Designing marketing strategies based on a dual-method analysis of consumer attitudes toward generative AI

Abstract The rapid growth of generative artificial intelligence technologies has led to diverse discussions and reactions among consumers, necessitating a more comprehensive understanding of how consumers interpret and respond to this innovation. Prior research either relies on surveys and experiments or focuses on single tools, offering limited insight into naturalistic, large-scale consumer discourse. This research contributes to the literature by bridging the gap between scholarly theories and real-time public sentiment, moving beyond focus on single-tool studies (e.g., ChatGPT) to offer a comprehensive analysis of generative AI adoption. This study analyzes 1.3 million Reddit posts and comments from 2018 to 2025 using topic modeling, sentiment analysis, and trend analysis, complemented by a thematic review of 35 most relevant research papers in the academic literature. Our findings reveal that as the technology becomes more powerful and integrated into daily life, consumer concerns shift from purely technical issues to deeply socio-economic and ethical challenges, specifically regarding job displacement, legal challenges, the 'monopoly of hardware', and the desire for authenticity in AI-generated outputs. Notably, we identify a ‘novelty-utility’ paradox where consumers favor AI in creative domains but exhibit strong algorithm aversion in tasks perceived as fundamental human skills. Additionally, consumer responses are moderated based on AI novelty effects, algorithm aversion, and the importance of transparency and customizability in the user experience. For practitioners, we derive data-driven marketing strategies emphasizing augmentation-focused positioning, temporal responsiveness, proactive ethical positioning, and participatory design. The results are scoped to digitally engaged early-adopter communities that shape broader technology discourse.