HOW CAN ADVERTISERS LEVERAGE AI AND GENERATIVE AI?
Half of advertising in 2023 involves some form of AI (Stam, 2023), and marketing is an industry McKinsey predicts has one of the largest amounts of potential value to gain from AI (Chui et al. 2023). Advertisers and marketers also recognize this potential, believing current use of generative AI has room to grow (Deveau, Griffin, and Reis, 2023). The goal of this special issue is to help advertisers unlock the potential of both AI and generative AI by developing theoretical knowledge that can inform advertising practice. Successful manuscripts will bolster our growing collection of articles on AI (e.g., Campbell, Plangger, Sands et al., 2022; Kietzmann, Paschen, and Treen, 2018; Wu and Wen, 2021).
AI-related tools are already present in the ad industry, being used for prospecting (e.g., 6sense.com), data management and customer engagement (e.g., segment.com), copywriting (e.g., Jasper.ai, Writer.com), SEO (e.g., SurferSEO.com, Headlime.com, Semrush.com), chatbots (e.g., Chatfuel.com, Drift.com), digital ad personalization and optimization (e.g., albert.ai), media monitoring and competitive intelligence (e.g., Brand24.com, Crayon.co), influencer selection (e.g., influencity.com), social media engagement (e.g., Manychat.com), PR campaigns (e.g., Howler.media), social media content creation (e.g., predis.ai, Flick.social), visuals (e.g., DALL-E 2, DreamStudio.ai, midjourney.com), and of course dedicated tasks related to advertising (e.g., ChatGPT).
However, as AI tools are developing rapidly in the advertising industry they remain a relatively new area of advertising research. As such, little is known about how consumers respond to AI and how advertisers can leverage AI to maximize its potential and mitigate its risks. This special issue of JAR seeks manuscripts on use of all forms of AI and generative AI in advertising. Our goal is to publish a set of articles that provide theoretical insights and actionable recommendations related to how AI affects consumers and advertisers.
Submissions are welcome on an ongoing basis up to March 25, 2024.
We suggest the following indicative topics but welcome others as well:
- What possibilities exist for how AI and generative AI can be harnessed by advertisers? Where are advertisers likely to see the most effective use of AI?
- How might advertising research evolve due to new generative AI-based research tools? Can they replace or merely augment human efforts?
- To what extent are consumers aware of and knowledgeable about AI practices in content they view? What factors influence audience experience and trust in viewing AI generated content? How do consumers react to AI mimicking human behaviors?
- How can generative AI be used in SEO and experimentation such as A/B testing?
- When and how are generative AI tools best used to create visuals and copy in advertisements? How do consumers respond to ads created using generative AI and why? Do consumers respond differently to certain types of ads and, if so, why?
- How do AI technologies such as interactive ads and logo detection influence consumer experience and the consumer journey?
- Generative AI has the potential to create hyper-personalized ads served to micro-segments or even individual consumers. How will consumers respond to such ads? When and why might consumers like vs. resist such personalization?
- Generative AI makes it possible to alter characteristics of models in ads to increase diversity. For instance, AI can be used to change ethnicity, age, and gender. How do consumers respond to such virtual diversity?
- How can advertisers respond to the threat of components of their ads being copied, altered, or used by others? To what extent should brands use material (i.e., images, text) and ideas from others when creating using generative AI?
- What factors affect organizational adoption of AI and what risks do advertisers and marketers need to be aware of and mitigate to ensure its effective use?
- What ethical considerations do advertisers need to be aware of (e.g., algorithm bias) when utilizing generative AI and what consequences exist for Diversity, Equity and Inclusion (DEI)? What implications does this have for governance of AI to ensure a responsible and ethical approach to use?
While theoretical insights are vital, given our strong industry readership, we also ask authors to pay particular attention to the practitioner implications of their research findings. The length for JAR submissions is 7,000 words, excluding references and web appendices. Authors are encouraged to make use of online appendices for material useful, but not central, to the paper. Submission guidelines can be found here.
The special section editors are Ben Lowe (b.lowe@kent.ac.uk), Eddie Luo (e.luo@kent.ac.uk) and Des Laffey (d.j.laffey@kent.ac.uk).
Papers should be submitted via the JAR’s Editorial Manager online platform.
References
Campbell, C., K. Plangger, S. Sands, J. Kietzmann, J., and K. Bates. “How Deepfakes and Artificial Intelligence Could Reshape the Advertising Industry: The Coming Reality of AI Fakes and Their Potential Impact on Consumer Behavior.” Journal of Advertising Research 62, 3 (2022): 241–251.
Chui, M., E. Hazan, R. Roberts, A. Singla, K. Smaje, A. Sukharevsky, L. Yee, and R. Zemmel (2023, June 14). “The Economic Potential of Generative AI: The Next Productivity Frontier.” Retrieved from the McKinsey Digital web page https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
Deveau, R., S. J. Griffin, and S. Reis (2023, May 11). “AI-Powered Marketing and Sales Reach New Heights with Generative AI.” Retrieved from the McKinsey website https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/ai-powered-marketing-and-sales-reach-new-heights-with-generative-ai
Kietzmann, J., J. Paschen, and E. Treen. “Artificial Intelligence in Advertising: How Marketers Can Leverage Artificial Intelligence along the Consumer Journey.” Journal of Advertising Research 58, 3: (2018) 263–267.
Stam, A. (2023, June 12). “AI Will Impact at Least Half of All Ad Revenue in 2023, GroupM Predicts.” Retrieved from the AdAge website https://adage.com/article/agency-news/ai-will-impact-least-half-all-ad-revenue-2023-groupm-predicts/2499161
Wu, L., and T. J. Wen. “Understanding AI Advertising from the Consumer Perspective: What Factors Determine Consumer Appreciation of AI-Created Advertisements?” Journal of Advertising Research 61, 2 (2021): 133–146.