The arrival of agentic commerce means organizations now operate in a trading environment where verified claims – not marketing pitches – drive referral traffic from AI search and therefore, drive sales.
This shift has led to the creation of an entirely new vendor category and a new generation of essential tools. It has also placed a renewed emphasis on online customer reviews and other trust signals, such as testimonials and social media follower counts, which customers – both human and algorithmic – depend on to inform their buying decisions.
Those who worked hard to deliver 5-star experiences are now reaping the rewards of their efforts. On the other hand, those who bought their reputations through paid-for reviews and follower counts, are quickly seeing their fortunes change as algorithmic buyers increasingly penalize those they deem to have taken shortcuts.
The brands that buy credibility
In agentic commerce genuine credibility is less likely to be blacklisted by bots and genuine customer reviews drive AI search results. Still, the evidence suggests a huge number of brands are trying to buy credibility by manipulating trust signals.
Paid for and AI-generated reviews aren't difficult to spot: they are mostly 5-star, vague and short, and they often carry similar wording. Amazon, Trustpilot, and Google are already using their own AI tools to identify and remove posts that carry these hallmarks, and AI assistants such as Claude, Gemini and ChatGPT are wise to them, too.
Yet according to figures published by Anybusiness.com.au, searches for the term "buy reviews" have increased 1,325% in the past year, with the term reaching 6.7 million searches in April 2026.
Its findings, dated 5 May, 2026, also include data that shows searches for "buy followers" reached 981,000 in the past month, an increase of 48 percent year-on-year.
The conclusion is that this suggests there is "a growing black market for online credibility as businesses, influencers and sellers compete for consumer trust".
Director of operations, Mary Tamvakologos, says: "Reputation is one of the most valuable assets a business can build. Buying reviews or followers might look like a shortcut, but it can damage long-term trust if customers realise the credibility was manufactured."
Instead, Tamvakologos advises businesses to "build proof properly", for example by asking real customers for reviews, responding to complaints, showing transparent policies, publishing useful product information and making it easy for people to verify who is behind the business.
"In ecommerce, trust is not just a marketing asset. It directly affects conversion, repeat purchases and customer loyalty. Brands that invest in genuine customer experience will always be in a stronger position than those trying to buy the appearance of one," Tamvakologos adds.
The new indicators of trust
The rise in paid-for reviews poses a question about authenticity in the new ecommerce landscape: If more web content (including reviews) is now AI-generated and/or paid for, and AI assistants are basing decisions on this content, how can customers and their AI assistants distinguish the real reviews and experiences from the fakes?
Allyse Slocum, VP of product and audience marketing at Trustpilot, says: "As AI-generated content becomes more common, verification and transparency matter more than ever. Indicators such as verified purchases, specific experiential language, recency, and reviewer consistency help both humans and AI systems distinguish genuine customer feedback from synthetic or automated content."
At Trustpilot, Slocum says "robust platform safeguards" include filtering all reviews for fakes using cutting-edge fraud detection technology and employing a dedicated team of content integrity specialists. Trustpilot also allows its active community of consumers and businesses to flag suspicious reviews.
In 2025, the platform removed 7.8 million fake reviews, with 91 percent detected automatically.
Recency, relevance, and ranking: How to really improve discoverability in AI search
Clearly, authenticity is the key to success.
As Slocum explains, in AI search, discoverability depends less on marketing language and more on "trustworthy, up-to-date signals that show real-world experience".
"Brands should focus on earning and maintaining reputable, third-party customer proof on a consistent basis, not just during peak shopping seasons," she says. "That means building a consistent flow of reviews, making it easy for customers to leave detailed feedback, and ensuring that review content is structured in a way that AI systems can understand," she adds.
To ensure Trustpilot maintains its reputation as a dependable source of reputation management, its review archive is structured, indexed, and labeled to make it increasingly machine-readable for AI systems. Slocum says the goal is to ensure that the content within reviews can be effectively recognized, interpreted, and surfaced in AI-generated summaries or recommendations.
It's already paying off. Click throughs from AI search have increased 1,490 percent year-on-year, and according to Promptwatch, Trustpilot ranked as the fifth most cited domain globally on ChatGPT in January 2026.
Trustpilot also now offers brands a "practical toolkit" for improving how they show up in AI-driven search, including tools such as real-time reviews, review optimization, AI visibility metrics, and unified reputation dashboards.
Slocum explains: "Ultimately, it helps brands ensure that when AI engines summarize reputations, they're drawing from the most credible, current, and complete picture possible."
Its new AI Search metrics are based on the "3Rs" for building trust in the age of AI: recency, relevance, and ranking. Trustpilot says these are the human signals AI search prioritizes and that keep brands current, contextually aligned, and consistently surfaced. Its new suite of tools applies the 3Rs to enable businesses to keep their public reputation synced with the fast-evolving pace of AI.
Optimizing your customer reviews for AI search
In an agentic economy, pricing rules, delivery promises, escalation paths, service and support, FAQs, financial results, ESG claims and even contact details must be aligned to remove error, ambiguity, and contradiction. Failure to do so equals failure to rank in AI search results.
Reviews are critical to teaching AI assistants that a brand is trustworthy – even more so when connected to the wider customer journey.
To transform individual reviews into more useful trust signals for both consumers and AI assistants Slocum says brands can get a clearer picture of the customer experience by combining reviews with data from website activity, product details, social media, and customer service interactions.
"For example, a home security brand that connects review sentiment with product usage and support data can reveal that customers praise easy installation but flag app connectivity issues: helping AI deliver more credible recommendations while highlighting clear areas for improvement," she explains.
The arrival of agentic commerce changes many established rules in ecommerce, but trust remains central to converting inquiries, driving sales, and securing repeat business in the long term.
Quick links
- The new rules of discoverability
- What you can learn from the best and worst customer service
- How generative AI search is changing the customer journey