Artificial intelligence (AI) has significantly advanced efficient, data-driven decision-making, but as AI becomes increasingly embedded in everyday life, it is essential to examine how our cultural values affect trust in AI within subjective contexts. This paper utilizes Hofstede’s cultural dimensions to investigate potential patterns in receptiveness towards perceived AI predictions during art interpretation. This work contributes a novel study design integrating electroencephalography (EEG), Pleasure-Arousal-Dominance (PAD) values, the Self-Assessment Manikin (SAM) scale, and machine-learning predictions from ArtEmis. Through regression modeling, no significant relationship was found between any cultural dimension and the number of responses altered post-AI prediction. However, 26 out of the total 35 college-student participants acknowledged experiencing self-reflection or persuasion when exposed to AI, regardless of cultural dimensions. This paper expands on prior research and notes future opportunities to address limitations related to sample size and the personalization of AI-user interaction.