One step forward, two steps back: AI generated content vs. perceived trust, authenticity and credibility

Abstract

Background: The article examines the impact of knowledge about AI-generated content on perceived trust, authenticity, and credibility. It is based on the assumption that companies use AI in their marketing communications as a means of optimization and that customers are distrustful of its use, which negatively affects their subjective perception of the value of the marketing concept associated with AI. This situation requires the identification of functional solutions in relation to changes in consumer attitudes.
Objective: For this reason, the aim of this article is to identify which formats and contents of marketing communication using AI are risky in terms of consumer-perceived value and, based on these findings, to develop framework recommendations for the practical use of AI in marketing communication.
Methodology: In order to achieve this goal, our own research is being conducted using a survey method. The research was conducted between August and October 2025, with a sample of 485 respondents from the Czech Republic. The results were then statistically analysed using IBM SPSS Statistics software.
Findings: It was confirmed that AI-generated marketing content has a negative effect on perceived trust, authenticity, and credibility when recognized by consumers. At the same time, risky forms and content of marketing communication using AI were identified. It has been found out that 1) there is no statistically significant relationship between the displayed form of AI-powered marketing communications and the level of trust, authenticity, and credibility that consumers have in these communications; 2) from a consumer perspective, the rational content of AI-powered marketing communications has a very high level of impact on trust, authenticity, and credibility (by contrast, the emotional content of these communications was perceived as having a low or very low level of trust, authenticity, and credibility); and 3) there is no statistically significant relationship between the age of consumers and their level of trust, authenticity, and credibility in AI-powered marketing communications.
Practical implications: From a long-term strategic perspective, companies should build so-called AI-ready marketing architectures that enable the effective integration of algorithmic tools while maintaining the integral human dimension of communication.
Limitations: The applicability of these recommendations is determined by several factors, including the technological maturity of the company, the level of digital literacy of the target segments, sector-specific characteristics, and the nature of the competitive environment.

Keywords: AI generated content, trust, authenticity, credibility, consumer literacy, value-based marketing, corporate social responsibility, CSR.

JEL classification: M14, M31, M37

Acknowledgement: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This paper was supported within The Internal Grant Agency of AMBIS University KMCR-2025-01 and IGA 1050.