AI vendor evaluation in market research means checking whether an AI-based service provider is trustworthy, ethical, and careful with your data before you sign a contract. Generative AI tools promise faster fieldwork and sharper insights, but not every supplier can prove how their models actually work. ESOMAR built its 20 Questions framework to close that exact gap.<\/p>\n\n\n\n
Generative AI use keeps climbing. McKinsey found<\/a> that 65 percent of organizations now use generative AI regularly, nearly double the share from the year before. Market research teams are buying into that wave, but few have a repeatable way to separate a responsible AI partner from a risky one.<\/p>\n\n\n\n This guide breaks down how to evaluate an AI vendor in market research, what ESOMAR’s questions actually ask, and where a platform like QuestionPro fits into a responsible AI evaluation.<\/p>\n\n\n\n\n\n AI vendor evaluation in market research is a structured review of a supplier’s people, technology, and data practices before you buy an AI-based tool or service. It answers one question: can this vendor be trusted with your respondents’ data and your research budget?<\/p>\n\n\n\n The review usually covers three areas. Who built the AI and how experienced are they? Does the AI product actually do what the vendor claims? And how well does the vendor protect the data that trains and runs the model?<\/p>\n\n\n\n An AI-based service is any offering where a vendor performs research tasks using AI, often combined with human review, rather than software you operate entirely yourself. That distinction shapes everything in the next section.<\/p>\n\n\n\n An AI tool is software you license and operate yourself. An AI-based service is work a vendor performs for you using AI, often layered with human review. The table below shows how that distinction changes what you evaluate.<\/p>\n\n\n\nWhat is AI vendor evaluation in market research?<\/strong><\/h2>\n\n\n\n
AI-based services vs AI tools: What is the difference?<\/strong><\/h2>\n\n\n\n