Almost four in ten Europeans use AI when researching purchases

Almost four in ten Europeans use generative AI as part of their product research process before making a purchase. That figure, 38 percent, points to a significant shift in how consumers prepare before deciding to buy.

Where people previously relied mainly on search engines, comparison sites and review platforms, a growing number of consumers are turning to AI chatbots and similar tools to ask questions, compare options and understand specifications. The rise of widely accessible generative AI applications such as ChatGPT, Gemini and Copilot has substantially lowered that barrier over the past two years.

The figures come from research reported by Emerce. Further details about the study design, sample size and the party that conducted the research cannot be fully verified based on the available source material.

How consumers use AI for product research

Generative AI is well suited to the early stage of a purchase journey: a consumer can ask questions about product features in plain language, weigh the pros and cons of different brands, or have a shortlist drawn up based on a budget and personal preferences. This interactive way of searching differs fundamentally from a traditional search query, where the user must navigate through multiple pages of results themselves.

The fact that consumers use AI does not automatically mean they act on AI-generated recommendations without looking further. Many users treat the tool as a starting point and then consult other sources to confirm their choice. Nevertheless, the moment at which brands and retailers need to be visible is shifting: those that do not appear in the output of an AI model risk being eliminated from the consideration process at an early stage.

Implications for e-commerce and content strategies

For online retailers and brands, this development has concrete implications. Traditional search engine optimisation (SEO) is geared towards how the algorithms of Google or Bing rank pages. With generative AI, the dynamic is different: the models retrieve information from a wide range of sources, process it and present a summary. Structured product information, clear specifications and authoritative product descriptions play a greater role in that process than keywords alone.

Some marketers are already speaking of generative engine optimisation (GEO) as a successor to or complement of SEO. The idea is that content is structured in such a way that AI models can process that information reliably and completely. How effective this approach is in practice, and which factors determine visibility in AI-generated responses, remains the subject of ongoing research and debate within the industry.

Differences within Europe

The figure of 38 percent is a European average, but adoption of AI tools varies by country, age group and product category. In countries with higher smartphone penetration and a younger average internet-using population, the share of AI users in purchase journeys tends to be higher. Product category also plays a role: for more expensive or technically complex products, such as electronics, travel or financial products, the willingness to research more extensively and use new tools in the process is generally greater.

Country-specific figures for the Netherlands are not available based on the source material at hand. The overall European picture does, however, align with broader trends identified by market researchers: the use of generative AI for information needs is growing rapidly, although some users are also beginning to question the reliability of AI-generated information.

What this means for the Dutch and European AI ecosystem

For founders and investors focused on AI applications in retail, e-commerce or marketing technology, these figures offer concrete market validation. Demand for tools that help companies measure and improve their visibility in AI-driven search journeys is growing in step with consumer adoption. Startups working on AI content optimisation, product data enrichment or conversational commerce are well positioned to capitalise on this momentum.

For policymakers and industry associations, the shift also raises questions about transparency: to what extent are consumers aware of how AI models arrive at product recommendations, and which information sources factor into that process? As more purchase decisions are partly influenced by AI-generated content, the discussion around transparency and consumer protection in relation to these systems becomes increasingly relevant. In Europe, that discussion is taking place partly in the context of the AI Act, which binds providers of general-purpose AI systems to information obligations.