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Unruly AI Review Summaries Are Rewriting Brand Stories, but Proactive CMOs Still Can Take Back Control
CMOs must treat customer reviews as strategic data assets to prevent AI summaries from flattening their brand narrative and losing control to algorithms.
Key Points
AI is increasingly summarizing customer reviews for millions of shoppers, stripping context and creating a brand control problem for marketers.
The issue is compounded by a rise in fake AI-generated reviews, which pollute the data sets used by summarization tools and erode consumer trust.
To regain control, leading retailers like J.Crew and Amazon are deploying their own on-site AI summarization tools and investing in higher-quality review collection.
There's a unique brand of AI-creep happening right now that most CMOs haven't fully reckoned with. AI systems are reading customer reviews, summarizing them, and serving those summaries to millions of shoppers, and brands have little control over how products are being described. ChatGPT users make more than 84 million shopping-related queries per week. When a shopper asks "what's the best running shoe for flat feet?" or "is this moisturizer worth the price?", the AI doesn't visit your product page. It reads aggregated reviews, synthesizes the sentiment, and delivers a verdict.
The brand control problem: The core issue is decontextualization. When an AI engine summarizes hundreds of reviews into a paragraph, it strips out the nuance that makes individual reviews valuable. A review that says "the sizing runs small but once you get the right size, the quality is incredible" gets flattened into a mixed sentiment score. The qualification disappears. The negative signal gets amplified.
Polluting the data: Beyond a lack of nuance, there's the emerging problem of AI-generated reviews polluting the data set. Roughly 3% of front-page reviews on major e-commerce platforms are AI-generated, rising to 5% in categories like beauty and baby products. These synthetic reviews degrade the quality of the summaries that other AI systems generate from them in a feedback loop that erodes trust for everyone.
J.Crew saw this coming. Before rolling out AI review summaries on their own site, they invested months in soliciting more reviews from past purchasers, deliberately building the data set before the AI layer went on top. As their SVP of Digital Experience Ruchika Julapalli put it, "Had we not invested in that review volume and some of those capabilities, we wouldn't have actually had good-quality review summaries." But most brands haven't done the work. Beyond the uncontrollable UGC management problem, there's a brand-narrative issue that can be remediated with a firm CMO-level response.
Reviews as a data asset, not a marketing afterthought: Brands that will control their AI-mediated narrative are the ones treating reviews with the same strategic seriousness as their media spend. That means investing in review volume (more reviews = better AI summaries), review depth such as prompting customers for specific feedback about sizing, ingredients, and use cases, and review freshness where recent reviews signal active products to AI systems.
The proprietary summarization layer: J.Crew, Amazon, Walmart, and Dick's Sporting Goods have all deployed AI review summaries on their own sites. When brands control the summarization, they also control the framing. When they leave it to LLMs, they outsource product narrative to an algorithm optimizing for user satisfaction as opposed to brand story.
When a customer receives a personalized SMS with a product recommendation based on their purchase history, no AI is summarizing reviews in the middle. The message comes directly from your brand, tailored to their specific context. As AI increasingly mediates product discovery and evaluation, the brands with direct messaging relationships have a structural advantage: they can tell their own story, in their own words, without an AI gatekeeper.
Solicit reviews through your owned channels. Post-purchase SMS and email flows that ask specific questions ("How did the sizing work for you?" "What's your favorite feature?") generate the kind of detailed, specific reviews that AI summarizes well. Generic "leave a review" prompts produce generic reviews that AI summarizes poorly. The quality of your review corpus is directly proportional to the quality of your review solicitation strategy.
The brands that treated SEO as a strategic function 15 years ago gained compounding advantages over the brands that treated it as a technical task. We're at the same inflection point with AI-mediated product discovery. Your reviews are now a primary input to the AI systems that shape how millions of shoppers perceive your products. The CMOs who recognize this and invest accordingly in review strategy, owned-channel communication, and first-party data will control their brand narrative in the age of AI. Everyone else will be at the mercy of someone else's summary.
