AI is rapidly reshaping online commerce, and it’s happening in plain sight. Referral traffic to retailers on Black Friday from AI chatbots and search engines jumped 800% over the same period last year, according to Adobe, which suggests a swelling number of shoppers now turn to AI first when they’re thinking about buying something. That leaves a thorny question hanging: Where does that leave product-review sites, which used to sit at the center of those decisions?
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Key Takeaways
- Adobe: retailer referrals from AI chatbots/search jumped 800% over Black Friday.
- Product-review sites are losing their place at the center of buying decisions.
- Survival: direct audiences, AI-citable structured data, non-Google revenue.
If any category of media is visibly spooked by AI, it’s publishers who specialize in product recommendations, whose entire model grew dependent on search traffic over the last decade and a half. The content is informational, built to be discovered and skimmed. Most articles are designed to answer a question: “What’s the best robot vacuum?” “Who has the best deals on sofas?” “How do I set up my soundbar?” AI does an excellent job of answering those questions directly, packaging the result so neatly that readers never have to click through to a publisher’s site.
When you actually want to buy something, though, a simple answer is rarely enough. Completing your purchase usually means going to a retailer (though buying directly from a chat window is now possible—more on that in a minute). But it also means feeling confident about what you’re buying. The big question is: Do review sites still have a part to play in that, or has AI quietly taken over the role of “trusted guide”?
From search kingmakers to supporting cast
If they do, most media companies seem to acknowledge it’s a significantly smaller one. When Business Insider announced its strategy shift earlier this year amid layoffs, it said it would move away from evergreen content and service journalism. In the past year, Future plc folded Laptop magazine, and Gannett did the same for Reviewed.com. And Ziff-Davis—which operates PCMag, Everyday Health, and several other sites focused on service journalism—sued OpenAI earlier this year for ingesting Ziff content and summarizing it for OpenAI users.
The decline of the review site is somewhat incongruous with a statistical reality: 99% of buyers look to online reviews for guidance, and reviews influence over 93% of purchase decisions, according to CapitalOne Shopping Research. That doesn’t mean buyers are always seeking out professionally written articles (there are plenty of user reviews out there), but the point is readers want credible, reliable information to guide their purchases, and credibility is still a scarce resource online. Well-known review sites (e.g. The Wirecutter) appearing in a summary can be a signal of such credibility, even if the reader never visits the original page.
And it does appear that AI summaries favor journalistic content over other types. A recent Muck Rack report that looked at over 1 million AI responses found that the most commonly cited source of information was journalism, at 24.7%—which is both comforting and a little ironic, given the traffic implications.
It’s nice to be needed, but does that lead to buyers actually making purchases through the media site—a necessary step for the site to receive an affiliate commission and the primary way these sites make money? Again, the buyer needs to click somewhere to buy their product, and from the AI layer they have three choices: 1) a retailer, 2) a third-party site (which includes review sites), and 3) the chat window itself. Only one of those reliably keeps the publisher in the loop.
Why the ‘extra detail’ becomes the product
Obviously, it’s in the interest of review sites to steer people to No. 2 as much as they can. When Google search was the only game in town, that meant ranking high when people search for “best pool-cleaning robots” (or whatever) and hope you were the site that ended up guiding them to the retailer. With AI, the game is similar, but the numbers are different: Fewer people will come to your site, but data points to them being more intentional and engaged. They’re not opening multiple review sites and selecting their favorite—AI is doing that for them. ChatGPT even has a mode specifically for shopping, which makes the old funnel feel quaint.
To improve the chance of a reader choosing to go to your content over a retailer, what appears in an AI summary needs to convey unique and valuable content that they can’t get from just a summary. That means being thoughtful about “snippets”—the bits of the article that signal to search engines what’s important. Test data, side-by-side comparisons, and proprietary scoring can all suggest nuance that someone might need to click through to fully appreciate. Taking things a step further, publishers can create structured answer cards meant to be fully captured in AI search, with a simple, concise claim plus a “view full test details” link—a kind of compromise between visibility and depth.
If affiliate breaks, what replaces it?
Regardless, even if a review site does everything right with SEO, schema, snippets and all the other search tricks, a large portion of readers will either go directly to retailers, or buy the item directly from chat—OpenAI and Perplexity are both offering “Buy Now” widgets. However, whatever recommendations the AI makes still need to be based on something, and review sites are certainly part of that mix. That introduces the possibility of a different business arrangement—one where the value is upstream, not at the checkout link.
The AI companies so far seem totally uninterested in affiliate commissions from their buying widgets, but licensing and partnerships could be an alternative. You could even imagine branded partnerships, where the widget explicitly labels the buying recommendations are powered by specific publications. That would lend them more credibility, leading to more purchases—and bigger deals. With AI-ready corpora like Time’s AI Agent, licensing the content could be a plug-and-play experience, potentially offered across several AI engines, turning “source material” into a sellable asset.
New rules, same job
Gone are the days when a publisher could simply produce evergreen content that ranks in SEO, attach some affiliate links, and watch the money roll in. But the game isn’t over, it’s just changed. Avoiding or blocking AI isn’t the answer, but simply getting noticed and summarized isn’t enough. The sites that survive the transition to an AI-mediated world must become indispensable for the part of the journey AI is least suited to own—providing information that’s comprehensive, vetted, and above all, human.
Frequently Asked Questions
AI is enabling review sites to produce content at dramatically greater scale through AI-assisted or fully AI-generated reviews, automated comparison tables, and dynamically updated content. This is raising questions about authenticity, testing standards, and the real value of human versus AI-generated evaluations in journalism and media.
AI-generated product reviews vary widely. When grounded in actual testing data, user reviews, or manufacturer specifications, AI can produce useful summaries. But AI reviews generated without physical product testing typically lack nuanced first-hand insights, and they can perpetuate inaccurate product information at scale without a human editor to catch errors.
Google has updated its helpful content guidelines specifically to reward first-hand expertise and penalize thin AI-generated content lacking genuine product experience. Sites publishing AI reviews without real testing are increasingly seeing ranking penalties, while human-tested reviews with distinctive first-person observations and methodology disclosure tend to rank better.
Journalistic review outlets that invest in genuine product testing and expert opinion are better positioned than content farms using AI shortcuts. The competitive challenge is volume: AI-powered sites can publish reviews of thousands of products while traditional outlets test dozens. The competitive advantage for journalism shifts to depth, trust, and verified expertise.
Signs of genuine human testing include: specific product observations that couldn’t come from a spec sheet, comparisons to competitors tested simultaneously, photos or videos of the actual product, clear methodology disclosure, and named reviewers with established track records. Generic spec-heavy content with no personal opinion or suspiciously broad product coverage commonly signals AI generation.
