Qualtrics has unveiled XM Data & AI, a new approach to Experience Management designed to help organizations use customer, employee, product and brand data to simulate outcomes, predict behavior and deliver actions during critical experience moments.

The company says its new Qualtrics XM Data & AI Platform will be available in 2027, expanding its existing experience-management technology toward AI-driven decision-making. Qualtrics is positioning the platform around what it calls the “Experience Gap” — the difference between what people expect from a company and what they ultimately experience.

According to Qualtrics, nearly $3 trillion in sales is at risk from poor customer experiences. The company argues that organizations have historically lacked technology capable of translating experience signals into timely action at scale.

Market Landscape

Customer experience management has traditionally centered on collecting feedback through surveys, analyzing sentiment and measuring satisfaction. While these systems can provide valuable insight, much of the process remains retrospective: organizations learn what happened after an interaction has already occurred.

Qualtrics is attempting to shift that model toward predictive and prescriptive experience management. Its proposed platform combines experience data with AI capabilities intended to help organizations assess potential decisions before deployment, anticipate individual behavior and embed actions directly into customer or employee interactions.

The company’s May 2026 acquisition of Press Ganey Forsta is also central to the expanded data strategy. Qualtrics says the $6.75 billion acquisition adds decades of healthcare experience data and established governance capabilities to its broader XM dataset. Press Ganey brings healthcare experience data spanning more than 41,000 facilities, according to Qualtrics.

Strategic Outlook

A central component of XM Data & AI is the concept of continuous “Experience Loops,” or X-loops. Instead of treating a customer journey as a linear process with a defined endpoint, Qualtrics describes these loops as continuously connecting acquisition, retention and growth.

The platform is designed around three capabilities: simulation, prediction and trusted outcomes. Simulation can be used to test potential customer reactions before a pricing, product or policy decision is implemented. Prediction is intended to identify what an individual may do while there is still time to intervene. Trusted outcomes focus on embedding AI-driven actions directly into business processes.

Qualtrics also emphasizes its experience ontology, which provides context around experience data, including who a signal relates to, where it occurs in the lifecycle and what outcome may be appropriate.

The strategic implication is significant for marketers. If experience data can move from retrospective reporting to predictive decision support, customer experience could become more tightly connected to customer lifetime value, personalization and operational execution.

Top Insights

• Experience data is moving toward prediction: Qualtrics wants organizations to act before experience problems become outcomes.
• Simulation becomes a decision tool: Digital representations of customers could allow organizations to test pricing, products and policies before deployment.
• Context remains critical: Qualtrics argues that AI needs structured experience context to produce more reliable outcomes.
• Healthcare expands the data foundation: The Press Ganey Forsta acquisition adds healthcare experience data and governance capabilities to the platform.

Get in touch with our MarTech Experts.