During a live event on September 9 featuring CEO Jason Maynard and cofounder Ryan Smith, Qualtrics announced a bold new vision for the future — a future where its platform becomes a decision system. The new vision extends beyond collecting and analyzing customer feedback and data to predicting and taking action. Coming in 2027 are three new capabilities:
- Simulation: tests potential decisions against synthetic personas and digital twins to model how customer groups may respond before actions are taken.
- Prediction: uses models and lifetime value scoring to anticipate individual customer behavior and recommend next-best actions.
- Trusted outcomes: applies governance and orchestration to enable AI-driven actions.
It’s a compelling vision, so it’s no surprise that we’ve heard it before. For years, technology vendors have promised a future where organizations can predict customer needs, orchestrate journeys in real time, and automatically take the next best action. Qualtrics itself pursued that vision through its acquisition of Usermind in 2021, though the offering largely sat on the shelf due to low client demand.
Qualtrics’ leaders posit that AI finally makes the vision a reality. They stressed that their new offering will solve the “experience gap” between what customers expect and what is delivered. And they are right to be bullish on their ability to deliver. AI makes the simulation, prediction, and outcome loops possible, and the company is investing in strong foundations like AI agent logs for traceability.
The Real Challenge Is No Longer Technology
The big problem to overcome is the readiness gap, not the experience gap. Organizational capabilities and readiness are advancing much more slowly than technology capabilities. Many CX teams continue to struggle with the same foundational issues they faced a decade ago:
- Customer data remains fragmented across systems.
- Experience data and operational data remain disconnected.
- Ownership of customer journeys is spread across multiple teams.
- Governance models remain immature.
- Success metrics often optimize channels rather than customer outcomes.
These barriers are precisely what limited previous generations of journey orchestration, next-best action, and decisioning technologies. There is little evidence that AI alone eliminates them. In fact, AI may amplify them.
Organizations with fragmented customer data will generate fragmented predictions. Organizations with disconnected systems will struggle to operationalize recommendations. Organizations without clear accountability for customer outcomes will find it difficult to trust automated decisions, regardless of how sophisticated the underlying models become.
Execution May Matter More Than Vision
The readiness challenge does not belong solely to customers. Qualtrics itself will need to reimagine its culture, its pricing, and its sales and partner strategy to deliver on this vision. For Qualtrics, best known as a DIY tool, the difficulty of shifting to more services-led engagements should not be underestimated. Delivering on its vision will require a different mix of services, ecosystem partners, implementation approaches, and advisory capabilities than many CX programs have needed historically.
That means helping customers:
- Connect fragmented experience and operational data.
- Establish governance for automated decisions, especially in highly regulated industries.
- Define ownership of cross-functional customer outcomes.
- Operationalize new ways of working with AI-enabled decision-making.
What CX Leaders Should Do Next
CX leaders evaluating announcements like this should resist the temptation to begin with technology evaluation. Instead, start with readiness.
Ask three questions:
- Do we have sufficiently connected customer data to support trustworthy predictions?
- Do we have governance processes that define when AI can recommend actions and when humans remain accountable?
- Do we have clear ownership of customer outcomes across channels, business units, and functions?
If the answer to any of these questions is no, the next investment should be less about AI and more about building the foundation required to use AI effectively.
There is a lot more to discuss coming out of the event this week. Forrester clients, book a call with me if you’d like to go deeper.
