Risks of using generative artificial intelligence in marketing research

Abstract

The article examines the practice of using generative artificial intelligence (GAI) in marketing activities, which allowed us to identify its impact on marketing research and outline the risks that researchers face at each stage of the process.

Introduction. Digitalization is changing the business landscape. A technology that has a significant scope of application and is capable of performing many tasks efficiently is generative artificial intelligence. In addition to the ability to automate routine processes, GAI is able to generate ideas, understand the client more deeply, provide hyper-personalization, make better forecasts and offer innovative solutions in the field of marketing. Its use expands the possibilities for analyzing data sets and predictive analytics, but at the same time is accompanied by a number of risks and challenges. This necessitates a critical understanding of the consequences of using GAI in marketing research.

Problem statement. The integration of generative AI into marketing research is transforming approaches to collecting, processing, and interpreting consumer behavior data. While AI technologies provide obvious benefits, there is a growing dependence on algorithmic solutions, the use of which carries risks that can significantly affect the results obtained.

Unresolved aspects of the problem. espite the significant interest in AI on the part of scientists, the issue of using generative artificial intelligence in marketing research is beyond their attention. In particular, the issues of ensuring data confidentiality, data quality control, combating bots, preventing "hallucinations" of AI models, and others remain unaddressed. That is, risks that violate human rights and can distort research results.

Purpose of the article.The purpose of the article is to systematize the risks of using AI in marketing research and find ways to minimize them.

Presentation of the main material. Analytical reports of research agencies on the practice of using AI are analyzed. Practical areas of its application in marketing activities are highlighted, the advantages and disadvantages of using AI in the process of marketing research are highlighted, the risks faced by market researchers are outlined, the risks of using AI in marketing research are systematized by the nature of their origin, and measures to minimize the identified risks are provided.

Conclusions. Marketing research using AI should be based on the use of a hybrid approach (human ↔ AI), since it is able to provide an optimal combination of the advantages of algorithmic technologies and human expertise. The practical significance lies in the possibility of minimizing risks, adhering to ethical standards, and reducing errors in decision-making.