The future of advertising campaigns: The role of AI-generated images in advertising creative | Intellect Skip to content
1981
  1. Home
  2. A-Z Publications
  3. Journal of Pervasive Media
  4. Volume 8, Issue 1
  5. Article
AI, Augmentation and Art
  • ISSN: 2633-8793
  • E-ISSN: 2633-8785

Abstract

Computational creativity is a growing component of new artificial intelligence (AI) technologies that allow a machine to render creative constructs such as music, text and images. A rapidly growing area of computational creativity is AI text-to-image engines capable of producing realistic imagery that can now meet the standard of human quality outputs. DALL-E 2, built by OpenAI, is a leader in the field and offers commercial access to AI-produced images. To understand the impact of engines such as DALL-E 2 on advertising agencies and their creative workflows, we conducted a series of focus groups with Aotearoa, New Zealand-based advertising agencies exploring creative practitioners’ considerations on the capability of the DALL-E 2 text-to-image technology. An existing Volkswagen advertising campaign called ‘Small but Ferocious’ that used ‘blended’ animals as a visual metaphor for their economical yet powerful ‘TSI’ engines was expanded in a ‘faux’ continuation of the campaign. Four new images produced by DALL-E 2 were presented to creatives attending the focus groups. Participants were then asked about these new creative-AI assets concerning image quality, creative production and collaborative models. A thematic analysis of the comments from the focus groups was conducted and elicited three themes: and . Participants’ responses revealed that they were both excited and concerned about DALL-E 2’s capability in image production, its effect on creative workflows and the role of the human vs. machine in generating creative outputs. The result was a clear sense of inevitability for how creative roles will change as computational creativity systems, such as DALL-E 2, advance and are adopted into agency workflows.

© 2023 Intellect Ltd
Loading

Article metrics loading...

/content/journals/10.1386/jpm_00003_1
2023-08-18
2024-04-27
Loading full text...

Full text loading...

References

  1. Adams, William C.. ( 2015;), ‘ Conducting semi-structured interviews. ’, in K. E. Newcomer,, H. P. Hatry, and J. S. Wholey. (eds), Handbook of Practical Program Evaluation, Hoboken, NJ:: Wiley;, pp. 492–505.
     [Google Scholar]
  2. Ang, Swee Hoom,, Lee, Yih Hwai, and Leong, Siew Meng. ( 2007;), ‘ The ad creativity cube: Conceptualization and initial validation. ’, Journal of the Academy of Marketing Science, 35:2, pp. 220–32.
     [Google Scholar]
  3. Appel, Gil,, Grewal, Lauren,, Hadi, Rhonda, and Stephen, Andrew T.. ( 2020;), ‘ The future of social media in marketing. ’, Journal of the Academy of Marketing Science, 48:6, pp. 79–95.
     [Google Scholar]
  4. Bakpayev, Marat,, Baek, Tae Hyun,, van Esch, Patrick, and Yoon, Sukki. ( 2022;), ‘ Programmatic creative: AI can think but it cannot feel. ’, Australasian Marketing Journal, 30:1, pp. 90–95.
     [Google Scholar]
  5. Barker, Richie. ( 2019;), ‘ Creatives talk technology: Exploring the role and influence of digital media in the creative process of advertising art directors and copywriters. ’, Media Practice and Education, 20:3, pp. 244–59.
     [Google Scholar]
  6. Bilton, Chris. ( 2007), Management and Creativity: From Creative Industries to Creative Management, Oxford:: Blackwell Publishing;.
     [Google Scholar]
  7. Braun, Virginia, and Clarke, Victoria. ( 2006;), ‘ Using thematic analysis in psychology. ’, Qualitative Research in Psychology, 3:2, pp. 77–101.
     [Google Scholar]
  8. Brougham, David, and Haar, Jarrod. ( 2017;), ‘ Employee assessment of their technological redundancy. ’, Labour and Industry, 27:3, pp. 213–31.
     [Google Scholar]
  9. Byrne, David. ( 2022;), ‘ A worked example of Braun and Clarke’s approach to reflexive thematic analysis. ’, Quality & Quantity, 56:3, pp. 1391–412.
     [Google Scholar]
  10. Campbell, Colin,, Plangger, Kirk,, Sands, Sean, and Kietzman, Jan. ( 2022a;), ‘ Preparing for an era of deepfakes and AI-generated ads: A framework for understanding responses to manipulated advertising. ’, Journal of Advertising, 51:1, pp. 22–38.
     [Google Scholar]
  11. Campbell, Colin,, Plangger, Kirk,, Sands, Sean,, Kietzmann, Jan, and Bates, Kenneth. ( 2022b;), ‘ 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, pp. 241–51.
     [Google Scholar]
  12. Chelliah, John. ( 2017;), ‘ Will artificial intelligence usurp white collar jobs?. ’, Human Resource Management International Digest, 25:3, pp. 1–3.
     [Google Scholar]
  13. Chen, Gang,, Xie, Peihong,, Dong, Jing, and Wang, Tianfu. ( 2019;), ‘ Understanding programmatic creative: The role of AI. ’, Journal of Advertising, 48:4, pp. 347–55.
     [Google Scholar]
  14. Coffin, Jack. ( 2022;), ‘ Asking questions of AI advertising: A maieutic approach. ’, Journal of Advertising, 51:5, pp. 608–23.
     [Google Scholar]
  15. Davenport, Thomas H., and Mittal, Nitin. ( 2022;), ‘ How generative AI is changing creative work. ’, Harvard Business Review, 14 November, https://hbr.org/2022/11/how-generative-ai-is-changing-creative-work. Accessed 15 January 2023.
     [Google Scholar]
  16. Eglash, Ron,, Robert, Lionel,, Bennett, Audrey,, Robinson, Kwame Porter,, Lachney, Michael, and Babbitt, William. ( 2020;), ‘ Automation for the artisanal economy: Enhancing the economic and environmental sustainability of crafting professions with human–machine collaboration. ’, AI & Society, 35:3, pp. 595–609.
     [Google Scholar]
  17. El-Murad, Jaafar, and West, Douglas C.. ( 2004;), ‘ The definition and measurement of creativity: What do we know?. ’, Journal of Advertising Research, 44:2, pp. 188–201.
     [Google Scholar]
  18. Grba, Dejan. ( 2022;), ‘ Deep else: A critical framework for AI art. ’, Digital, 2:1, pp. 1–32.
     [Google Scholar]
  19. Gross, Dariusz. ( 2022;), ‘ The GAN is dead, long live DALL-E 2!. ’, MLearning.ai , 8 April, https://medium.com/mlearning-ai/the-gan-is-dead-long-live-the-dall-e-2-5a7e4d847179. Accessed 20 February 20223.
  20. Huang, Ming-Hui, and Rust, Roland T.. ( 2018;), ‘ Artificial intelligence in service. ’, Journal of Service Research, 21:2, pp. 155–72.
     [Google Scholar]
  21. Hughes, Dan. ( 2022;), ‘ Best examples of AI in marketing. ’, Digital Marketing Institute , 1 April, https://digitalmarketinginstitute.com/blog/some-inspiring-uses-of-ai-in-digital-marketing. Accessed 12 February 2023.
  22. Huh, Jisu, and Malthouse, Edward C.. ( 2020;), ‘ Advancing computational advertising: Conceptualization of the field and future directions. ’, Journal of Advertising, 49:4, pp. 367–76.
     [Google Scholar]
  23. Jiménez, Eduardo Alejandro López, and Ouariachi, Tania. ( 2021;), ‘An exploration of the impact of artificial intelligence (AI) and automation for communication professionals. ’, Journal of Information, Communication and Ethics in Society, 19:2, pp. 249–67.
     [Google Scholar]
  24. Kim, WooJin,, Ryoo, Yuhosua,, Lee, SoYoung, and Lee, Jung Ah. ( 2022;), ‘ Chatbot advertising as a double-edged sword: The roles of regulatory focus and privacy concerns. ’, Journal of Advertising, online first, https://doi.org/10.1080/00913367.2022.2043795.
     [Google Scholar]
  25. Liu, Gloria. ( 2022;), ‘ The world’s smartest artificial intelligence just made its first magazine cover. ’, Cosmopolitan, 22 June, https://www.cosmopolitan.com/lifestyle/a40314356/dall-e-2-artificial-intelligence-cover/. Accessed 20 February 2023.
     [Google Scholar]
  26. Lyu, Yanru,, Wang, Xinxin,, Lin, Rungtai, and Wu, Jun. ( 2022;), ‘ Communication in human–AI co-creation: Perceptual analysis of paintings generated by text-to-image system. ’, Applied Sciences, 12:23, pp. 1–19.
     [Google Scholar]
  27. Marcus, Gary,, Davis, Ernest, and Anderson, Scott. ( 2022;), ‘ A very preliminary analysis of DALL-E 2. ’, ARXIV Preprint, 2204, pp. 1–14.
     [Google Scholar]
  28. McCarthy, John,, Minsky, Marvin,, Rochester, Nathaniel, and Shannon, Claude E.. ( 1955;), ‘ A proposal for the Dartmouth summer research project on artificial intelligence. ’, Stanford University , 31 August, http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html. Accessed 20 February 2023.
  29. McCormack, Jon,, Hutchings, Patrick,, Gifford, Toby,, Yee-King, Matthew,, Llano, Maria Teresa, and D’Inverno, Mark. ( 2020;), ‘ Design considerations for real-time collaboration with creative artificial intelligence. ’, Organised Sound, 25:1, pp. 41–52.
     [Google Scholar]
  30. Mogaji, Emmanuel,, Olaleye, Sunday, and Ukpabi, Dandison. ( 2020;), ‘ Using AI to personalise emotionally appealing advertisement. ’, in N. P. Rana,, E. L. Slade,, G. P. Sahu,, H. Kizgin,, N. Singh,, B. Dey,, A. Gutierrez, and Y. K. Dwivedi. (eds), Digital and Social Media Marketing: Emerging Applications and Theoretical Development, Handel:: Springer;, pp. 137–50.
     [Google Scholar]
  31. Nader, Karim,, Toprac, Paul,, Scott, Suzanne, and Baker, Samuel. ( 2022;), ‘ Public understanding of artificial intelligence through entertainment media. ’, AI & Society, online first, https://doi.org/10.1007/s00146-022-01427-w.
     [Google Scholar]
  32. Nairat, Malik,, Nordahl, Mats, and Dahlstedt, Palle. ( 2020;), ‘ Generative comics: A character evolution approach for creating fictional comics. ’, Digital Creativity, 31:4, pp. 284–301.
     [Google Scholar]
  33. Norris, Phil. ( 2021;), ‘ 10 impressive examples of AI in marketing. ’, Blog Social Media , 18 November, https://blog.socialmediastrategiessummit.com/10-examples-of-ai-in-marketing/. Accessed 18 February 2023.
  34. O’Connor, Ryan. ( 2022;), ‘ How DALL-E 2 actually works. ’, Assembly AI , 19 April, https://www.assemblyai.com/blog/how-dall-e-2-actually-works/. Accessed 20 February 2023.
  35. OpenAI ( n.d;.), ‘ DALL-E 2. ’, https://openai.com/product/dall-e-2. Accessed 13 January 2023.
  36. Oppenlaender, Jonas. ( 2022;), ‘ The creativity of text-to-image generation. ’, in Proceedings of the 25th International Academic Mindtrek Conference, Tampere, Finland, 16–18 November, New York:: ACM;, pp. 192–202.
     [Google Scholar]
  37. Pfeffer, Jeffrey, and Fong, Christina T.. ( 2005;), ‘ Building organization theory from first principles: The self-enhancement motive and understanding power and influence. ’, Organization Science, 16:4, pp. 327–451.
     [Google Scholar]
  38. Pullen, Matthew. ( n.d;.), ‘ TSI Small but Ferocious. ’, Matthew Pullen Advertising Portfolio , https://matthewpullen.co.za/volkswagen-tsi-small-but-ferocious. Accessed 14 October 2022.
  39. Qin, Xuebing, and Jiang, Zhibin. ( 2019;), ‘ The impact of AI on the advertising process: The Chinese experience. ’, Journal of Advertising, 48:4, pp. 338–46.
     [Google Scholar]
  40. Radu, Mihnea. ( 2015a;), ‘ This is a Tiguan: Half tiger, half iguana, says Volkswagen. ’, Autoevolution , 30 January, https://www.autoevolution.com/news/this-is-a-tiguan-half-tiger-half-iguana-says-volkswagen-video-91756.html. Accessed 20 January 2023.
  41. Radu, Mihnea. ( 2015b;), ‘ Volkswagen print ads show “Small but Ferocious” hybrid animals to promote TSI turbos. ’, Autoevolution , 27 March, https://www.autoevolution.com/news/volkswagen-print-ads-show-small-but-ferocious-hybrid-animals-to-promote-tsi-turbos-93765.html. Accessed 20 January 2023.
  42. Ramesh, Aditya,, Pavlov, Mikhail,, Goh, Gabriel,, Gray, Scott,, Voss, Chelsea,, Radford, Alec,, Chen, Mark, and Sutskever, Ilya. ( 2021;), ‘ Zero-shot text-to-image generation. ’, in M. Meila, and T. Zhang. (eds), Proceedings of the International Conference on Machine Learning, Virtual, 18–24 July, https://doi.org/10.48550/arXiv.2102.12092.
     [Google Scholar]
  43. Reddy, Anuradha. ( 2022;), ‘ Artificial everyday creativity: Creative leaps with AI through critical making. ’, Digital Creativity, 33:4, pp. 295–313.
     [Google Scholar]
  44. Reviriego, Pedro, and Merino-Gómez, Elena. ( 2022;), ‘ Text to image generation: Leaving no language behind. ’, ARXIV preprint, https://doi.org/10.48550/arXiv.2208.09333.
  45. Rodgers, Shelly. ( 2021;), ‘ Themed issue introduction: Promises and perils of artificial intelligence and advertising. ’, Journal of Advertising, 50:1, pp. 1–10.
     [Google Scholar]
  46. Schetinger, Victor,, Bartolomeo, Sara Di,, El-Assady, Mennatallah,, McNutt, Andrew M.,, Miller, Matthais, and Adams, Jane L.. ( 2023;), ‘ Doom or deliciousness: Challenges and opportunities for visualization in the age of generative models. ’, preprint, Computer Graphics Forum, 42:3, https://doi.org/10.31219/osf.io/3jrcm.
     [Google Scholar]
  47. Scott, Linda M.. ( 1994;), ‘ Images in advertising: The need for a theory of visual rhetoric. ’, Journal of Consumer Research, 21:2, pp. 252–73.
     [Google Scholar]
  48. Smith, Amy,, Schroeder, Hope,, Epstein, Ziv,, Cook, Michael,, Colton, Simon, and Lippman, Andrew. ( 2023;), ‘ Trash to treasure: Using text-to-image models to inform the design of physical artefacts. ’, in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC:, 7–14 February, ARXIV preprint, https://doi.org/10.48550/arXiv.2302.00561.
     [Google Scholar]
  49. Taylor, Charles R.. ( 2019;), ‘ Editorial: Artificial intelligence, customized communications, privacy, and the general data protection regulation (GDPR). ’, International Journal of Advertising, 38:5, pp. 649–50.
     [Google Scholar]
  50. Thomas, Veronica L., and Fowler, Kendra. ( 2021;), ‘ Close encounters of the AI kind: Use of AI influencers as brand endorsers. ’, Journal of Advertising, 50:1, pp. 11–25.
     [Google Scholar]
  51. Tuomi, Aarni. ( 2023;), ‘ AI-generated content, creative freelance work and hospitality and tourism marketing. ’, in B. Ferrer-Rosell,, D. Massimo, and K. Berezina. (eds), Information and Communication Technologies in Tourism 2023, Springer Proceedings in Business and Economics, Cham:: Springer;, pp. 323–28, https://doi.org/10.1007/978-3-031-25752-0_35.
     [Google Scholar]
  52. Turnball, Sarah, and Wheeler, Colin. ( 2017;), ‘ The advertising creative process: A study of UK agencies. ’, Journal of Marketing Communications, 23:2, pp. 176–94.
     [Google Scholar]
  53. Vakratsas, Demetrios, and Wang, Xin (Shane). ( 2021;), ‘ Artificial intelligence in advertising creativity. ’, Journal of Advertising, 50:1, pp. 39–51.
     [Google Scholar]
  54. van Noort, Guda,, Himelboim, Itai,, Martin, Jolie, and Collinger, Tom. ( 2020;), ‘ Introducing a model of automated brand-generated content in an era of computational advertising. ’, Journal of Advertising, 49:4, pp. 411–27.
     [Google Scholar]
  55. Vartiainen, Henriikka, and Tedre, Matti. ( 2023;), ‘ Using artificial intelligence in craft education: Crafting with text-to-image generative models. ’, Digital Creativity, online first, https://doi.org/10.1080/14626268.2023.2174557.
     [Google Scholar]
  56. Veale, Tony, and Pérez, Rafael Pérez y. ( 2020;), ‘ Leaps and bounds: An introduction to the field of computational creativity. ’, New Generation Computing, 38:4, pp. 551–36.
     [Google Scholar]
  57. Verma, Manisha, and Mishra, Shaunak. ( 2022;), ‘ Recommendation systems for ad creation: A view from the trenches. ’, in F. M. Harper,, V. Murdock,, M. Ekstrand,, B. Shapira,, J. Basilico,, K. Lundgaard, and E. Oldridge. (eds), Proceedings of the 16th ACM Conference on Recommender Systems, Seattle, WA, 18–23 September, Seattle, WA:: RecSys;, pp. 525–27.
     [Google Scholar]
  58. Vires, Katja de. ( 2020;), ‘ You never fake alone. ’, Information, Communication & Society, 23:14, pp. 2110–27.
     [Google Scholar]
  59. Wu, Linwan,, Dodoo, Naa Amponsah,, Wen, Taylor Jing, and Ke, Li. ( 2022;), ‘ Understanding Twitter conversations about artificial intelligence in advertising based natural language processing. ’, International Journal of Advertising, 41:4, pp. 685–702.
     [Google Scholar]
  60. Wu, Linwan, and Wen, Taylor Jing. ( 2021;), ‘ Understanding AI advertising from the consumer perspective: What factors determine consumer appreciation of AI-created advertisements?. ’, Journal of Advertising Research, online first, https://www.journalofadvertisingresearch.com/content/early/2021/03/25/JAR-2021-004.article-info. Accessed 26 January 2023.
     [Google Scholar]
  61. Yang, Guangwei,, Liu, Yan, and Zhang, Xiaoyong. ( 2017;), ‘ Research on the application of technologies in smart ad design. ’, Art, Science and Technology, 30:5, p. 43.
     [Google Scholar]
  62. Yu, Yongqi. ( 2021;), ‘ The role and influence of artificial intelligence on advertising industry. ’, in Proceedings of the 2021 International Conference on Social Development and Media Communication, Sanya, China, 26–28 November, Sanya:: Atlantis Press;, pp. 190–94.
     [Google Scholar]
  63. Zhou, Kai-Qing, and Nabus, Hatem. ( 2023;), ‘ The ethical implications of DALL-E: Opportunities and challenges. ’, Mesopotamian Journal of Computer Science, online first, pp. 17–23.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1386/jpm_00003_1
Loading
The future of advertising campaigns: The role of AI-generated images in advertising creative
Journal of Pervasive Media 8, 29 (2023); https://doi.org/10.1386/jpm_00003_1
/content/journals/10.1386/jpm_00003_1
/content/journals/10.1386/jpm_00003_1
Loading

Data & Media loading...

  • Article Type: Article
Keyword(s): advert production; aesthetics; artificial intelligence; computational creativity; DALL-E 2; technology
This is a required field
Please enter a valid email address
Approval was a success
Invalid data
An error occurred
Approval was partially successful, following selected items could not be processed due to error