Comparison shopping was once an “all too human” exercise. Shoppers searched, contrasted specs, scanned reviews, and weighed tradeoffs before settling on the right product.
These days? A lot of that work is being handed off to AI tools, with more and more likely to follow in the years ahead.
In fact, retail analytics show that generative AI (GenAI)-driven traffic to ecommerce sites continues to accelerate. During peak shopping months like November and December 2025, referrals from GenAI platforms increased by 693% year over year, according to Adobe — a clear signal that AI is already influencing how shoppers discover and evaluate products. That same research found GenAI tools influenced more than 20% of all online retail sales globally during that same holiday season.
As you can imagine, that shift has some serious implications for brands. In particular, AI systems act as decision filters that, for better or worse, brands don’t fully control — functional gatekeepers that decide which products get compared, explained, or excluded before a shopper ever sees the full field of options.
As comparison shopping becomes more automated and proactive, how will shoppers make decisions — and how can brands ensure their products show up?
Salsify’s “2026 Consumer Research” report shows that 19% of shoppers now discover new products through AI search tools like ChatGPT and Gemini. Among U.S. shoppers, that figure rises to one in four.
Perhaps more surprisingly, 22% of shoppers use AI search tools specifically to research products, surpassing once stalwart channels like product review sites (19%) and online forums (14%).
That means that, rather than starting with a retailer search bar or a review site, many shoppers are turning to AI tools to generate an initial set of options before they ever browse a category page. And with AI shopping guides from Amazon, OpenAI, and Algolia, comparison is increasingly happening earlier in the journey, with key differences summarized and options narrowed before shoppers ever browse a category page.
Comparison still happens — it has to. But it increasingly starts with smaller, pre-filtered sets of options that are defined by automated systems, rather than human exploration.
As comparison becomes increasingly automated, visibility depends less on persuasion and more on interpretation. AI-powered comparison systems don’t have marketing or editorial teams making judgment calls — they rely on structured signals and consistent information to determine which products belong in a shortlist, and which don’t.
In a world where AI-assisted discovery is increasingly changing the journey, that distinction matters. In fact, one study by Rep AI found that these kinds of searches can accelerate purchase decisions by 47%, and raise conversion up to four times as high when compared to non-assisted browsing.
That underscores a critical point: Being surfaced in an AI-generated comparison isn’t just about awareness — it can make or break the outcome, too.
When shoppers rely on AI recommendations to make a purchase, Salsify’s latest research suggests they’re looking for very specific signals: detailed product descriptions, clear explanations, social proof, and direct comparisons with competing products. Shoppers trust AI product recommendations enough to buy if:
Image Source: Salsify 2026 Consumer Research
Luckily, in large part, these are the same inputs AI systems use to evaluate product relevance for shoppers.
That puts pressure on brands to ensure their product information is both complete and consistent in every channel where it may appear. Products are easier for automated systems to evaluate when:
When product data is fragmented or contradictory, AI systems struggle to confidently rank or recommend it.
As these tools increasingly become decision filters for consumers, the risk isn’t being ranked lower — it’s being excluded altogether. It’s just another reason why omnichannel consistency remains so critical on the digital shelf.
AI-powered shopping guides have marked an important shift. They took a traditionally manual and fragmented process and made it faster, more accessible, and easier to navigate. But they’re not the end state of comparison shopping.
What’s emerging next is a broader evolution in how comparison works. It’s becoming more visual and input-rich, allowing shoppers to start from images, voice, or loosely defined needs.
It’s becoming more conversational and adaptive, unfolding through interaction rather than a single, static list. And it’s becoming more closely connected to action — removing friction as shoppers move from evaluation to decision without restarting the process at each step.
Industry analysts suggest the next phase will be less about new destinations and more about how comparison is woven into search, interaction, and decision-making. Platforms and analysts are already investing heavily in multimodal and conversational interfaces, suggesting the next shift may move away from keyword-only searches.
Shoppers are increasingly able to start with images, voice, or loosely defined prompts — allowing systems to infer intent and surface relevant options. That means a customer can search for a product without even knowing what it’s called, or how to describe it to a traditional search engine.
There’s also talk of agentic commerce, where assistants manage every part of the customer journey, from awareness to consideration — leaving only the final decision to the customer. The latest Salsify research shows that up to 21% of shoppers say they’re interested in AI agents and would use them regularly.
Taken together, these signals suggest that what comes after AI-powered shopping guides isn’t a single new tool, but a broader shift: Comparison shopping becomes more interactive, more embedded, and more continuous.
As machines play a larger role in mediating discovery and comparison, it’s more important than ever for product information to be machine-friendly, consistent across surfaces, and clear enough for AI systems to accurately interpret purpose and context.
In a comparison landscape shaped as much by automated systems as by human judgment, visibility isn’t earned by being louder or more promotional; it’s earned by being understood.