Montserrat Padierna

Montserrat Padierna

Customer Intelligence & Experience Lead Walmart Canada
Montserrat Padierna

24 February 2026

11:00 AM A human-led approach to building AI-enabled customer listening in-house for scalable insight

With customer data volumes exploding and decision cycles shrinking, customer insights teams are under pressure to move faster without losing credibility. In this session, Montserrat Padierna, Customer Intelligence and Experience Lead at Walmart Canada and CX Network Advisory Board member, shares how she has approached building AI-enabled customer listening capabilities in-house as more than a reporting function. Padierna’s system is a living experience management system that supports short-term and long-term priorities.
Rather than leading with tools, this approach starts with intent: clear business questions that shape which data is used, how AI is applied, and how insight is delivered back to the organization. AI plays a critical role in connecting data across transactions, customer care interactions, reviews, ratings, and behavioural data, providing consistency and scale that wouldn’t be possible manually. But human expertise remains central. Experienced practitioners guide the work by asking the right questions and validating outputs, ensuring insights are relevant and actionable.
The session will also take an honest look at adoption challenges from fear and resistance around AI, to the risk of over-automation. We will share practical lessons on narrowing use cases, closing the loop with the business, and embedding governance so AI strengthens customer listening without replacing the human judgment it depends on.
Attendees will learn:
  • How to build AI-enabled customer listening capabilities in-house while keeping human expertise at the centre
  • How to move from dashboards to decision-ready insight by anchoring AI to real business questions and KPIs
  • What it takes to scale AI responsibly including managing change, preventing misinterpretation, and continuously improving through human feedback