Key Takeaways for Retail CTOs and the C-Suite in the Age of AI

Retailers today face a perfect storm: economic uncertainty, evolving tariffs, and fast-shifting customer expectations. In response, artificial intelligence investment is accelerating. However, despite the momentum, research shows only 28 percent of executives feel they're using AI effectively, while in retail, one-third of companies have yet to start meaningful AI adoption.

This isn't just a technology gap. For the C-suite, it signals that traditional ways of managing customer experience are falling short. Fragmented data, siloed teams, and outdated workflows are limiting the ability to act with speed and confidence. Closing that gap requires more than just additional tools. It calls for a different kind of operating model: one that prioritizes adaptability, visibility, and cross-functional alignment.

From Functional Focus to Journey Alignment

In many organizations, teams optimize for their own metrics without visibility into what happens before or after their point of contact with the customer. This leads to fragmented experiences — we’ve all had the cringe feeling of getting a personalized offer for a product just returned, or an email push while a support ticket remains unresolved. Customers feel these disconnects even when no single team is at fault.

A journey-led approach reframes the work. Rather than treating customer experience as a series of tasks, it becomes a shared outcome and brings context to insights. AI can play a supporting role by surfacing relevant signals, but only if teams are aligned on which journeys matter most and how progress is measured in relation to the larger organizational goals.

More Relevance, Less Noise

Personalization efforts often fall short because they rely on incomplete or outdated inputs. AI can help bridge that gap, but only when it’s applied with context. Behavior, timing, past interactions … these signals help determine not just what to say, but when and where to say it.

This isn’t about hypertargeting. It’s about reducing noise and making interactions more useful. When teams understand where a shopper is in their journey, personalization becomes more precise and operational load goes down.

From Awareness to Anticipation

McKinsey data shows that retailers have invested heavily in personalization, but these efforts sometimes rely on siloed systems or one-off tools that miss the broader context of what customers actually need in the moment. AI has the potential to change that by drawing on signals like recent purchases, engagement history, and timing. The technology can then guide the retailer when and how to interact more effectively. This makes personalization more relevant and less reliant on constant manual updates.

However, personalization alone doesn’t solve the bigger issue. Most customer experience breakdowns don’t start at the moment of failure. They build over time: from missed handoffs, repetitive processes, or decisions made without shared visibility. AI can surface those early signs, but only if insights are connected across the entire journey. Without that context, even the most advanced systems risk treating symptoms instead of solving root causes.

This is the difference between seeing a problem and anticipating one. With journey visibility, teams can spot patterns, not just anomalies, and course-correct before customers feel the impact.

From Data Overload to Intelligent Action

Retailers are overwhelmed by data, but underpowered in turning that data into coordinated action. Our research shows many leaders fear they're missing key moments, especially in high-stakes areas like payments. With so many tools producing insights in isolation, it becomes hard to determine what matters most.

Journey management offers a path forward by connecting disparate data points into a clear, shared view. This is especially valuable when testing or scaling new payment solutions, whether that’s buy now, pay later (BNPL); QR code checkouts; or biometric verification. A failed transaction isn’t always a payment issue. Sometimes the root cause lies upstream, in the customer’s onboarding experience or in a service journey gone unresolved. By connecting these dots, retailers can make better decisions, faster, and deliver more seamless, consistent payment experiences.

Rethink Dashboards as the Default

Dashboards remain the primary interface for decision-making in most retail organizations, yet the majority of available data goes unused. That’s because dashboards tend to reflect past events, not future needs, and are built for individual functions, not end-to-end outcomes.

Leading organizations are shifting away from static dashboards and toward systems that unify customer signals with operational context. Journey intelligence gives leaders not just a snapshot, but a directional view. This helps them understand where to focus and why.

A More Cohesive Path Forward

AI is not a shortcut to better customer experience. Without clear context and coordination, it risks reinforcing silos rather than breaking them down. For the C-suite, the opportunity lies in rethinking how decisions are made and how customer needs are understood across departments.

Journey management provides the structure for that shift. It enables teams to align on shared goals, act with greater clarity, and use AI where it drives meaningful value. In a competitive retail landscape, the advantage won’t come from having the most data. It will come from knowing how to use it together.

Jochem van der Veer is the co-founder and CEO of TheyDo, an intuitive journey management platform.