AI-driven Visual Communication in Advertising: A Study on Consumer Engagement and Brand Recognition

Abstract

The rapid advancement of artificial intelligence (AI) is reshaping visual communication practices within the global advertising industry. This systematic literature review (SLR) examines how AI-driven visual tools influence two critical marketing outcomes: consumer engagement and brand recognition. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, the study analyzes 43 peer-reviewed, Scopus-indexed articles published between 2018 and early 2026. The review identifies key AI technologies—including generative adversarial networks (GANs), diffusion models, computer vision, and dynamic creative optimization (DCO)—and evaluates their applications in advertising creative processes. Findings indicate that AI-generated visuals significantly enhance consumer engagement by improving attention, emotional response, interactivity, and perceived personalization through real-time contextual adaptation. In parallel, AI strengthens brand recognition and recall by ensuring visual identity consistency, optimizing distinctive brand assets through predictive analytics, and enhancing memorability using data-driven design principles. Emerging trends such as synthetic influencers, ethical AI deployment, and neuromarketing integration are also highlighted. While AI offers substantial benefits in scalability, efficiency, and performance measurement, notable research gaps persist regarding long-term brand equity, ethical governance, and human–AI creative collaboration. This review provides an integrative framework to guide future research and strategic practice.