Online reviews have long been one of the most powerful drivers of purchase decisions and the rise of AI has made them even more important, argues Social Soup founder Sharyn Smith. Since the boom of AI agents over the past couple of years, reviews now form a core part of a brand’s digital presence, directly influencing how AI will rank, recommend and, ultimately, understand a product.
Social Soup’s research shows that reviews sit almost at the top of the trust hierarchy when people are deciding what to buy, second only to personal recommendations from friends and family. Most people look at reviews when they are buying something, and most consult them at multiple points in the decision-making journey – from early research through to the moment they’re standing in-store or hovering over the buy button online.
That behaviour has intensified as trust in online environments has declined. In 2026, consumers are seeking more and more sources of information to help them make decisions. They don’t rely on a single opinion or platform. They cross-check. They compare. They read the five-star reviews. They scroll straight to the one-star ones. They search Google, TikTok, Instagram and other platforms for real experiences. They look for context, recency and relevance before they commit.
Reviews now intersect social search, ecommerce and AI. They influence what surfaces in TikTok results. They influence what appears in Google’s AI overviews. And they influence what an AI agent recommends to people. Many companies still treat reviews as something that “happens” rather than something that is necessary to get noticed in AI-generated results.
Too often, companies collect reviews passively, respond inconsistently, and rarely connect them to broader influencer or PR strategies. But AI doesn’t see these channels as separate. It reads everything as one ecosystem. When your reviews, creator content and brand messaging reinforce the same story, trust compounds and patterns form, which are the answers that show up when searching about a category or brand.
AI platforms like ChatGPT, Gemini and Perplexity are trained on reviews as well as forums, social posts, creator content and commentary. When someone asks an AI assistant “what’s the best product is for sensitive skin”, or “which under $30 wine is best”, the answer is shaped by what the AI agents have learned from the volume, consistency and sentiment of reviews as well as other online profile data across social media, forums, owned websites and so on.
Showing up in AI agent recommendations doesn’t come from perfectly optimised metadata or clever keyword stuffing. It comes from what people are genuinely saying about your company or your brand, over time, across multiple surfaces. Every review – good, bad or neutral – becomes a data point.
Our research consistently shows that people don’t want overly glowing, one-dimensional praise. They trust reviews that are honest and balanced, that include pros and cons, and that are recent, descriptive and relatable. Slightly imperfect reviews often outperform perfect ones when it comes to trust, usefulness and encouraging people to buy. It’s about consistency over just being loud online.
There’s also a missed opportunity in how reviews are generated. Research shows that while most people read reviews, far fewer people actually take the time to write them. It’s not because they don’t want to help others, but because the process is often time-consuming or unclear. When brands make it easy and worthwhile to leave a review, participation increases. When brands have a wholistic strategy to generate reviews across all the places that influence people and AI they will get a winning advantage over their competitors when their customers are making buying decisions.
Reviews are not just conversion tools, but long-term signals that shape how both people and machines perceive brands. When reviews are embedded into an ecosystem that includes creators who are good at contextualising products, they become far more powerful than other elements of a brand’s online profile. The most impactful programs we run are from everyday people leaving authentic reviews across influential sites. These are run alongside large quantities of micro influencers who generate high quality reviews about products at scale, with the right phrases and messages about the brand.
If you want to be recommended by AI agents, you need to be investing in review ecosystems that includes consistent, authentic feedback across multiple channels and touchpoints. With reviews now at the intersection if social search, ecommerce and AI, they may well be your most influential channel in 2027.
Sharyn Smith is the founder and CEO of Social Soup.
