Artificial intelligence (AI) is becoming increasingly present in all areas of our lives and is gradually being introduced into all spheres of work processes, including qualitative marketing research. For all its advantages, qualitative research has certain shortcomings that AI could help overcome. It is known to be carried out on small samples and its results are not considered statistically representative. The researcher is a key part of the qualitative research process but must be highly qualified and unbiased. At the same time, the whole process of qualitative research involves complex and lengthy stages that are time consuming and therefore expensive. In my master’s thesis, I focused on the comparison between traditional in-depth interviews and in-depth interviews conducted with AI. I wanted to examine if AI could collect the same quality of data, if it could adapt to the conversation during the interview in the same way as a human, and if AI could contribute to greater time and cost efficiency. The results showed that the quality of the data obtained was higher in the classic implementation of in-depth interviews, mainly due to the human moderator, who was better able to adapt to the flow of the conversation and more consistent in asking follow-up questions for clarification when needed. However, the AI-assisted interviews significantly shortened the research process, which also helped to reduce costs. AI was found to have great potential in qualitative marketing research, particularly in terms of extending the method to larger samples, but the researcher remains a key element of in-depth interviews that AI cannot replace.
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