Has artificial intelligence ruined Tripadvisor or merely exposed the weaknesses of the review system?
Tripadvisor has not disappeared, nor has artificial intelligence destroyed it overnight, but generative AI has seriously changed the question on which that platform built its influence for years: can an unknown person on the internet be trusted when describing a hotel, restaurant, excursion or attraction. The platform that became globally recognizable precisely because of its mass of user reviews now finds itself in a dual role. On the one hand, it is itself introducing artificial intelligence to summarize reviews, suggest itineraries and connect travelers with offers. On the other hand, it has to convince users that the same technological wave is not turning reviews into an endless series of convincing but unverified texts.
The question is especially important because Tripadvisor’s model is not only media-based or social, but also commercial. Reviews, ratings, photographs and rankings influence decisions about bookings, restaurant visits and the purchase of excursions. According to data the company itself published in its transparency report for 2025, in 2024 it received 31.1 million reviews, and 4.2 million of them were moderated, or 13.5 percent of all reviews. Tripadvisor states that in the same year it prevented or removed 2.7 million fake reviews, which shows that the problem is not a marginal phenomenon, but constant pressure on the very infrastructure of trust.
What AI has changed in the old problem of fake reviews
Fake reviews existed long before generative artificial intelligence tools became widely available. Hotels, restaurants and intermediaries could previously order positive comments, try to damage competitors with negative ratings or encourage guests to leave insincerely favorable impressions. What has changed is the cost and persuasiveness of producing such content. Instead of short, repetitive and easily recognizable comments, AI can in a few seconds create text that sounds personal, detailed and grammatically polished, with descriptions of the room, staff, food, view or an alleged problem during the stay.
Because of this, it is no longer only a question of whether a platform can recognize bots or obvious patterns of behavior. The challenge has become significantly more complex: algorithms and moderators must distinguish a real experience from text written to imitate a real experience. According to a statement by the U.S. Federal Trade Commission from August 2024, the new rules against fake reviews specifically also include representations that falsely suggest they were written by a real person, including reviews generated by artificial intelligence. The FTC thereby acknowledged that generative AI is not only a technological novelty, but also a regulatory problem in the field of consumer protection.
Tripadvisor claims in its transparency report that it fights manipulation through a combination of automated systems, human moderators, investigators and community reports. The company states that it checks behavioral patterns, technical signals and review content, and that it stops some suspicious posts before they become visible to users. But the very fact that millions of reviews have been removed or blocked shows how exposed the system is to attempts at manipulation. At a time when AI can generate thousands of different versions of a similar impression, the fight against fake content increasingly resembles a race between production tools and detection tools.
Tripadvisor is simultaneously using AI as a product
Artificial intelligence is not only a threat to Tripadvisor; it is also part of its new strategy. Back in 2023, the company began introducing AI summaries of hotel reviews, initially for some users and for frequently reviewed hotels. According to the company’s announcement at the time, the goal was for travelers to more quickly see the most important themes that recur in reviews, such as location, cleanliness, comfort, breakfast or value for money. Such a function can be useful because many properties have thousands of comments that are difficult to review manually.
The problem arises when the intermediary layer between users and the experiences of other travelers moves even further away from the original content. If an AI summary extracts the wrong emphasis, softens negative comments too much or fails to show the difference between older and newer reviews, the user may get an impression that is not completely faithful to the real set of experiences. Tripadvisor states that its AI tools rely on reviews, ratings, photographs and data connected with real trips, but trust in such summaries depends on the quality of the input data. If some of the input reviews are fake, exaggerated or artificially generated, AI can only package an already contaminated set of information more neatly.
In April 2026, Tripadvisor emphasized in a post about AI travel planning that travelers are increasingly moving between different applications, assistants and platforms, and that it wants to be present in new conversational interfaces as well. The company cited partnerships with OpenAI, Perplexity, Anthropic’s Claude and Amazon’s Alexa+, explaining that recommendations can be based on Tripadvisor’s global travel insights and connected with bookings. This shows that the company is not trying to stop the AI wave, but is trying to turn it into a distribution channel. At the same time, a key question opens up: will users in an AI answer even see the difference between a verified recommendation, a sponsored result, a popular property and content created through review manipulation?
Why users feel the platform has lost its old credibility
Part of the dissatisfaction with Tripadvisor cannot be reduced only to artificial intelligence. For years, users have criticized major review platforms because of too many advertisements, commercial priorities, unclear rankings, outdated comments and the difference between what is popular among tourists and what is truly high-quality. AI has intensified that problem because it has further blurred the boundary between authentic experience and optimized content. When a user encounters a review that sounds too generic, too smooth or too much like an advertisement, trust weakens even if the review is actually real.
Tripadvisor’s challenge is therefore not only technical, but reputational. Review platforms function as long as users believe that the average of a large number of opinions is better than an individual recommendation. If suspicion arises that a significant part of that average has been artificially created, purchased or algorithmically reshaped, the value of the entire system falls. It is not necessary for most reviews to be fake for damage to occur; it is enough that users no longer know which ones are reliable. In the digital environment, trust is lost faster than it is rebuilt.
At the same time, one should avoid the exaggerated claim that AI has single-handedly “destroyed” Tripadvisor. The available data show a more complex picture. The company still has a huge base of user content, is developing new AI functions and generates revenue through a broader portfolio that includes Tripadvisor, Viator and TheFork. According to the company’s investor releases, annual reports continue to describe a business in which content, advertising, experiences and bookings are interconnected. In other words, AI has not brought down the platform, but has further pressured its most sensitive point: the belief that rankings and reviews reflect real experiences.
Regulators are taking an increasingly strict view of fake reviews
The growth of the fake review problem can also be seen in regulatory reactions. In 2024, the U.S. FTC adopted a rule prohibiting the purchase and sale of fake reviews and testimonials, including content that falsely represents a person’s experience or is attributed to a person who does not exist. The agency announced the possibility of civil penalties for knowing violators and emphasized that fake reviews harm consumers and honest competitors. Although these rules apply to the U.S. market, they are also important for global platforms because they shape expectations about the responsibility of digital intermediaries.
In the European Union, the broader framework is provided by the Digital Services Act, which, according to the EUR-Lex summary, sets responsibilities for online platforms in the fight against illegal content, disinformation and risks to consumers, and requires greater transparency. In addition, EU consumer law rules had already strengthened requirements for traders who display reviews, especially regarding explanations of whether they verify that reviews come from real users. In the United Kingdom, new rules under Competition and Markets Authority guidance additionally target fake reviews, hidden incentivized reviews and misleading information derived from reviews.
Such a regulatory direction means that platforms cannot defend themselves only by claiming that they are neutral intermediaries. If reviews influence consumer decisions, and the platform earns revenue from those decisions, it is increasingly expected to actively prevent manipulation. For Tripadvisor, this means that moderation tools, user reports and transparent explanations of rankings are becoming just as important as new AI features. Otherwise, technological innovation may look like an attempt to accelerate sales, not to protect the quality of information.
AI can help, but it cannot restore trust by itself
There is also a positive side to artificial intelligence in this context. AI can help identify unusual patterns, networks of connected accounts, sudden waves of similar reviews, suspicious language structures and technical traces that would not be immediately visible to human moderators. Tripadvisor states in its transparency report that it uses advanced technology and human analysis, which is a reasonable approach because automation and editorial judgment must complement each other. A system that relies only on people would be too slow for millions of posts, while a system that relies only on algorithms could wrongly penalize real users or miss sophisticated manipulation.
But AI cannot solve the problem of trust if users are not clear about what they are looking at. The user must know whether the text is an original review, an algorithmic summary, a paid advertisement, a recommendation based on popularity or a personalized result. It is especially important to clearly mark when artificial intelligence takes on the role of editor and condenses a multitude of opinions into a few sentences. Otherwise, the platform risks users starting to perceive everything displayed as a marketing-shaped recommendation, even when it is based on real experiences.
For businesses that depend on Tripadvisor, the consequences are also significant. A restaurant, hotel or guide with authentically good ratings can lose visibility if competitors successfully manipulate the system. On the other hand, a property unfairly affected by fake negative reviews can suffer real financial damage. That is why the fight against fake reviews is not only a matter of the platform’s reputation, but also of market competition. In its statement about the new rule, the FTC explicitly linked fake reviews with the unfair diversion of business away from honest competitors.
The answer to the question: it has not destroyed it, but it has forced it to change
The most accurate answer to the question of whether AI has ruined Tripadvisor is: it has not ruined it, but it has exposed and increased the weaknesses on which the entire economy of online reviews is based. Tripadvisor emerged at a time when a large amount of user opinions acted as a counterweight to official brochures, advertisements and star ratings awarded by institutions or the industry. Today, that same mass of opinions must defend itself against machines that can produce convincing text without travel, without a meal, without an overnight stay and without a real experience.
This does not mean that reviews have lost all value. They are still useful when read critically, especially when newer comments, user photographs, recurring patterns of praise and complaints, and property owners’ responses are compared. But it is no longer enough to look at the average rating and a few highlighted comments. The AI era requires more cautious reading, and it requires platforms to provide clearer labels, better moderation and a more open explanation of how rankings and summaries are created.
Tripadvisor’s future will therefore probably not depend on whether it uses AI, but on whether it uses it in a way that increases, rather than reduces, trust. If artificial intelligence helps users find relevant, fresh and verifiable information more quickly, the platform can retain an important role in travel planning. If, however, AI further blurs the difference between experience, advertisement and algorithmic recommendation, the perception that Tripadvisor has lost credibility could continue to spread. In that sense, artificial intelligence is not the end of Tripadvisor, but a test of its core value: can it, in a sea of automated content, still prove that real people and real journeys stand behind the reviews.
Sources:
- Tripadvisor – Transparency Report 2025, data on the number of reviews, moderation and removed fake reviews (link)
- Tripadvisor Media Center – post on the role of artificial intelligence in travel planning and partnerships with AI assistants (link)
- Tripadvisor Media Center / Hospitality Net – post on the introduction of AI summaries of hotel reviews (link)
- Federal Trade Commission – statement on the final rule against fake reviews and testimonials (link)
- EUR-Lex – summary of the European Union Digital Services Act (link)
- Competition and Markets Authority / GOV.UK – guidance on fake reviews and the obligations of businesses in the United Kingdom (link)