Zainab Hussain is a distinguished e-commerce strategist who has spent her career bridging the gap between complex data operations and front-end customer engagement. With a background rooted in optimizing retail decision-making, she has a front-row seat to the industry’s shift toward autonomous technologies. In this discussion, we explore the findings of recent research involving 200 high-level retail executives, focusing on the technical hurdles and strategic opportunities presented by agentic AI. We examine why traditional loyalty programs are struggling to keep pace, the move toward hyper-personalization at scale, and why the future of customer retention lies in making shoppers feel understood rather than just targeted.
The recent data suggests a significant disconnect between the desire for agentic AI and the actual infrastructure currently in place. Why do you think nearly three-quarters of retailers admit their loyalty systems aren’t quite ready for this leap?
When we look at the survey of 200 Chief Customer Officers and Insight Leaders, the reality is quite stark; while everyone sees the potential of AI, a staggering 72% admit their foundations are lacking. Only 29% of retailers believe their current loyalty systems are actually prepared to handle the deployment of agentic AI. This gap exists because many legacy systems were built to be reactive—recording what a customer did in the past rather than predicting and acting on what they will do next in real-time. Moving to an agentic model requires a level of data fluidity and processing speed that most older CRM infrastructures simply weren’t designed to support. It is a massive technical undertaking to transition from a system that just tracks points to one that can autonomously identify opportunities and recommend strategic actions.
Beyond just automating tasks, there’s a strong push toward optimizing retail decisions through intelligent agents. How do you see the role of the human analyst changing as AI takes over the heavy lifting of data processing?
The shift we are seeing is less about replacing humans and more about elevating the work they do. Currently, 4 out of 10 retailers believe that AI will significantly reduce the need for human analysts to spend their days churning out routine reports. Instead of spending weeks trying to explain “what happened” in the past, teams can focus on complex commercial judgments and high-level strategy. About 54% of retail leaders feel the biggest impact over the next few years will be the sheer speed of customer insight and decision-making. When an intelligent agent handles the routine operational choices, it frees up the human experts to act on AI-driven recommendations that require a more nuanced, emotional touch.
We often hear about personalization, but the move toward one-to-one engagement at scale seems to be the “holy grail” for loyalty programs. What makes agentic AI the catalyst that finally allows retailers to break away from broad customer groupings?
For a long time, “personalization” in retail really just meant sorting people into large buckets based on general demographics, but 44% of retailers now believe AI will finally enable truly individual experiences. Agentic AI is the key because it allows for activation at a scale that is physically impossible for human teams to manage manually. Instead of a marketing team creating five different email versions for five customer segments, the AI can theoretically create a unique experience for every single shopper simultaneously. It moves the needle from “customers like you bought this” to “we know exactly what you need right now,” allowing brands to respond to changing behaviors the moment they happen. This real-time understanding is what transforms a standard loyalty program into a proactive partner in the customer’s journey.
There is a delicate balance between maximizing profit and maintaining customer trust, particularly regarding pricing strategies. Why is there a growing sentiment that personalized offers, rather than dynamic pricing, will be the true battleground for loyalty?
The distinction between these two strategies is vital because one builds trust while the other can quickly erode it. Dynamic pricing often feels like a moving target to the consumer, which can make them feel exploited or manipulated depending on the time of day or their location. In contrast, personalized offers make a customer feel seen and understood, which is why experts like Thomas Hill argue this is the real future of loyalty. When you use agentic AI to deliver a specific value or a relevant discount to a single user, it reinforces the relationship rather than just squeezing out a few extra cents of margin. The goal is to optimize the decision for the long-term value of the customer, not just the immediate transaction.
What is your forecast for the adoption of agentic AI in CRM and loyalty functions over the next few years?
My forecast is that we will see a rapid “first-mover” advantage where about one-third of the industry—those who have already identified loyalty and CRM as the primary functions for this tech—will pull significantly ahead of the pack. By the time we reach the 2026 RTIH Innovation Awards in London, I expect we will be seeing case studies where agentic AI isn’t just a pilot program but the backbone of the entire customer retention strategy. Retailers will stop looking at loyalty as a series of disconnected campaigns and start viewing it as a continuous, autonomous conversation. The winners will be those who move past the reporting phase and successfully integrate AI to handle routine operational choices, allowing their brands to be more responsive and human-centric than ever before.
