AI in Advertising: New Directions in Practice, Consumer Responses, and Research Methods

Editors

• Yang Feng, California State University, Fullerton
• Quan Xie, Southern Methodist University
• Joanna Strycharz, University of Amsterdam

Description

Artificial intelligence is transforming advertising at multiple levels: as a tool for creative and strategic work, and as an autonomous agent capable of planning and executing tasks independently. This transformation raises fundamental questions about how advertising professionals collaborate with AI systems, how roles and authorship are being redefined, how consumers respond to AI-driven advertising, and what research methods and ethical safeguards are needed when AI participates in the research process itself.

The special issue invites contributions addressing three interconnected domains: human-AI collaboration in advertising practice and creative work; how AI-generated and AI-personalized advertising affects consumer perception and behavior; and how researchers should adapt their methodologies, standards, and ethical frameworks when collaborating with AI in data collection, stimulus generation, and analysis. Submissions may employ any methodological approach and should move beyond describing tools toward deeper insights about advertising, persuasion, and communication in the age of AI.

Potential topics

• Human-AI collaboration in advertising creative processes, including authorship, creative judgment, and practitioner roles across different contexts of advertising
• AI-assisted campaign strategy, optimization, and automated decision-making
• Agentic AI as a proactive partner in advertising practice and its implications for human oversight and accountability
• Governance structures for human-AI collaboration in advertising agencies and brand organizations
• The full range of human-AI collaborative modes, from tool use to co-creation to agentic delegation, and their implications for advertising practice and governance
• Human-AI collaboration in prosocial and public interest advertising
• Consumer perception, emotion, evaluation, and response to AI-generated advertising
• AI-driven personalization and its effects on persuasion, privacy, and consumer trust, consent, data protection, and consumer vulnerability
• Anthropomorphism, virtual influencers, AI digital twins, and AI agents as advertising vehicles
• AI advertising across diverse contexts, such as PSAs, health communication, political advertising, public policy, and nonprofit campaigns
• Ethical implications of AI advertising for vulnerable audiences, including children, older adults, patients, and politically targeted publics
• Consumer awareness, literacy, and resistance in response to AI-driven advertising systems
• Construct validity and stimulus equivalence in advertising experiments using AI-generated materials
• Reliability and replicability standards for AI-assisted advertising research
• Validity of AI-mediated data collection in advertising research
• Research ethics of AI-simulated participants and agentic data collection in advertising studies
• Privacy, consent, and data protection in AI-assisted research, synthetic data, and agentic data collection
• Bias and representational equity introduced through AI-assisted research designs and/or AI-generated advertising content
• Theoretical implications of human-AI collaboration for established advertising frameworks
• Agentic AI in advertising research and the governance structures needed to maintain scholarly rigor