-time, but it is the human-in-the-loop nuance, the transparency of data usage and communication consistency that reinforces relationships.
By combining the power of AI tools with an empowered, empathetic CX team that responds at just the right time, it becomes easier to transform everyday interactions into lasting loyalty.
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