AI and the Future of Advertising Creativity

Éditeurs invités

• Yung Kyun Choi, Dongguk University
• Tae Hyun Baek, Sungkyunkwan University

Synthèse

This special issue examines how generative AI is transforming advertising creativity. Generative tools are shifting creative work from slow, expensive human-led processes to rapid, scalable production of copy, images, video, and message variants. This technological shift raises fundamental questions about how advertising creativity is imagined, produced, evaluated, and valued in an industry where creative advantage has long been central to competitive success.

The papers sought will investigate how AI affects each stage of creative work, from idea generation through asset production to personalization and variant creation. Beyond the mechanics of creative production, the issue addresses how agencies, brands, and platforms are reorganizing creative labor, which roles and skills remain valuable, and how business models built on production fees are being reshaped as marginal costs approach zero.

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Thèmes proposés

• How does AI change the way creative ideas are generated, selected, and refined, and where in that process is human judgment most valuable?
• When does AI assistance widen the range of creative directions a team explores, and when does it narrow it?
• How should briefs, brainstorming, and creative workflows be redesigned around generative tools?
• What is the most effective division of labor between human creatives and AI across ideation, drafting, and refinement?
• How does near-zero marginal cost production change what advertising creative gets made, and how much of it?
• What is gained and lost when finished assets are generated rather than crafted?
• How does AI-produced creative compare with human-produced work on effectiveness, quality, and cost (for example, click-through, attention, and brand lift)?
• How does production at scale change media planning, creative testing, and iteration?
• How does generative AI change dynamic creative optimization and one-to-one message tailoring?
• How can brands produce thousands of variants without eroding distinctiveness and brand consistency?
• When does personalized AI creative outperform a single strong idea, and when does it not?
• How do consumers respond to creative that is visibly machine-tailored to them?
• How are agencies, in-house teams, and platforms reorganizing creative labor around AI?
• Which creative roles and skills are being automated, augmented, or newly created?
• How does AI reshape the agency and client relationship, the pitch process, and value capture?
• What happens to agency business models when the cost of production approaches zero?
• Does AI change how creativity is defined, judged, and rewarded in advertising?
• How should originality, distinctiveness, and craft be valued when execution becomes commoditized?
• Does widespread AI use homogenize advertising creative, and how can brands resist sameness?
• How should creative awards, evaluation standards, and quality benchmarks adapt?
• What methods (field experiments, computational and multimodal analysis, large-scale A/B testing) best capture the effect of AI on creative outcomes?
• How can creativity itself be measured at scale across large volumes of AI-generated work?
• How can researchers study homogenization, distinctiveness, and the diversity of creative output?
• When does AI-generated creative help or hurt brand building and long-term equity, and what guardrails keep it on-brand and effective?