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ResearchJanuary 15, 2026·12 min read

2026 AI Shopping Report: How Consumers Are Buying With AI

We surveyed 4,200 online shoppers to understand exactly how AI engines like ChatGPT, Perplexity, and Gemini are influencing what they buy — and from whom.

Key finding:63% of shoppers now use an AI assistant before completing a purchase — up from just 18% in 2024. If your products aren't appearing in AI answers, you're invisible to more than half your potential customers.

Executive Summary

AI-assisted shopping has crossed the majority threshold. In early 2026, MetafyAI surveyed 4,200 US and UK consumers who purchased a product online in the previous 30 days. The results confirm what many brands have been sensing: AI search engines are rapidly replacing the traditional "Google then Amazon" funnel.

63%
shoppers use AI before buying
41%
first-touch via AI, not search
2.8×
higher conversion from AI referral
$4,200
avg. annual AI-influenced spend

The AI Engines Driving Purchases

ChatGPT leads as the primary AI shopping assistant, used by 52% of AI-assisted shoppers. Perplexity comes second at 28%, particularly strong in electronics and home appliances. Google's AI Overview (formerly SGE) accounts for 19%, while Gemini Advanced is growing fastest among Gen Z.

  • ChatGPT: 52% share — strongest in apparel, beauty, and general merchandise
  • Perplexity: 28% share — index-heavy categories (tech, home, outdoor)
  • Google AI Overview: 19% share — product discovery in mid-funnel
  • Gemini Advanced: 14% and growing — fashion, lifestyle, Gen Z demographics
  • Claude: 8% share — B2B and high-consideration purchases

How AI Selects Products to Recommend

The most striking finding: AI engines cite structured product data 3.4× more often than unstructured page text. Products with clean schema markup, clear feature attributes, and consistent catalog data were 78% more likely to be named by name in an AI response.

Implication for brands: Traditional SEO (backlinks, keyword density) has almost no bearing on AI citation. What matters is catalog completeness, structured data quality, and consistent product representation across channels.

What makes a product "AI-recommendable"?

  • Complete product schema with all relevant attributes (material, size, compatibility, etc.)
  • Rich, factual descriptions — not marketing copy, but specific claims
  • Consistent brand and product name across all channels (website, Amazon, Google Shopping)
  • Positive sentiment in third-party review content visible to AI crawlers
  • Clear differentiators vs. competitors stated in natural language

The Purchase Funnel Is Compressing

With traditional search, the average path from awareness to purchase was 4.7 touchpoints over 3.2 days. For AI-assisted purchases, our data shows 1.9 touchpoints over 0.8 days. AI answers product questions, compares alternatives, and builds enough confidence for a purchase decision — all in a single conversation.

4.7→1.9
touchpoints: traditional vs AI
3.2→0.8
days to purchase
78%
of AI-referred buyers converted
34%
higher AOV from AI-referred customers

Category Breakdown

Electronics & Tech

The highest AI adoption category at 71%. Shoppers use AI to compare specs, assess compatibility, and understand technical trade-offs. Perplexity dominates here with 44% share thanks to its citation-heavy format that shoppers trust for technical decisions.

Beauty & Personal Care

Growing fastest — AI adoption up 112% YoY. ChatGPT dominates with ingredient analysis, skin type matching, and "what's comparable to [luxury brand] but affordable" queries. Brands with well-structured ingredient and benefit data are winning disproportionately.

Home & Furniture

High-consideration, long funnel category where AI provides the most value. Shoppers ask AI to help visualize, compare dimensions, and check compatibility with existing furniture. Products with rich dimension data, material information, and clear assembly details get cited most.

Apparel & Fashion

Emerging strongly — 49% AI adoption. Queries are style-based ("what jeans work for an apple body shape") and occasion-based ("outfit ideas for a summer wedding under $200"). Semantic product tagging is critical for this category.

The Brands Winning in AI Search

Our analysis of 2,400 product categories found that the brands appearing most often in AI recommendations share three characteristics: highly structured product data, consistent cross-channel representation, and active monitoring of their AI citation rate.

MetafyAI customers on average: See a 3.1× increase in AI citation rate within 90 days of implementing structured catalog optimization, with a 47% improvement in AI-referred traffic over 6 months.

Recommendations for Brands

  • Audit your AI visibility: run your top 20 product queries in ChatGPT, Perplexity, and Gemini today
  • Complete your product schema: every attribute gap is a citation opportunity you are missing
  • Write factual descriptions: replace marketing language with specific, verifiable claims
  • Standardize product names and brand representation across all sales channels
  • Monitor AI citation trends weekly — the landscape is shifting faster than traditional SEO
  • Invest in review generation: sentiment in third-party reviews directly influences AI recommendations

Methodology

MetafyAI surveyed 4,200 US and UK online shoppers aged 18–65 who made at least one online purchase in November or December 2025. Surveys were conducted online in January 2026. Data was weighted to be representative by age, gender, region, and household income. AI citation analysis was conducted on a separate dataset of 2,400 product categories using proprietary AI monitoring infrastructure.