Artificial or Authentic? Exploring the Impact of AI Disclosure on perceived Authenticity in B2B Marketing

Abstract

Generative artificial intelligence (AI) is currently reshaping the paradigm of how businessto-business (B2B) marketers create customer-centric content. While regulatory bodies are calling for transparency, practitioners must cope with the potential consequences disclosing something as AI-generated, such as being perceived as less authentic by the customers – a disclosure-dilemma for managers. Based on established algorithmic aversion theory and empirical findings in other contexts, this thesis aims to bridge the gap for a B2B context and determine whether AI authorship disclosure is followed by an authenticity penalty and whether that penalty is in some way dependent on how familiar the recipient is with the technology. A two-cell between-subjects online experiment (N = 102) exposed participants to the same promotional e-mail, randomly labelled as either AI- or human-written. After reading the stimulus, respondents rated its perceived authenticity and reported their own trust in AI and familiarity with AI. Results show that e-mails disclosed as AI-authored were judged significantly less authentic. The degree of AI familiarity did not moderate this effect: even highly familiar participants still penalized AI disclosure. However, greater trust in AI did raise authenticity perceptions under both disclosure conditions and familiarity correlated positively with trust. Taken together, the findings suggest that AI disclosure can undercut a critical relational signal in B2B marketing; a high affinity of the buyers with AI systems does not suffice as a counterweight to the associated penalty. Businesses should therefore combine disclosure with complementary trust-building cues such as evidence of human oversight and proof of trustworthiness of the AI system. Disclosure may also be something which can be implemented sporadically wherever authenticity is not as critical or obligatory.

Date of Award	2025
Original language	English
Supervisor	Elisabeth Frankus (Supervisor)