Smart Advertising: AI Driven Innovation and Technological Disruption in the Advertising Ecosystem
DOI:
https://doi.org/10.4185/10.4185/RLCS-2022-1693Keywords:
artificial intelligence, advertising, programmatic, creativity, automation, deep fake, big dataAbstract
Introduction: The impact of artificial intelligence (AI) in media industries has received increasing attention in recent years. Research literature in this regard has focused on content production and distribution sectors, leaving advertising in a discreet background. This article aims to take the study of AI and advertising to the forefront, identifying the scope of current research on the subject and offering a map of the research trends, drawing them as a key vector of technology-based innovation in the media ecosystem. Methodology: In order to do so, a qualitative scoping review of the current research literature on AI and advertising has been developed, completed by the contribution of professional reports from the sector. Results and discussion: The existing literature points to the efficiency in large unstructured data sets processing, predictive / prescriptive analysis, natural language recognition and image recognition, as automation as the main AI innovation vectors. The disruptive impact of AI affects all phases of the advertising process: market research and analysis, creativity, media planning and buying, and effectiveness evaluation. Conclusions: Research tends to perpetuate the traditional structure of the advertising process and obviates the ecosystem dimension of innovation, which transforms actors and their relationships.
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References
Acquisti, A., Taylor, C., y Wagman, L. (2016). «The economics of privacy». Journal of Economic Literature, 54(2), 442-92. https://doi.org/10.1257/jel.54.2.442
Adform (2019) Fact or fiction? The threat of cookie Apocalypse. IAB Europe whitepaper. https://iabeurope.eu/wp-content/uploads/2019/11/Fact-or-Fiction-The-threat-of-a-Cookie-Apocalypse.pdf
Albinali, E. A. y Hamdan, A. (2020, November). The implementation of artificial intelligence in social media marketing and its impact on consumer behavior: evidence from Bahrain. International Conference on Business and Technology (pp. 767-774). Springer, Cham. https://doi.org/10.1007/978-3-030-69221-6_58
Ahn, J. B. (2020). A Study on Advertising Future Development Roadmap in the Fourth Industrial Revolution Era. International Journal of Internet, Broadcasting and Communication, 12(2), 66-76. https://doi.org/10.7236/IJIBC.2020.12.2.66
Ali, W. y Hassoun, M. (2019). Artificial intelligence and automated journalism: Contemporary challenges and new opportunities. International journal of media, journalism and mass communications, 5(1), 40-49. http://dx.doi.org/10.20431/2454-9479.0501004
Arvidsson, A. y Colleoni, E. (2012). Value in Informational Capitalism and on the Internet. The Information Society, 28(3), 135-150. https://doi.org/10.1080/01972243.2012.669449
Allam, S. (2016). The Impact of Artificial Intelligence on Innovation-An Exploratory Analysis. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3821173
Barker, A. (2020) “’Cookie Apocalypse’ forces profound changes in online advertising”, Financial Times, 02/26/2020 https://www.ft.com/content/169079b2-3ba1-11ea-b84f-a62c46f39bc2
Bradley, S. (2021). “Could AI product placement help brands break through the ad break?” The Drum, 05/05/2021. https://www.thedrum.com/news/2021/05/05/could-ai-product-placement-help-brands-break-through-the-ad-break
Buckley, D. (2021). Privacy enhancing technologies for trustworthy use of data. Centre for Data Ethics and Innovation, Reino Unido. https://cdei.blog.gov.uk/2021/02/09/privacy-enhancing-technologies-for-trustworthy-use-of-data/
Busch, O. (2019) Programmatic Advertising. The Successful Transformation to Automated, Data-Driven Marketing in Real-Time. Berlin, Springer.
Campbell, C., Plangger, K., Sands, S. y Kietzmann, J. (2021). Preparing for an era of deepfakes and AI-generated ads: A framework for understanding responses to manipulated advertising. Journal of Advertising, 1-17. https://doi.org/10.1080/00913367.2021.1909515
Carrillo-Durán, M. V. y Rodríguez-Silgado, A. (2018). El ecosistema programático. La nueva publicidad digital que conecta datos con personas. El profesional de la información, 27(1), 195-201. https://doi.org/10.3145/epi.2018.ene.18
Chen, G., Xie, P., Dong, J. y Wang, T. (2019). Understanding programmatic creative: The role of AI. Journal of Advertising, 48(4), 347-355. https://doi.org/10.1080/00913367.2019.1654421
Christiansen, L. (2011). Personal privacy and internet marketing: an impossible conflict or a marriage made in heaven?. Business horizons, v. 54, n. 6, pp. 509-514.
Cillo, V., Petruzzelli, A. M., Ardito, L. y Del Giudice, M. (2019). Understanding sustainable innovation: A systematic literature review. Corporate Social Responsibility and Environmental Management, 26(5), 1012-1025. https://doi.org/10.1002/csr.1783
Codina, Lluís (2020). Revisiones sistematizadas en Ciencias Humanas y Sociales. 3: Análisis y Síntesis de la información cualitativa. En: Lopezosa C., Díaz-Noci J., Codina L. (Eds.) Methodos Anuario de Métodos de Investigación en Comunicación Social, 1. Barcelona: Universitat Pompeu Fabra; 2020. p. 73-87. https://doi.org/10.31009/methodos.2020.i01.07
Duan, C., & Yang, H. (2018). Data, Algorithmic Model, and Decision-Making: The Development of Computational Advertising. Journalism Bimonthly, 2018(1), 128-136. https://en.cnki.com.cn/Article_en/CJFDTotal-XWDX201801017.htm
Enache, M. C. (2020). AI for Advertising. Annals of the University Dunarea de Jos of Galati: Fascicle: I, Economics & Applied Informatics, 26(1). https://doi.org/10.35219/eai1584040978
EU (2021). The Digital Services Act Package. https://digital-strategy.ec.europa.eu/en/policies/digital-services-act-package
Grant, Maria J. y Booth, Andrew (2009). A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26, pp.91–108. https://doi.org/10.1111/j.1471-1842.2009.00848.x
Hancock, J. T., Naaman, M. y Levy, K. (2020). AI-mediated communication: definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89-100. https://doi.org/10.1093/jcmc/zmz022
Helberger, N., Huh, J., Milne, G., Strycharz, J. y Sundaram, H. (2020). Macro and exogenous factors in computational advertising: Key issues and new research directions. Journal of Advertising, 49(4), 377-393. https://doi.org/10.1080/00913367.2020.1811179
Hill, R. K. (2016). What an algorithm is. Philosophy & Technology, 29(1), 35-59. https://doi.org/10.1007/s13347-014-0184-5
Huang, M. H. y Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30-50. https://doi.org/10.1007/s11747-020-00749-9
Houle, O. y Mauss, J.C. (2021) The Impact of Cookie Apocalypse on Digital Media. Ads. https://www.adviso.ca/en/blog/guides-en/attribute-measure-retarget/
ICO (2019). Update Report into Adtech and Real Time Bidding. June, 20, 2019. https://ico.org.uk/media/about-the-ico/documents/2615156/adtech-real-time-bidding-report-201906-dl191220.pdf
Kietzmann, J., Paschen, J. y Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263-267. https://doi.org/10.2501/JAR-2018-035
Koren, Y., Somekh, O., Shahar, A., Itzhaki, A., Cohen, T., Krasteva, M. y Shadi, T. (2020). Dynamic Creative Optimization in Verizon Media Native Advertising. En: 2020 IEEE International Conference on Big Data (Big Data) (pp. 1654-1662). IEEE. https://doi.org/10.1109/BigData50022.2020.9378251
Kumar, V., & Shaphali G. (2016). Conceptualizing the Evolution and Future of Advertising, Journal of Advertising, 45 (3), 302–17. https://doi.org/10.1080/00913367.2016.1199335
Kumar, V., Rajan, B., Venkatesan, R., y Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135-155. https://doi.org/10.1177/0008125619859317
Lee, H. y Cho, C. H. (2020). Digital advertising: present and future prospects. International Journal of Advertising, 39(3), 332-341. https://doi.org/10.1080/02650487.2019.1642015
Lee, J., Suh, T., Roy, D. y Baucus, M. (2019). Emerging technology and business model innovation: the case of artificial intelligence. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 44. https://doi.org/10.3390/joitmc5030044
Li, H. (2019). Special section introduction: Artificial intelligence and advertising. Journal of advertising, 48(4), 333-337. https://doi.org/10.1080/00913367.2019.1654947
Liu, X. (2019), A big data approach to examining social bots on Twitter. Journal of Services Marketing, 33 (4), 369-379. https://doi.org/10.1108/JSM-02-2018-0049
Malthouse, E. C. y Li, H. (2017) Opportunities for and Pitfalls of Using Big Data in Advertising Research, Journal of Advertising, 46:2, 227-235, https://doi.org/10.1080/00913367.2017.1299653
Malthouse, E. C., Maslowska, E., y Franks, J. U. (2018). Understanding programmatic TV advertising. International Journal of Advertising, 37(5), 769-784. https://doi.org/10.1080/02650487.2018.1461733
Manfredi, J. L. y Ufarte, M. J. (2020). Inteligencia artificial y periodismo: una herramienta contra la desinformación. Revista CIDOB d'Afers Internacionals, 49-72. https://doi.org/10.24241/rcai.2020.124.1.49
Martínez, I. J., Aguado, J. M. y Boeykens, Y. (2017). Implicaciones éticas de la automatización de la publicidad digital: caso de la publicidad programática en España. Profesional de la Información, 26(2), 201-210. http://www.elprofesionaldelainformacion.com/contenidos/2017/mar/06.pdf
Martínez, I.J. y Aguado, J.M. (2019). El impacto de la tecnología digital en el sector publicitario. Universidad de Murcia. https://doi.org/10.5281/zenodo.3737948
Mittelstadt, B. D.; Allo, P.; Taddeo, M.; Wachter, S. y Floridi, L. (2016). «The ethics of algorithms: Mapping the debate». Big Data & Society, 3(2), 2053951716679679. https://doi.org/10.1177/2053951716679679
Napoli, P. M. (2014). Automated media: An institutional theory perspective on algorithmic media production and consumption. Communication Theory, 24(3), 340–360. https://doi.org/10.1111/comt.2014.24.issue-3
Qin, X. y Jiang, Z. (2019). The impact of AI on the advertising process: The Chinese experience. Journal of Advertising, 48(4), 338-346. https://doi.org/10.1080/00913367.2019.1652122
Palomo-Domínguez, I. (2021). Del mito a la viralidad. El caso de la campaña de Cruzcampo que resucitó a Lola Flores. aDResearch ESIC 26, e262. https://doi.org/10.7263/adresic-026-02
Pärssinen, M.; Kotila, M.; Cuevas, R.; Phansalkar, A. y Manner, J. (2018). Is Blockchain Ready to Revolutionize Online Advertising?. IEEE Access. pp. 1-1. https://doi.org/10.1109/ACCESS.2018.2872694
Paschen, U., Pitt, C. y Kietzmann, J. (2020). Artificial intelligence: Building blocks and an innovation typology. Business Horizons, 63(2), 147-155. https://doi.org/10.1016/j.bushor.2019.10.004
Rodgers, S (2021) Themed Issue Introduction: Promises and Perils of Artificial Intelligence and Advertising, Journal of Advertising, 50:1, 1-10, https://doi.org/10.1080/00913367.2020.1868233
Rodrigo-Martín, L., Rodrigo-Martín, I. y Muñoz-Sastre, D. (2021). Los Influencers Virtuales como herramienta publicitaria en la promoción de marcas y productos. Estudio de la actividad comercial de Lil Miquela. Revista Latina de Comunicación Social, (79), 69-90. https://doi.org/10.4185/RLCS-2021-1521
Shumanov, M., Cooper, H. y Ewing, M. (2021), "Using AI predicted personality to enhance advertising effectiveness", European Journal of Marketing, pre-print. https://doi.org/10.1108/EJM-12-2019-0941
Skiera, B. (2016), Data, Data, and Even More Data: Harvesting Insights from the Data Jungle, GfK Marketing Intelligence Review, 8 (2), 10–17. https://doi.org/10.1515/gfkmir-2016-0010
Song, M. (2019). A Study on Artificial Intelligence Based Business Models of Media Firms. International Journal of Advanced Smart Convergence, 8(2), 56-67. https://doi.org/10.7236/IJASC.2019.8.2.56
Thomas, V. L. y Fowler, K. (2021). Close encounters of the AI kind: Use of AI influencers as Brand endorsers. Journal of Advertising, 50(1), 11-25. https://doi.org/10.1080/00913367.2020.1810595
Túñez-López, J. M., Toural-Bran, C. y Cacheiro-Requeijo, S. (2018). Uso de bots y algoritmos para automatizar la redacción de noticias: percepción y actitudes de los periodistas en España. El Profesional de la Información, 27(4), 750-758. https://doi.org/10.3145/epi.2018.jul.04
Vakratsas, D. y Wang, X. (2020). Artificial intelligence in advertising creativity. Journal of Advertising, 50(1), 39-51. https://doi.org/10.1080/00913367.2020.1843090
Watts, J. y Adriano, A. (2021). Uncovering the sources of machine-learning mistakes in advertising: Contextual bias in the evaluation of semantic relatedness. Journal of Advertising, 50(1), 26-38. https://doi.org/10.1080/00913367.2020.1821411
Yang, Y., Yang, Y. C., Jansen, B. J. y Lalmas, M. (2017). Computational advertising: A paradigm shift for advertising and marketing?. IEEE Intelligent Systems, 32(3), 3-6. https://doi.org/10.1109/MIS.2017.58
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