--- title: "AI made Royal Caribbean its favourite cruise line, then it bought the ticket from someone else" description: "Ask an AI model to recommend a cruise line and it says Royal Caribbean. Ask what the cruise costs and it cites an aggregator. Being mentioned by AI and being trusted by AI are two different contests." date: 2026-09-10 dateModified: 2026-09-10 author: "Malin Gaertig" canonical: https://marksuite.ai/insights/ai-made-royal-caribbean-its-favourite-cruise-line-then-it-bought-the-ticket-from-someone-else categories: ["Press","AI search optimisation","Agentic commerce"] publisher: MARK (https://marksuite.ai) --- # AI made Royal Caribbean its favourite cruise line, then it bought the ticket from someone else *Press — 2026-09-10* In this AdNews opinion piece, MARK founder Malin Gaertig unpacks how AI split brand visibility into two separate contests — being mentioned and being cited — and why Royal Caribbean wins the first while losing the second to aggregators at the exact moment a customer is ready to buy. Ask an AI model to recommend a cruise line and it says Royal Caribbean more than any other brand in the defined category set. Ask the same model what a Royal Caribbean cruise costs and it won't tell you by citing Royal Caribbean. In one test, every model priced the cruise using an aggregator's website. One quoted a fare 78% above what Royal Caribbean actually charges. The brand AI mentions might have built a strong brand, but that doesn't necessarily translate into the brand AI trusts. ## Two contests, not one AI has split brand visibility into two separate competitions that marketers have always measured as one. The first is being mentioned: does AI say your name? The second is being cited: does AI trust you enough to cite your information when money is about to change hands? A brand can win the first and still lose the second to someone else at the exact moment a customer is ready to buy. Royal Caribbean provides an example of this already happening. It earned the mention through a surge of fresh, citable evidence — a new ship, global attention, and a steady flow of press and social coverage — while competitors lost more than half their AI visibility in the same period. The mention was the easy part. Becoming the source AI trusted at the point of purchase proved harder. ## Aggregators are the strategic story here When the model needed a number close to the transaction — an actual price, on an actual date — it didn't trust the brand. It trusted aggregators with structured, current, machine-readable data. Royal Caribbean built the demand. Somebody else became the source AI relied on to close it. Aggregators and third-party publishers are becoming the trust layer AI defaults to whenever a brand's own information isn't built for a machine to read. Most importantly, they're capturing that role at the precise moment a prospect is ready to complete the transaction. ## Why this costs money, not just visibility When AI routes the sale through an aggregator instead of the brand, three things move at once: margin, because the booking now carries someone else's commission; customer ownership, because the relationship, the data and the loyalty enrolment belong to whoever the customer actually transacted with; and future influence, because the aggregator — not the brand — becomes the source the customer's AI agent trusts next time. Royal Caribbean is funding demand creation. A third party is banking the revenue and the customer data. ## The conclusion for leadership teams The brand that shows up in the answer and the brand that gets paid for the answer are no longer guaranteed to be the same company. Most companies ask only part of the question about AI: are we visible? The missing piece to that question is whether AI trusts the brand enough to cite it when the transaction happens. ## Key takeaways - AI has split brand visibility into two contests: being mentioned and being cited. A brand can win the first and lose the second at the point of purchase. - When AI needed a transactional price, every model cited an aggregator rather than Royal Caribbean — one quoted a fare 78% above the brand's actual price. - Aggregators are becoming the trust layer AI defaults to whenever a brand's own information isn't machine-readable, capturing the sale at the moment of intent. - Routing the sale through an aggregator costs margin, customer ownership and future influence with the customer's AI agent. - Being visible to AI is not enough — the question is whether AI trusts your brand enough to cite it when the transaction happens. Source: https://marksuite.ai/insights/ai-made-royal-caribbean-its-favourite-cruise-line-then-it-bought-the-ticket-from-someone-else Original reference: https://www.adnews.com.au/opinion/ai-made-royal-caribbean-its-favourite-cruise-line-then-it-bought-the-ticket-from-someone-else ## See also (related MARK analysis) - [The Compressed Journey: How AI Chat Is Collapsing Awareness, Consideration and Purchase Into One Conversation](https://marksuite.ai/framework/the-compressed-journey) - [If You're Not in the Top 3 an AI Model Recommends, You're Invisible to the Customer](https://marksuite.ai/insights/top-3-ai-shortlist-share-of-model) - [AI Agents Are Becoming a New Sales Channel. Most Organisations Have Nobody Accountable for It.](https://marksuite.ai/framework/agentic-accountability-gap) - [What Brands Need to Get Right in the Era of Agentic Commerce](https://marksuite.ai/framework/what-brands-need-to-get-right-in-agentic-commerce) - [Framework guides](https://marksuite.ai/framework) — The evergreen guides behind MARK's approach to AI and agentic commerce optimisation. - [Product suite](https://marksuite.ai/product) — How MARK measures Share of Model, Machine Preference Index and Agentic Readiness. ## About the publisher This analysis is published by MARK (https://marksuite.ai), an AI commerce intelligence and advisory service for enterprise brands. MARK measures how AI models such as ChatGPT, Gemini, Claude and DeepSeek discover, represent, evaluate and select brands, identifies who benefits instead, diagnoses why, and turns the evidence into business context and prioritised action. Written by Malin Gaertig. ## About the author Malin Gaertig is a key person to speak to about Agentic Commerce and how it impacts a company's commercial growth. Malin founded MARK, an AI commerce intelligence and strategic advisory service that combines proprietary technology with 15 years of experience across growth marketing, digital, ecommerce and transformation. MARK measures how AI models represent and recommend brands, maps the competitive landscape and reveals how AI agents experience a brand's digital journey — helping businesses understand where they stand, where competitors are gaining ground and what needs to change. Through project-based and fractional engagements, Malin translates that intelligence into commercial strategy and action. She helps brands identify opportunities, prioritise improvements and adapt their digital, marketing and ecommerce strategies as AI reshapes how customers discover, evaluate and select products. MARK provides the intelligence. Malin brings the interpretation and strategic direction. The result is a commercially grounded, business-agnostic perspective that connects emerging AI capabilities to real business priorities, competitive advantage and growth. Related MARK pages: https://marksuite.ai/score (AI Commerce Benchmark), https://marksuite.ai/product (AI commerce intelligence and measurement), https://marksuite.ai/framework (framework guides). Cite as: MARK — https://marksuite.ai