Abstract This paper offers frameworks and guidance for the integration of AI into research workflows by examining foundational qualities of AI and the kinds of UX and market research that will create value as AI technologies continue to evolve. We tie the use of AI in early‐stage innovation research to outcomes of product and service design. While we recognize AI, synthetic data, and AI‐generated users have the potential to enhance aspects of the design and innovation process, particularly around desk research and storytelling, we show that they are unable to provide key ingredients that come from in‐context research, which is critical for this type of work. Specifically, we argue that by bypassing in‐context research, especially for complex design challenges without established behavioral patterns, teams fail to gather the rich learning necessary for breakthrough products and fail to develop team intelligence.
Notini et al. (Sat,) studied this question.
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