Think about the last time you considered a significant purchase. Did you open a browser and start with a Google search, or did you type a question into ChatGPT first? For a growing majority of American shoppers, the answer is increasingly: both.
A new consumer study by SEMrush, conducted in December 2025 across 1,030 U.S. shoppers, has produced some of the most detailed data yet on how AI tools have embedded themselves into everyday buying decisions. The results don’t just confirm that AI is changing how people shop — they reveal where it’s changing things, which platforms are doing the most work, and critically, what actually influences a consumer when a brand shows up in an AI response.
This post unpacks every major finding from that study, contextualizes it against other market research, and translates the implications into specific actions for brands and marketers. If you’re responsible for your brand’s digital visibility — organic search, content, paid media, or brand strategy — this data matters to your day-to-day decisions right now.
The Scale of AI Adoption Is No Longer a Future Story
The most striking headline from the SEMrush study isn’t a prediction. It’s a current reality: 85% of U.S. consumers use AI tools at least once a week, and 48% engage with them daily. A full 25% of respondents said they use AI multiple times per day.
This isn’t a niche group of early adopters or tech-savvy professionals. The survey was deliberately distributed across age brackets — 27.6% aged 18–34, 34.7% aged 35–54, and 37.7% aged 55 and over — and across income levels, from households earning under $25,000 annually to those earning over $200,000. Fifty percent of respondents hold a bachelor’s, master’s, or doctoral degree.
In short, AI tool usage at high frequency is now a mainstream consumer behavior. Not a trend. Not something to monitor for 2027. A present-day fact about how your customers move through the world.
What are these consumers using AI for? A lot. Fifty-eight percent use it to look up information or get explanations. Forty-six percent use it to learn about a topic in depth. Thirty-eight percent use it specifically for product research. Thirty percent use it to compare options side by side before making a decision.
That last number is the one marketers should sit with. Nearly a third of all AI users are going directly to an AI tool when they want to compare competing brands or products. That’s a moment that, for years, brands assumed belonged to comparison sites, review platforms, or Google Shopping. It doesn’t anymore — or rather, it no longer belongs exclusively there.
Which platforms are doing the heavy lifting?
ChatGPT leads with 64% monthly usage among surveyed consumers. Google’s Gemini follows at 49%. Meta AI — accessed through Instagram, Facebook, and WhatsApp — reaches 39% monthly. Google’s AI Mode within search captures 28%, while AI Overviews within traditional Google results accounts for 22%.
Further back in the pack: Grok at 12%, Perplexity at 9%, and Claude at 8%. Those trailing figures likely reflect general consumer populations rather than professional or technical audiences — the SEMrush authors note that Perplexity and Claude may index significantly higher among business and research-focused users.
The practical implication for brands: you don’t need to optimize for every AI surface simultaneously. Prioritizing ChatGPT, Gemini, and Google’s integrated AI features will cover the majority of your audience’s AI touchpoints.
AI Has Entered Every Stage of the Purchase Decision
One of the more important correctives the SEMrush study offers is to the idea that AI is only a “top of funnel” tool. The data doesn’t support that.
Consumers are using AI at every identifiable stage of a purchase decision:
- 51% use it during early discovery — when they’re still figuring out what category of product they want
- 57% use it to narrow down their choices once they have a shortlist
- 53% use it to compare products they’re already actively considering
- 50% use it to make a final purchasing decision
That last point is especially significant. Half of all surveyed consumers are consulting AI at the moment of decision, not just at the moment of awareness. If your brand is absent from AI responses, you’re not just missing awareness — you’re potentially being excluded from the final shortlist.
The study also looked at how consumers frame their queries when using AI for product research, and the results reveal something important about intent: these aren’t the vague, exploratory searches typical of early-stage Google research.
52% of consumers specify constraints upfront — a budget, a compatibility requirement, a specific feature, or a use case. They’re not typing “good running shoes.” They’re asking “what are the best running shoes for wide feet under $150 that work well on gravel trails?” That level of specificity means AI is being used as a precision filter, not a broad discovery tool.
Thirty-three percent go back and forth with AI in a multi-turn conversation, refining their question as they receive answers. Only 43% start with a broad query before narrowing down.
For brands, the practical implication is direct: the clearer and more specific your product descriptions, the more likely an AI model can match your offering to a constrained, high-intent query. Vague positioning gets filtered out.
AI and Google Search Are Not Competing — Consumers Use Both
There’s been considerable debate in the marketing industry about whether AI tools will replace Google. The consumer behavior data suggests this debate has been framed incorrectly.
77% of surveyed consumers use AI tools and search engines together, as part of the same research process. Only 4% said they rely mostly on AI. Search engines remain the more common starting point for many shoppers — 33% said they typically begin their research on Google — with AI close behind at 26%, and 18% actively switching between both throughout the process.
The more accurate picture is that AI and search serve complementary roles. Consumers use AI to understand, synthesize, and filter. They use search to verify, price-check, and transact. The IAB’s independent study, which surveyed 600 U.S. consumers through ethnographic research, reached a similar conclusion: “AI doesn’t shorten the path to purchase — it reshapes it, creating new steps and opportunities.”
This combined-channel behavior has a direct consequence for brand content strategy: you need to be present and credible in both environments. Content that ranks on Google and content that gets cited by AI models have overlapping but not identical requirements. Both reward expertise, clarity, and trustworthiness — but the format, structure, and specificity of how that expertise is expressed may need to differ.
What about traffic to brand websites?
This is where the data pushes back against another common assumption. Many marketers fear that if consumers get answers from AI, they’ll never visit the brand’s website. The numbers tell a different story.
Ninety-four percent of consumers click on links within AI responses at least sometimes. Thirty-eight percent say they do so often or almost always. Only 3% say they never click on links in AI answers.
Beyond clicking: 87% of U.S. consumers say AI summaries help them understand brands faster, and 68% visit brand websites just as often or more than before. Twenty-two percent say they’re actually more likely to visit a brand site after seeing it mentioned in an AI response.
What AI appears to be doing is front-loading the research phase — compressing early-stage information gathering from hours to minutes — while still routing engaged, high-intent consumers to brand properties for verification and purchase. That’s not a threat to brand websites. It’s a change in the nature of the traffic arriving there.
How AI Is Changing the Way Consumers Discover — and Evaluate — Brands
43% of consumers report discovering a new brand through an AI tool. That’s not a small number. Nearly half of the surveyed population has encountered a brand for the first time through a ChatGPT or Gemini response, not a paid ad, not a Google SERP, not a social media post.
And when AI tools do mention a brand or product, consumers don’t just passively note it. Forty percent go to Google to search for more information about that brand. Thirty-six percent use Google to compare it with alternatives. Thirty-four percent ask AI follow-up questions about it. Twenty-eight percent go directly to the brand’s website.
Only 8% ignore the mention entirely. For brands that aren’t currently appearing in AI responses, that ignored 8% represents the entire pipeline they’re missing out on — because the other 92% of consumers who do encounter brand mentions in AI follow up in some concrete way.
47% of consumers say they notice brands mentioned in AI responses often or very often. This is a new form of brand exposure that didn’t exist two years ago. It functions somewhere between a search result impression and a personal recommendation — and it’s tied to a specific purchase intent moment in a way that a social media ad typically isn’t.
Now here’s where the data gets genuinely interesting for brand managers and SEO practitioners: position in an AI response matters far less than content quality.
Only 20% of consumers say a brand stands out because it appears earlier or higher in an AI answer. What actually makes a brand memorable and actionable in an AI response is how it’s described:
- 43% say a clearer or more detailed explanation makes a brand stand out
- 39% note price or value context as a differentiating factor
- 37% respond to descriptions that match their specific needs
- 28% are influenced by direct comparisons between options
This is a meaningful departure from traditional SEO, where position one captures disproportionate clicks regardless of content quality. In AI responses, being mentioned second with a precise, context-matched description may outperform being mentioned first with generic language.
The actionable insight: brands should focus on ensuring that their descriptions across the web — on their own sites, in third-party reviews, in press coverage, and in structured data — are specific, needs-matched, and include relevant context like price range, use case, and differentiating features. This is the information AI models draw on when constructing their responses.
Trust Is Conditional — and the Verification Habit Is Built In
Consumer trust in AI recommendations is real, but it’s calibrated. The study found that 75% of consumers rate their trust in AI recommendations at 3 or 4 out of 5 — solid, conditional trust that informs decisions without eliminating independent judgment. Only 20% said they trust AI completely, and 7% expressed low trust.
That conditional trust translates into a consistent verification behavior. 86% of consumers say they verify AI brand recommendations at least sometimes, and 20% say they always verify before acting. The verification channels consumers turn to follow a logical hierarchy: Google at 68%, brand websites at 48%, review sites at 35%, YouTube at 35%, friends and family at 33%, and social media at 30%.
What this means practically is that a brand’s appearance in an AI response is not the end of the consumer’s evaluation process — it’s an invitation to be scrutinized. The consumer will then check your Google presence, visit your website, look for reviews. If what they find there is inconsistent, outdated, or thin, the AI mention generates friction instead of trust.
For brands, this creates a validation chain that requires all touchpoints to be consistent and credible: your AI-facing content, your Google presence, your website experience, your third-party reviews, and your social presence all need to tell the same coherent story. The consumer is stitching these sources together in real time.
McKinsey’s research on AI search echoes this point: “Winning brands will take action to improve visibility and positive sentiment on both AI summaries and AI platforms. Achieving that requires a new kind of content investment.”
AI Is Already Driving Real Purchases Across Every Category
The most commercially relevant finding in the SEMrush study is this: 50% of consumers have made a purchase after using AI during their research process. This is not theoretical. It has already happened, at scale, across every product category and price point surveyed.
Twenty-two percent have gone further — completing a purchase directly inside an AI tool, without leaving the interface. That native AI commerce figure is still a minority behavior, but its growth trajectory is clear.
Where are consumers buying after AI-assisted research?
- 39% say AI has influenced a retail or consumer goods purchase
- 29% for food and grocery purchases
- 29% for wellness and health products
- 27% for electronics
- 21% for travel
- 16% for education products and services
- 15% for home services
- 13% for financial services
The distribution is worth studying. High-consideration, high-cost categories like financial services and home services still show double-digit AI influence — meaning even in categories where purchase decisions are complex and trust requirements are high, consumers are using AI as part of their research. No category is insulated from this.
The study also examined purchase value: 37% of consumers rely on AI most for mid-range purchases like electronics and subscription services. Twenty-eight percent use it for high-cost or high-risk decisions. Thirty-six percent say they apply AI equally across all purchase types.
The implication is that AI shopping behavior is not constrained to low-stakes or impulse purchases. Consumers are using AI to inform expensive, considered decisions just as readily as everyday buys.
What Brands Must Do: A Strategic Framework for AI Visibility
Based on the data, the strategic priorities for brands aren’t complicated — but they do require a shift in where effort and budget are directed.
1. Treat AI Visibility as Its Own Channel
For years, brands have tracked their performance across search (organic and paid), social, email, and direct. AI is now a distinct discovery channel with its own mechanics, and it needs its own measurement framework. If you don’t know how your brand appears in ChatGPT, Gemini, or Google’s AI Overviews, you’re operating blind in a channel where 43% of consumers are already discovering new brands.
2. Optimize for Description Quality, Not Just Keyword Density
The shift from position-dependent SEO to description-quality optimization is one of the most practically meaningful changes emerging from this data. Your brand needs to be described across the web — on your own site and in third-party sources — with the kind of specific, contextual, needs-matching language that AI models use when constructing responses to precise consumer queries.
This means auditing your product pages, your About section, your press coverage, and your review profiles for specificity. Generic brand copy will not travel well into AI responses. Precise, feature-forward, use-case-specific descriptions will.
3. Secure the Verification Chain
Because 86% of consumers verify AI recommendations before buying, every channel they’ll check needs to hold up. Google My Business profiles need to be current. Website copy needs to load fast and answer core questions clearly. Review platforms — Google Reviews, Trustpilot, G2, industry-specific platforms — need active management. YouTube presence, for those categories where video plays a role in evaluation, needs to be credible and informative.
Being mentioned favorably by AI and then sending consumers to a thin or outdated website is worse than not being mentioned at all, because it erodes exactly the conditional trust the AI mention generated.
4. Develop Content That Serves Both Search and AI
The good news from the 77% co-usage figure is that brands don’t need to choose between ranking on Google and appearing in AI responses. The content practices that support both overlap significantly: well-structured, accurate, specific, authoritative content with clear topical depth. The key differences are in format — AI models respond well to structured data, concise factual statements, comparison language, and explicit value/price context. Google still rewards traditional signals like backlinks, page authority, and user behavior metrics.
A dual-channel content strategy isn’t twice the work. It’s about writing content with greater specificity and structure, then ensuring it’s discoverable across both surfaces.
5. Consider Generative Engine Optimization (GEO)
GEO — the emerging practice of optimizing content specifically for how generative AI models retrieve and cite information — has quickly moved from academic concept to practical discipline. Key GEO principles align with the study data: use cited statistics and factual specificity (AI models favor citable facts), use structured headers and clear entity names, ensure your brand is mentioned in authoritative third-party sources alongside relevant descriptors, and use schema markup and structured data to make key product facts machine-readable.
The Future: Where AI-Assisted Shopping Is Going
The behavioral trajectory is not ambiguous. 69% of surveyed consumers expect AI to play a bigger or much bigger role in how they shop in the future. Only 3% expect AI’s role to shrink.
The downstream effects are equally clear. 46% of consumers anticipate relying less on traditional search engines as AI improves. Forty-two percent expect to rely less on social media for shopping discovery. Review sites (34%), influencer recommendations (33%), advertising (30%), and blogs (28%) are also expected to lose relative ground as AI tools become more capable.
This doesn’t mean any of those channels disappear. It means their relative weight in consumer decision-making shifts, and the brands that continue investing in them to the exclusion of AI visibility will experience declining returns.
OpenAI’s launch of Shopping Research in ChatGPT — a feature that lets users explore, compare, and discover products through conversational interfaces — illustrates where this is heading. Google’s AI Mode within search is another signal. The infrastructure for AI-native commerce is being built right now, and the brands establishing their presence in AI responses today are building advantages that will compound over time as these features mature.
Frequently Asked Questions
What is the AI tools and modern buyer journey study by SEMrush?
The SEMrush study on AI tools and the modern buyer journey is a survey-based consumer research report published in early 2026, based on interviews with 1,030 U.S. shoppers conducted in December 2025. The study examined how often consumers use AI tools, which platforms they use most, how AI fits into different stages of a purchase decision, how much they trust AI recommendations, and whether AI usage has translated into actual purchases. Respondents were distributed across age groups (18–34, 35–54, and 55+), income brackets from under $25,000 to over $200,000 annually, and education levels. The study is one of the most demographically comprehensive consumer AI shopping surveys published to date.
Which AI tools do consumers use most for shopping and product research?
According to the SEMrush study, ChatGPT leads AI tool usage with 64% of consumers using it on a monthly basis. Google’s Gemini follows at 49% monthly usage. Meta AI — accessible across Instagram, Facebook, and WhatsApp — reaches 39% of consumers monthly. Google’s AI Mode within traditional search captures 28%, while Google AI Overviews within standard search results accounts for 22%. Grok, Perplexity, and Claude trail significantly at 12%, 9%, and 8% respectively among general consumer populations, though these platforms likely see higher usage among professional and technical audiences. For most brands, optimizing for ChatGPT, Gemini, and Google’s integrated AI features will cover the majority of consumer AI touchpoints.
How does AI influence the buyer journey at different stages?
The study found that AI is being used at every stage of the purchase process, not just at the awareness stage. Fifty-one percent of consumers use AI during early discovery. Fifty-seven percent use it to narrow down a shortlist of options. Fifty-three percent use it when actively comparing products they’re already considering. Fifty percent use AI at the final decision stage. This distribution means that brands absent from AI responses aren’t just missing awareness — they may be excluded from the active shortlist phase and even from the final purchase decision.
Do consumers trust AI recommendations enough to make purchases based on them?
Consumer trust in AI is real but conditional. Seventy-five percent of surveyed consumers rate their trust in AI recommendations at 3 or 4 out of 5 — indicating solid but not unconditional trust. Only 20% trust AI completely, and 7% express low trust. Despite this conditional trust, 50% of consumers have already made a purchase after using AI during their research, and 22% have completed a purchase directly within an AI tool. The more common pattern is for consumers to use AI to narrow their options, then verify through Google (68%), brand websites (48%), or review platforms (35%) before completing a purchase.
Has AI replaced Google Search for shopping research?
The data clearly shows that AI has not replaced Google Search. Seventy-seven percent of consumers use AI tools and search engines together as part of the same research process. Only 4% rely mostly on AI. Google remains the more common starting point for many shoppers at 33%, with AI used as a starting point by 26%, and 18% actively switching between both. The more accurate description is that AI and search serve complementary roles: AI is used for synthesis, comparison, and filtering, while search is used for verification, pricing, and transaction. For brands, this means optimizing for both surfaces remains important.
What role does brand position play in AI responses?
Position within an AI response matters far less than the quality of how a brand is described. Only 20% of consumers say a brand stands out because it appears earlier or higher in an AI-generated answer. What actually differentiates brands in AI responses is description quality: 43% of consumers say a clearer or more detailed explanation makes a brand stand out, 39% notice price or value context, 37% respond to descriptions that match their specific need, and 28% are influenced by direct comparisons. This is a meaningful departure from traditional SEO, where position-one dominance drives disproportionate clicks regardless of copy quality.
How do consumers verify AI recommendations before buying?
Eighty-six percent of consumers verify AI brand recommendations at least sometimes, and 20% always verify before purchasing. Google is the primary verification channel, used by 68% of consumers for this purpose. Brand websites are checked by 48%. Review sites and YouTube are each consulted by 35% of consumers. Friends and family are consulted by 33%, and social media by 30%. Because this verification behavior is almost universal, every channel a consumer might check needs to present a credible, consistent brand story that reinforces rather than undermines the AI mention.
In which product categories has AI most influenced consumer purchases?
The study found that retail and consumer goods lead AI purchase influence at 39%, followed by food and grocery (29%), wellness and health (29%), and electronics (27%). Higher-consideration categories like travel (21%), education (16%), home services (15%), and financial services (13%) also show meaningful AI influence, suggesting that the effect is not limited to low-risk or impulse purchases. Thirty-seven percent of consumers rely on AI most for mid-range purchases like electronics and subscriptions, while 28% use it for high-cost or high-risk decisions, and 36% apply it equally across all purchase types.
What percentage of consumers have discovered new brands through AI?
Forty-three percent of consumers have discovered a brand they hadn’t previously known through an AI tool. Forty-seven percent say they notice brands mentioned in AI responses often or very often. When a brand is mentioned in an AI response, 40% of consumers search Google for more information about it, 36% use Google to compare it with alternatives, 34% ask AI follow-up questions, and 28% go directly to the brand’s website. Only 8% ignore a brand mention entirely, meaning 92% of consumers who encounter a brand in an AI response take some form of follow-up action.
What is Generative Engine Optimization (GEO) and why does it matter?
Generative Engine Optimization (GEO) is the practice of structuring content and brand information so that AI generative models are more likely to retrieve, accurately represent, and cite a brand in their responses. Key GEO practices include: using factual, specific, citable language with concrete data points; structuring content with clear headers and entity names; ensuring the brand is mentioned in authoritative third-party publications with relevant descriptors; using schema markup and structured data to make product details machine-readable; and maintaining consistent brand descriptions across owned and earned media. GEO differs from traditional SEO in that it optimizes for how AI models synthesize and present information, not just for how search engines rank individual URLs.
How can brands appear in Google AI Overviews and ChatGPT responses?
There is no guaranteed method for appearing in any AI response, but the factors most consistently associated with AI citations are: topical authority demonstrated through depth and breadth of accurate content on a subject; consistent brand mentions in credible third-party sources such as news coverage, reviews, and industry publications; use of structured data and schema markup; technically sound websites with fast load times and clear information architecture; and content that directly answers the specific types of questions consumers ask AI tools, including comparative queries, constraint-based queries (“best X for Y budget”), and use-case queries. Maintaining an accurate and well-reviewed Google Business Profile also influences Google’s integrated AI features.
What does the data say about AI’s future role in consumer shopping?
Sixty-nine percent of consumers expect AI to play a bigger or much bigger role in how they shop in the future, with only 3% expecting it to decrease. Forty-six percent anticipate relying less on traditional search engines as AI improves, and 42% expect to rely less on social media for shopping discovery. Review sites (34%), influencer content (33%), advertising (30%), and blogs (28%) are also expected to lose relative ground. These projections suggest that AI’s current influence on shopping — already significant — is in an early stage of a longer adoption curve.
How does AI affect website traffic for brands?
Despite concerns that AI responses might reduce visits to brand websites, the data suggests the effect is more nuanced. Sixty-eight percent of consumers visit brand websites just as often or more than before since AI tools became part of their research process. Twenty-two percent say they are more likely to visit a brand website after an AI interaction. Only 11% say they’re much less likely to visit a website after using AI. Ninety-four percent click on links within AI responses at least sometimes, with 38% doing so often or almost always. The effect appears to be that AI compresses early research while routing higher-intent consumers to websites, meaning the traffic arriving at brand sites from AI-influenced journeys may be more purchase-ready than average search traffic.
How should small and mid-sized brands approach AI visibility without large budgets?
The cost of AI visibility optimization is not primarily financial — it’s editorial. The brands most likely to appear favorably in AI responses are those whose content, product descriptions, and brand narratives are specific, accurate, and widely distributed across credible sources. Practical steps for smaller brands include: ensuring Google Business Profile is complete and regularly updated; actively managing reviews on Google, Yelp, and category-specific platforms; publishing useful, specific content that answers the exact questions consumers bring to AI tools; securing coverage in industry publications, trade press, and relevant directories; and structuring product descriptions with explicit feature, price, and use-case information rather than marketing-speak. These are largely editorial investments rather than media budget investments.
What is the difference between AI Overviews and AI Mode in Google?
Google AI Overviews are AI-generated summary panels that appear at the top of traditional Google search results pages for certain queries, typically informational searches. They draw from web sources and provide a synthesized answer with citations. Google’s AI Mode is a more immersive, dedicated interface within Google Search that enables multi-turn conversational queries, deeper synthesis, and more complex research tasks — functioning more like a standalone AI assistant while remaining within the Google ecosystem. Twenty-two percent of surveyed consumers use AI Overviews monthly, while 28% use Google’s AI Mode. Both surfaces are relevant to brand visibility, but they serve different user intents: AI Overviews intercept informational searches within traditional browsing, while AI Mode hosts more deliberate, extended research sessions.
If there’s one thing this data makes clear, it’s that the consumer decision-making process has become genuinely multi-channel in a new sense — not multi-channel in the old sense of “website plus social plus email,” but in a sense where AI tools, search engines, brand properties, and third-party platforms are all being consulted within a single purchase journey, often within minutes of each other. Brands that build coherence across all of these surfaces — that show up consistently and credibly whether a consumer asks ChatGPT, checks Google, reads a review, or lands on their website — are the ones best positioned to capture purchase intent wherever it surfaces. The question is no longer whether AI is part of your customer’s journey. The question is whether you’ve made it easy for AI to tell your brand’s story accurately.
About ALM Corp
ALM Corp is a full-service digital marketing agency that has generated over $7 billion in client sales and launched more than 5,700 websites across industries. As AI tools like ChatGPT, Gemini, and Google AI Overviews become central to how consumers discover and evaluate brands, ALM Corp’s integrated approach — spanning SEO, content strategy, Generative Engine Optimization (GEO), paid media, data analytics, and web development — is designed to ensure client brands are visible, credible, and well-described across every surface where purchase decisions are being made. Whether you need to optimize your existing content for AI retrieval, build the verification chain consumers rely on before buying, or develop a full-funnel strategy for the AI-augmented buyer journey, ALM Corp brings the data, the strategy, and the execution capability to make it happen. To learn how ALM Corp can strengthen your brand’s performance across AI and traditional search, visit almcorp.com.
