Ulta is positioning artificial intelligence as a personalization tool, and its loyalty program as the fuel that powers it, according to a report by CX Dive.

The headline finding matters for marketing leaders because it names the two assets most CMOs already control — a loyalty database and AI capability — and connects them directly. Ulta's framing treats loyalty data not as a retention metric but as input for individualized customer experiences at scale.

What does Ulta's approach signal?

The retailer's view of AI is deliberately narrow and applied. Rather than treating AI as a standalone initiative, Ulta frames it as an enabler of personalization — a use case with measurable outcomes such as engagement, conversion, and repeat purchase behavior.

The loyalty program plays the central role. Members generate first-party data through purchases, preferences, and interactions. That data becomes the raw material AI systems need to tailor offers, recommendations, and communications to individual shoppers.

This positions the loyalty program as strategic infrastructure. For CMOs weighing where AI investment pays back fastest, the Ulta example points to personalization built on consented first-party data.

Why does loyalty data matter for AI?

First-party data has become the default currency of personalization as third-party identifiers lose effectiveness. Loyalty members voluntarily identify themselves at each interaction, which gives retailers a persistent, permissioned view of the customer.

That persistence is what makes AI personalization practical:

• The retailer can link transactions to a known individual over time.
• AI models can learn preferences from actual behavior rather than inference alone.
• Personalized offers can be tied to purchase history and lifecycle stage.

In Ulta's framing, the loyalty program supplies the fuel. AI supplies the engine that turns that fuel into individualized experiences.

What should marketing leaders take from this?

The decision worth noting is sequencing. Ulta connects AI investment to a data asset it already owns and operates, rather than pursuing AI initiatives detached from customer relationships.

For CMOs at retailers and consumer brands, the implication is structural:

• Audit the loyalty program as a data source, not only as a rewards mechanism.
• Identify where AI can act on loyalty data to change customer-facing output — recommendations, offers, messaging.
• Measure personalization against commercial outcomes, since loyalty members' behavior provides the baseline.

How does this fit the broader retail picture?

Retailers across categories are under pressure to personalize at scale while relying less on third-party tracking. Loyalty programs have moved to the center of that shift because they offer a lawful, consented, durable customer identifier.

Ulta's stance, as reported by CX Dive, aligns with that trend: AI delivers value when it operates on rich first-party data, and the loyalty program is where that data concentrates in a beauty retail context.

What are the open questions?

The report does not specify which AI systems Ulta deploys, the size of its loyalty membership, or quantified results from its personalization efforts. Marketing leaders tracking this story will want those details: the models in use, the metrics being tracked, and any reported lift in engagement or revenue attributable to AI-driven personalization.

What is clear is the strategic position. Ulta sees AI as a tool, not a strategy. The strategy is personalization. The loyalty program supplies the data that makes both work.