Why agentic AI is the new “best buddy” for retail customer experience teams

What happened

A new poll of supply chain and logistics professionals shows retail customer experience teams remain in the early, exploratory stages of putting artificial intelligence to work on operational decisions. Only 29% of respondents said they are currently using AI to support real-time operational choices, while the largest group, 37%, described themselves as still testing pilots and trying to distinguish genuine capability from marketing claims.

The survey, covered by Retail Customer Experience, also asked where practitioners expect AI to deliver the most value. Dynamic routing and real-time replanning of deliveries emerged as the leading use case, cited by 34% of respondents — a signal that the industry sees the clearest near-term payoff in keeping delivery promises intact when conditions change.

Why it matters

For retailers, customer experience increasingly lives or dies on logistics: getting the right order to the right door on time. This data suggests the conversation has shifted from whether AI belongs in that process to what role it should actually play once deployed — a more difficult, operationally sensitive question. Agentic AI's appeal here is its capacity to react to disruption in real time, adjusting routes and delivery plans as conditions change, rather than simply analysing data after the fact.

The gap between enthusiasm and deployment is itself the story. Leaders are being asked to commit to AI-driven decisions that touch customer-facing promises, and many are understandably cautious about handing over control before trust in the technology's judgement is established.

By the numbers

• 29% of supply chain and logistics professionals are currently using AI to support operational decisions.
• 37% are actively exploring or piloting AI applications without full deployment.
• 34% identified dynamic routing and real-time replanning as the area where AI is expected to add the most value.

The Renascence take

The headline risk in this data isn't that adoption is slow — it's that most organisations are framing AI adoption as a technology rollout rather than a trust-building exercise with their own operations teams and, by extension, their customers.

What this survey really captures is a confidence gap, not a capability gap. Dispatchers and planners don't resist agentic AI because it can't reroute a delivery — they resist it because no one has shown them, in small and visible ways, that the system's judgement is sound under pressure. The operators who move fastest from piloting to real deployment won't be the ones with the most sophisticated models; they'll be the ones who let AI earn authority incrementally, starting with low-stakes decisions customers never notice, before trusting it with the moments that define whether a delivery promise is kept.