Every CX vendor right now is promising to close a gap. Whether its between what customers expect and what businesses deliver, between data collected and decisions made, or between where teams optimize and where customers actually are.
This week, I'd like to explore three major announcements that each claim to have closed a gap facing CX teams.
It may be easy to get lost in the solutions that vendors are offering. But for buyers, the real lesson could come from understanding why these 'gaps' are being targeted, and whether their organizations are quietly facing the same issue.
Editor's Pick - Can Simulation Actually Close the Experience Gap?
Hitting 'Publish'
Qualtrics built its entire announcement around an eye-grabbing stat:
"Close to $3 trillion in sales is at risk from poor customer experiences"
Its answer is the new XM Data & AI Platform, due in 2027, which adds simulation and prediction to experience data. The pitch is that businesses can now test a pricing change or a policy shift on digital twins of real customers before it ever reaches a live audience, rather than finding out how customers feel after the fact.
Qualtrics CEO Jason Maynard frames this as the missing piece that finally makes experience strategy executable:
"Experience has always been the strategy every leader believed in, but unfortunately the technology wasn't available to execute at scale"
Early results look genuinely strong. TruGreen reported $7 million in ROI from closed-loop feedback alone, with $30 million in total ROI across retention and churn prevention.
But simulation is only as good as the data and rules behind it, and Qualtrics is explicit that every action still gets checked against an organization's own policies before it reaches a customer.
That's reassuring from a governance standpoint, but it also means the platform's real test isn't whether it can simulate a decision. It's whether the organizations using it have the internal clarity to define what a "trusted" outcome actually looks like before they let the system act on it.
Can Autonomous Engagement Coexist With The Trust Gap?
Insider One's new Agent One system draws a sharp distinction between agents that assist and agents that act. Co-founder and CTO Serhat Soyuerel shared:
"Marketers were promised agents. What they got were operators. They complete part of the work, then hand control back to the team"
Agent One is built to remove that handback entirely, combining a system that runs engagement decisions (Agent One Teams) with one that listens to customers directly (Agent One Audiences), feeding each other in a continuous loop.
CEO Hande Cilingir frames it as a shift in priorities:
"The industry spent the last decade teaching systems to remember customers. The next decade will belong to systems that know when to change their mind"
While this next chapter of agentic AI sounds exciting, it naturally raises questions of trust. Naturally, enterprise leaders may end up asking themselves: "how much oversight are we actually keeping over decisions made at a scale no human team could review?".
The infamous 'Hugging Face' incident of an AI agent gone rogue is enough to send shivers up the spine of many enterprise leaders. Our colleagues at UC Today delved into this topic in depth.
