Would You Subscribe If You Knew It Was AI-Generated? A Study on AI Disclosure, Perceived Value, and Subscription Intentions

Generative Artificial Intelligence (GenAI) is increasingly used to create digital content across media platforms, raising questions about transparency and user acceptance. This thesis investigates whether disclosing AI involvement in content creation influences users’ willingness to subscribe to digital media content. The study also examines whether perceived value acts as a mechanism through which AI disclosure affects subscription intentions. The research contributes to the growing discussion on AI transparency and digital media monetization.

As organizations increasingly integrate AI into content production, they face important decisions regarding transparency and disclosure practices. Understanding whether users react differently to AI-generated content has significant implications for digital media companies, content creators, online learning platforms, and subscription-based businesses. This research provides evidence on whether AI disclosure influences consumer behavior and helps practitioners better understand the factors that drive subscription intentions in AI-enabled digital environments.

Results showed that disclosing AI label did not significantly affect users’ willingness to subscribe to digital media content. Furthermore, perceived value did not significantly mediate the relationship between AI disclosure and subscription intentions. However, perceived value emerged as a positive predictor of willingness to subscribe. Users who perceived the content as useful, emotionally appealing, and relevant reported substantially higher subscription intentions. Overall, content value appeared to matter more than disclosure itself when evaluating subscription-based digital content.

Implications for Practitioners

• Focus on delivering high-value content rather than relying solely on AI disclosure strategies.
• Prioritize usefulness, relevance, and content quality to increase subscription intentions.
• Maintain transparent communication regarding AI use without assuming disclosure will negatively affect user behavior.
• Monitor user perceptions of value, as perceived value strongly influences subscription decisions.

Study Methods

Study employed a quantitative between-subjects online experiment. Participants were randomly assigned to one of two conditions: an AI disclosure condition or a no-disclosure condition. Both groups evaluated the same simulated digital media post, with the AI disclosure condition receiving an explicit label and statement indicating that the content had been AI generated. Data were collected through an online survey (N = 118). Perceived value was measured using adapted functional, emotional, and social value dimensions from the PERVAL scale, while willingness to subscribe served as the primary outcome variable. Data were analyzed using reliability analysis, t-tests, regression analysis, and mediation analysis in R.