The power of generative marketing: Can generative AI reach human-level visual marketing content?

Capable of generating photorealistic images, generative AI can augment human creativity and disrupt the economics of marketing content production. While anecdotal evidence hints at high-quality visual outputs of generative AI, little is known about these novel models' effectiveness across marketing contexts. This paper explores the disruptive potential of text-to-image diffusion models for visual marketing content generation, systematically evaluating the performance of AI-generated vs. human-made images across three important marketing dimensions: human perception (quality, realism), social media engagement (likes, comments), and click-through rates (CTRs) of banner ads. In three preregistered studies, we collect more than 17,000 human evaluations for over 1,500 synthetic images generated with 13 text-to-image diffusion models. We obtain converging evidence that synthetic, AIgenerated images can (i) significantly outperform human-made images regarding perceived quality and realism, (ii) obtain comparable engagement levels in a social media context, and (iii) achieve a +22% higher CTR in a randomized field experiment with more than 86,000 impressions. Our findings suggest that the paradigm shift brought about by generative AI can help firms produce marketing content not only faster and cheaper but also at human quality and effectiveness levels with important implications for firms, consumers, and policymakers.