Advances in Computer and Communication Article Recommendation | When Artificial Intelligence Learns to "Create": The Frontier Exploration of Advertising Creativity Generation and Style Consistency Modeling

"Is AI-generated advertising a revolutionary breakthrough for the creative industry, or the ultimate challenge to human creativity?" "In the pursuit of efficiency and personalization in the digital age, have we truly found the key to balancing creativity and scale?" These questions concern not only the future form of the advertising industry but also touch upon the profound proposition of how humans and machines can coexist in creative activities.

Jing Zheng from the Courant Institute of Mathematical Sciences, New York University, in her paper "Generative AI-driven Visual Advertising Creativity Generation and Style Consistency Modeling" published in Advances in Computer and Communication, systematically explains how generative artificial intelligence drives the generation of visual advertising creativity and constructs a computational model for maintaining brand style consistency. This research is bringing paradigm-level thinking to the advertising industry and even the entire creative economy.

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Generative AI and Advertising Creativity: A Human-Machine Collaborative Creativity Revolution

Traditional advertising creative production heavily relies on the collision of human effort, time, and inspiration, akin to an adventure with an unknown outcome. The introduction of generative AI is like installing an "intelligent engine" into the creative pipeline. Through advanced technologies such as deep learning, Generative Adversarial Networks (GANs), and diffusion models, AI can learn style, elements, and compositional logic from vast amounts of visual data, subsequently generating novel, diverse, and strategy-aligned visual advertising concepts. This not only greatly enhances the efficiency and scale of creative output but also, through style consistency modeling, ensures brand tonality remains uniform across diverse creative forms—this is not merely an upgrade of tools but an "industrial revolution" in creative production methods.

The Dilemma of Digital Advertising: Generative AI's Solution

The current advertising industry faces multiple challenges: fragmented user attention, rising demands for personalization, and accelerated content iteration, while traditional creative processes often struggle to keep up with the "mass customization" demands of marketing. Jing Zheng's research indicates that generative AI-driven systems can generate hundreds or even thousands of visual concepts in a short time. By learning from a brand's historical materials, they can automatically maintain consistency in style elements such as color, typography, layout, and imagery. This means brands can simultaneously address the diverse needs of different global markets without worrying about a fragmented image. This is not only a victory for algorithms in the lab but also a systematic response to the three major pain points of the industry: scale, personalization, and branding.

From Model to Practice: The Technical Challenges and Ethical Considerations Behind Creative Consistency

Despite the promising prospects, the comprehensive implementation of generative AI in the field of advertising creativity still faces deep challenges. How can AI not only imitate style but also understand brand spirit and emotional core? How to avoid bias in automated generation and ensure cultural adaptability? And most fundamentally—how to define AI's role in the creative process: is it a tool, a collaborator, or, in a sense, an "author"? Jing Zheng's research emphasizes the importance of "controllable generation" and the "human-in-the-loop," pointing out that true breakthroughs come from the deep integration of technological models and human creative guidance. Every step of application deepening requires the joint advancement of technological, ethical, design, and management thinking.

The Future of AI Creativity: Reshaping Brand Narratives and the Creative Ecosystem

The future of generative AI in advertising creativity extends far beyond improving efficiency. It may foster dynamic, real-time brand visual systems, allowing advertisements to automatically adjust their style based on environment, user mood, or even weather. It might promote the democratization of creativity, enabling even small and medium-sized brands to possess powerful visual expression capabilities. More profoundly, it may redefine "creativity" itself, prompting humans to focus on higher-dimensional strategy, emotion, and story building, while delegating executable, combinatorial, and adaptive creative work to AI collaboration, thereby triggering interdisciplinary resonance among marketing, design, psychology, and computer science.

"The highest mission of technology is not to replace humans, but to expand the boundaries of human creativity." At the forefront where creativity and technology converge, generative AI-driven advertising creativity generation and style consistency modeling are like a bridge under construction, connecting the demands of scale with the expression of personalization, and linking the rationality of technology with the warmth of creativity. It may be quietly rewriting the rules of brand storytelling for the next era.

Do you think AI-generated advertising creativity will ultimately be more "human" or more "machine-like"?

The study was published in Advances in Computer and Communication

https://www.hillpublisher.com/ArticleDetails/5720

How to cite this paper

Jing Zheng. (2025) Generative AI-driven Visual Advertising Creativity Generation and Style Consistency Modeling. Advances in Computer and Communication, 6(5), 262-267.

DOI: http://dx.doi.org/10.26855/acc.2025.12.001