Nearly 60% of consumers have used AI to shop, and 58% have turned to generative AI instead of traditional search engines for product recommendations. For marketers, this shift compresses the traditional purchase funnel into a single AI-mediated conversation - and makes current measurement models obsolete.
Research from Capital One Shopping, CI&T, Adobe, and YouGov shows the trend is already mainstream. In the UK and Ireland, 61% of consumers have used AI while shopping, and 53% do so often. Consumers are now asking assistants like Copilot, ChatGPT, and Gemini to find the best deal and buy it - compressing discovery, comparison, and decision into one interaction.
72% of shoppers who use AI say it is now their primary tool for researching products and brands. Another 77% say AI helps them make faster decisions. For marketing measurement, this means the old multichannel attribution models no longer capture how purchases actually happen.
AI adoption varies by age and category
Younger consumers lead trust and usage. 34% of 18-24 year olds trust AI in retail, and nearly two-thirds of Gen Z and Millennials want hyper-personalised AI shopping experiences. Among consumers 55+, only 14% trust AI in retail, yet nearly 45% have used it in the past six months and 11% use it daily.
Trust remains highest for price comparisons (66%) and lowest for placing orders (11%). Consumers let AI influence the journey but still want control at checkout.
Product categories show different adoption patterns. Grocery leads: 57.8% of shoppers expect AI to help find deals and coupons. In general eCommerce, more than 92% have encountered AI during an online shopping journey. Social commerce in the UK sees 70% of consumers purchasing through channels where AI-curated suggestions guide behaviour.
Trust is still a barrier - and that affects measurement
Despite rapid adoption, 68% of UK consumers cannot name a single AI shopping experience that impressed them. 55% distrust AI chatbots, and over half worry about data mishandling. The quality of AI interactions matters more than simply having an AI presence.
For brands investing in AI for marketing, the takeaway is clear: visibility in AI-driven journeys depends on structured product data, real-time API feeds, and accurate availability information - not just ad spend.
What this means for marketing measurement
Marketing Mix Modeling must evolve to capture the real drivers of AI-influenced demand. Structured product data needs to become a measurable input. API readiness - real-time pricing, stock, fulfilment - now determines whether an AI assistant recommends a product. AI-driven channels like conversational commerce should be a distinct line item in MMM, not lumped in with website traffic.
Quantifying incremental AI-assisted sales requires separating them from traditional search, SEO, or retail media. TransUnion, for example, is already incorporating structured data scoring into MMM and treating AI-driven discovery as its own channel.
Marketers who want to build these skills can follow an AI learning path for marketing managers that covers measurement frameworks for AI-mediated customer journeys.
Why this matters for marketing professionals
AI assistants won't replace marketers - but they will replace the search-based customer journey you have relied on. The brands that optimize their data feeds, API accuracy, and measurement models today will dominate AI recommendations tomorrow. If your MMM does not account for structured data quality and API performance, you are already underestimating the real drivers of demand.
Your membership also unlocks:
