This research examines the role of emotion recognition in artificial intelligence (AI) as a means to strengthen consumer trust, with a particular emphasis on Galvanic Skin Response (GSR) analysis. The study addresses a significant gap in the current literature by exploring the emotional dynamics of AI trust in the context of AI-generated video advertisements. A neuromarketing approach was utilized, involving a sample of 17 respondents from Sumy State University, divided into ‘Trust’ and ‘Neutral’ groups based on their expressed trust in AI technologies. The study employed GSR to measure physiological responses, analyzing emotional arousal through metrics such as peak count, peaks per minute, and average peak amplitude. The findings indicate that while trust in AI does not significantly affect the frequency of emotional arousal, it does influence the intensity of emotional responses, particularly in content that challenges or affirms the participants’ views on AI. These insights underscore the complex relationship between trust and emotional engagement with AI-generated content and suggest that marketers should tailor AI-generated advertisements according to the trust levels of their target audience. This research contributes valuable empirical evidence to the ongoing discourse on AI trust, offering practical implications for the design and deployment of AI-driven consumer interactions.