Lessons from academics on AI in Advertising

When Campaign Magazine asked their “2024 faces to watch” what was the biggest threat to the advertising industry today, it was no surprise the standard answer revolved around the use of AI (Campaign, 2024). In today’s landscape, with the rapid rollout and integration of Generative AI (GenAI) the debate has shifted from whether or not to use it to theorizing how best to use it. Integrating GenAI into the marketing communications mix is not just a choice but a necessity for staying competitive. To understand how to do this effectively, we can turn to the extensive research on GenAI in the advertising industry.

1. GenAI’s ability to enhance marketing communications by harnessing consumer insights for content personalization is unparalleled.

In essence, marketing communications is an “audience-centered activity” where the goal is to engage audiences and promote conversations (Fill & Turnbull, 2019: 8). All effective marketing communications should place the audience at the core with a constant effort to engage consumers at various touch points. In order to achieve this, various tools and methods have been used to engage audiences. Enter the latest tool, GenAI.

Academics have explored the rise of AI in the advertising industry across various disciplines, from computer science, mass communication, media, psychology, and sociology to technology (Ford, et al., 2023). What is particularly significant for marketing communication is that an unprecedented amount of consumer data can be collected using these technologies. The sheer amount of detail AI can gain from a brand’s audience changes the game for effective targeting and personalized ad creation.

Never before have audiences been so well understood. With collected consumer data encompassing everything from demographics and location to buying history, AI is a not-so-secret weapon for personalization (Baciu, 2024). No longer does an advertising agency or marketing department need to spend vast amounts of effort and money on focus groups and field research, for AI will tell you all you need to know about your consumers’ needs, wants, and evolving behavior. With individual user data collected by AI, the generative aspect comes into play, taking that data and using it to tailor marketing content to consumers in a way that resonates with their personal characteristics (Cui, et al., 2024). Doing so allows brands to engage with consumers in their unique language, cultivating and reinforcing connections with the brand (Cui, et al., 2024). Therefore, it is not only the way that AI can collect consumer data; it is also an added fact that GenAI is advanced enough to take that data and use it to continuously further brand awareness and engagement. Keller (2019) claims that the most successful marketing communications are the ones that focus not only on creating awareness but also on targeting and retaining connections with audiences. If one is using that as the objective of their marketing communications, it seems like a no-brainer to make the shift to multivocal branding and personalized content using Generative AI.

Spotify DJ

An exemplary integration of GenAI’s personalization capabilities is Spotify’s GenAI platform, which provides users with their own DJ.

With the ability to analyze user data like listening history and mood the platform generates personalized playlists and music recommendations that create a one-of-a-kind listening experience (Spotify, 2023). By incorporating GenAI, Spotify has seen an increase in user satisfaction and longer listening sessions, leading to a sustained competitive advantage against its competition (Cui, et al., 2024).

In summary, effective marketing communications rely on unlocking audience insights and using them to effectively target, segment, and engage audiences. GenAI has revolutionized this process by collecting individual consumer data and using it to deliver a personalized consumer experience. Brands are no longer static entities; they can now personalize communication with consumers, leading to a sustained competitive advantage in the market. With GenAI changing the game for automating and targeting consumers, it is evident that brands must embrace this transformation as soon as possible (Park, et al., 2023).

2. Consumer sentiment can be negatively affected by brands use of GenAI.

As market research by Gartner (2023) predicts that by 2025, nearly one-third of major brands will craft their marketing communications using GenAI, it is of the utmost importance that the impact on consumers is evaluated. This task should be approached with a sense of urgency, as it will undoubtedly have significant implications for the future success of marketing strategies.

The limitations of using GenAI in marketing communications have caught the attention of academics, for they carry crucial managerial implications. Brüns and Meißner's (2024) recent study drew on literature from algorithm aversion and brand authenticity to find that brands' use of GenAI content can induce negative follower reactions and behavior. The reasons underpinning adverse reactions can be attributed to a few key reasons: consumers’ lack of trust and privacy concerns, poor contextual awareness, and creativity dilution.

Examining GenAI’s increased content personalization abilities, it is crucial to keep in mind that personalization through computation does not immediately result in consumer acceptance (Yang, et al., 2017). Furthermore, regarding consumer trust as a critical component of successful marketing communications, Bleier and Eisenbeiss (2015) found that overly personalized content can result in negative perceptions of a product or brand with an immediate impact on trust. Today’s consumers are savvy and recognize that every personalized advertisement delivered to them reveals that their information has been tracked and exploited by the brand (Anand & Shachar, 2009). In this way advertising privacy has been a top concern for consumers (Ham, 2019) and continues to be so with the uptake of GenAI (Ford, et al., 2023). While increased personalization creates a new way for brands to target and engage audiences, there is a trade-off between reduced consumer trust and increased privacy concerns.

Another significant implication of using GenAI content is poor positioning. Brüns & Meißner (2024) underscore the need to develop better systems that prevent inappropriate placement of programmatically generated ads. Since GenAI technologies only compute off preexisting databases, there is no room for contextual nuance to come into play. With discrimination and biases associated with GenAI algorithms (Lambrecht & Tucker, 2013), there is a need for human intervention in GenAI content for particularly vulnerable audiences (Lee & Cho, 2019). GenAI has also been criticized for its inability to deal with semantic relatedness in the surrounding context. For example, Watts and Ardrino (2020) use the example of putting a beer advert next to an article about drunk driving. A human could identify and automatically process the error in that placement, whereas GenAI would not so easily pick up on the nuance of the two contexts.

Although Jakesch et al. (2023) found that GenAI is becoming so advanced that audiences can often no longer tell the difference between human-created content and GenAI language, that does not mean that GenAI is the most effective at creating compelling and top notch creative campaigns. As GenAI relies heavily on data-driven decisions, it means that human creativity is diluted (Vakratas & Wang, 2020). While it has been established that GenAI’s great power lies in its ability to gather consumer data and personalize content, none of that matters if there is no understanding of the inherent human experience that the best creative ads capture.

Brands with the highest brand equity often use experiential and emotional appeals in their marketing communication (Ashley & Tuten, 2014). Think of iconic examples like Red Bull’s displays of adrenaline-inducing extreme sports or John Lewis’s heartwarming Christmas adverts. In a study by Bakpayev et al. (2020), AI-generated ads with emotional and hedonic messages were found to be received with less enthusiasm. In the case that GenAI lacks the contextual awareness to convey such intimate and relatable content required for effective marketing communications, then there should be an adverse effect on consumers’ responses to brands’ use of GenAI (Brüns & Meißner, 2024). Following the logic presented in this section, it can be said that effective marketing communication requires the uniquely human creative mind and decision-making skills that GenAI lacks.

3. The path forward is a collaborative one with human impute and GenAI together.

Considering the dangers of GenAI affecting consumer trust, privacy, misplacement, and human relatability, the last lesson concerns the way forward. While the advantages of GenAI systems relate to enhancing marketing communications by leveraging consumer data, it is notable how GenAI lacks the nuanced human elements that shape consumer perceptions of effective marketing communications. To address this gap, striking the right balance between human input and using GenAI has been proposed.

Academic literature and industry examples demonstrate that striking a balance between the two is essential. There is a significant opportunity to be gained in the collaboration of human minds with GenAI, specifically for creative endeavors. While a study by Bakpayev et al. (2020) found that the cognitive and rational appeal of GenAI content with human input was received positively by consumers, Brüns and Meißner (2024) also found that the adverse reactions to GenAI can be reduced when it is used to assist humans in content generation. Additionally, it is imperative that generative content is consistently refined by human expertise to maintain the authenticity and relevance needed for effective marketing communications (Brüns & Meißner, 2024).

The call for striking a balance between the two has been heard beyond research and academics, with the advertising industry increasingly focusing attention on using AI in more creative ways. A advertising agency, BDDO, has incorporated GenAI into its creative briefing process by using it to brainstorm visuals for campaigns (Wright, 2023). Forrester Analyst Rowan Curran states that GenAI is ultimately “just part of the workflow,” clarifying GenAI will never generate entire campaigns without the attention of various senior markets and various tests (Hadero & O’Brien, 2023). It is becoming increasingly clear that the most effective strategy is a balanced integration of human creativity and GenAI’s capabilities.

While the call for human oversight with GenAI content generation is explicit, the way in which a collaborate and integrated process can be implemented requires further investigation.

This alludes to the need for further research to focus on creating applicable frameworks for doing so. As advertising and marketing communications embrace the abilities of GenAI to stay competitive in today’s market, managers and decision-makers must consider the latest consumer sentiment around GenAI to combat a lack of trust and transparent usage. In addition, this final lesson ensures that despite GenAI’s rapid rise, the importance of creative workers’ roles is reinforced as vital in this new environment. Moreover, there is a need for policymakers and lawmakers to play catch up with the industry’s rapid usage of GenAI to ensure grey areas such as copyrighting and discriminatory effects are accurately addressed (Spring & Lou, 2024).

To conclude, the literature on the use of Generative Artificial Intelligence in marketing communications highlights three essential lessons. First, GenAI’s unmatched ability to collect and analyze consumer data allows for highly personalized content, driving deeper brand awareness and audience engagement. Second, while exceling in automation and personalization, GenAI use can negatively impact consumers trust and privacy, result in poor advertisement placement often lack the necessary creative appeal. Finally, by taking into consideration the first and second lesson the final conclusion is that the most effective path forward lies in striking a balance between GenAI and human input. By leveraging GenAI’s data-driven capabilities alongside human creativity and intuition, organizations can craft impactful campaigns that resonate with audiences while maintaining authenticity and trust. This symbiotic relationship where technology enhances human creativity rather than replacing is the future of marketing communications.

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