How can CX leaders scale AI without creating more risk than value?
That is the central question in this CX Today interview with Rebecca Wettemann, Principal at Valoir, as she joins Rob Wilkinson to unpack how enterprise thinking around AI in customer experience is changing. The conversation shows how many organizations have moved beyond early enthusiasm and are now under pressure to prove that AI can deliver measurable business outcomes without harming trust, increasing costs, or disrupting operations.
Wettemann explains that the market has shifted from fear of missing out to what she describes as fear of messing up. In practice, that means leaders are no longer satisfied with experimentation for its own sake. They want AI initiatives that improve workflows, support customers effectively, and justify the spend. According to Wettemann, one of the biggest barriers remains trust, especially when teams still associate AI with hallucinations, weak chatbot experiences, and unpredictable costs.
The interview also highlights why data integration continues to hold back progress. Wettemann argues that AI needs consistent, current, and correct data to perform well, especially in customer-facing use cases. Rather than trying to build one system that handles everything, she advises organizations to break work into smaller skills and tasks, then apply AI where the business case is clear.
Workforce design is another major theme. Wettemann notes that AI is changing the role of the human agent, with more people taking on higher-value work, supervising AI-driven interactions, and helping refine AI agents. That shift, she says, requires leaders to rethink metrics, compensation, onboarding, and support structures.
For CX leaders wondering where to begin, Wettemann’s advice is practical: experiment broadly, keep pilots small, learn what your data and workflows can support, and use those findings to build the right path into production.
