The use of artificial intelligence in secondary market research: its opportunities and challenges for companies

The rapid development of artificial intelligence in various fields is leading to profound changes. The way data is collected, processed, and used is changing, especially in the field of market research. While traditional methods are based on manual data collection and analysis, which is often error-prone and time-consuming, AI-based tools enable the rapid processing of large amounts of data. This enables companies to identify prevailing market trends early on, analyze customer needs, and make well-founded strategic decisions to gain a competitive advantage.
This paper examines the opportunities and risks of using AI-based tools in secondary market research in a two-stage Delphi study conducted using semi-structured interviews with experts. The goal is to compare key theoretical assumptions with empirical expert statements in order to derive theoretical and practical implications. The evaluation using MAXQDA shows that the focus is on increased efficiency, cost and time savings, challenges regarding data quality, bias, and the importance of human-machine interaction. The results demonstrate that the successful use of AI depends not only on technological factors but also on user competence, training, and conscious implementation.