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Is generative AI a game-changer for marketing?

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You may have noticed that websites like Amazon and TripAdvisor now use generative AI to summarize customer reviews, providing quick insights from countless user comments (see examples here and the image below).

Example of TripAdvisor review created by AI
Source: TripAdvisor

 

Imagine scrolling through a travel website and seeing AI-generated summaries that quickly highlight the pros and cons of hotels – like the example above. Now, consider this: What if every review you read – from product pages to social media – was also written by AI? For instance, an AI might generate glowing comments about a restaurant’s ambiance or a gadget’s sleek design, all without a single real customer trying them. Could you tell the difference? Would these reviews still influence your decisions? Our research explores these very questions.

Our study examines these questions in depth, uncovering how generative AI not only enhances emotional engagement but also challenges the boundaries of human communication skills in marketing. These developments have far-reaching implications for marketers, businesses, and policymakers as they navigate the opportunities and challenges posed by AI-generated content.

AI vs. Human Marketing Content: Who Does It Better?

Our study compared AI-generated marketing narratives about consumer experiences with sensorial products such as whisky or chocolate with those crafted by human experts. The results were surprising: in unbranded social media content, AI often matched or even surpassed human copywriters in engaging audiences. Evaluators frequently found AI-generated content emotionally appealing and, in some cases, more effective than human-created content. For instance, ChatGPT 4 demonstrated higher levels of perceived lexical diversity in its narratives, leading to stronger purchase intentions among consumers exposed to the content. This finding underscores AI’s ability to replicate certain writing skills that are typically associated with human expertise.

However, while AI excelled in emotional engagement, it fell short in other areas. Human experts were more adept at weaving nuanced sensory details into their content – elements that resonate deeply with consumers by appealing to their embodied cognition. This means human-created narratives were better at evoking vivid, multisensory experiences. For example, in our study, AI-generated reviews described a whisky tasting experience as simply “a pleasant and smooth drink” while human reviewers created a more vivid narrative: “the rich amber liquid delivered a warming blend of smoky oak, subtle vanilla, and a lingering note of caramel, evoking memories of a cozy evening by the fire”. These differences highlight how human storytelling retains an edge in creating emotionally resonant, sensory-rich narratives.

Human- vs AI-generated marketing narratives
Graph by the authors

 

Building on our research’s implications, future AI applications in marketing could focus on routine tasks like summarizing product attributes or creating social media posts to leverage its speed and scalability. However, for complex tasks such as crafting brand stories or handling nuanced queries, human input will likely remain essential.

A Double-Edged Sword: AI’s Strengths and Risks

Generative AI offers significant advantages for marketers, particularly in streamlining content production. By enabling businesses to create large volumes of tailored content efficiently, AI helps save time and costs while maintaining high levels of engagement. For example, our study showed that AI-generated product descriptions often led to higher purchase intent compared to human-written ones. Moreover, generative AI’s flexibility in adapting tone and style across diverse marketing channels has proven effective, though it necessitates careful oversight.

However, AI comes with notable risks. One major challenge is the generation of “hallucinations” – misleading or entirely inaccurate information presented confidently as fact. In one test, ChatGPT fabricated plausible but false product details, raising critical concerns about consumer trust. This underscores the importance of human validation to ensure content accuracy and reliability. Without appropriate oversight, businesses risk damaging their reputations and eroding consumer confidence.

Additionally, while AI excels in scalability and consistency, it often lacks the cultural sensitivity and contextual understanding that human creators bring. For instance, AI can misinterpret idiomatic expressions or cultural nuances, potentially leading to miscommunication or unintended offense in global campaigns. Consider a scenario where an AI misinterprets a colloquial phrase during a marketing campaign, leading to awkward or even offensive messaging. Such missteps can have lasting impacts on brand perception, particularly in highly competitive markets.

Why This Matters

As generative AI becomes more prevalent, businesses must weigh its benefits against its limitations. While AI can amplify creativity and engagement, it cannot fully replace human judgment. Marketers need to ensure a balance, using AI to complement—not replace—human expertise. This is particularly important in industries where trust, cultural nuance, and ethical considerations are paramount.

Generative AI also raises questions about authenticity. Consumers increasingly value genuine connections with brands, and over-reliance on AI-generated content could risk undermining that trust. For example, overly polished AI-crafted narratives might lack the imperfections or idiosyncrasies that make human storytelling relatable. Striking the right balance will be key to maintaining credibility and fostering long-term relationships with consumers.

What It Means for Policymakers

Generative AI’s ability to produce persuasive and engaging content raises important questions for policymakers. Regulations need to address transparency in AI-generated communications, ensuring that consumers can distinguish between AI-created and human-created content. For example, labeling requirements could mandate disclosure when reviews, product descriptions, or social media content are generated by AI. This transparency will be critical in building and maintaining consumer trust.

Policymakers also need to consider safeguards against misinformation. AI tools are capable of producing content that appears credible but lacks factual accuracy, which can erode consumer trust and distort markets. Developing standards for ethical AI deployment in marketing can help mitigate these risks. One potential solution could involve collaborative frameworks between governments, tech companies, and industry leaders to establish best practices.

Finally, there is the issue of accountability. Who is responsible when AI-generated content misleads consumers or causes harm? Clear guidelines on accountability will be critical as AI becomes more prevalent in public-facing marketing communications. Policymakers must also address how AI usage intersects with data privacy laws, especially when algorithms rely on vast amounts of consumer data to create personalized content.

Practical Insights for Marketers

To maximize the potential of generative AI while mitigating risks, marketers should consider the following strategies:

  • Combine Strengths: Use AI for efficiency and scalability while relying on humans for creativity, emotional intelligence, and cultural awareness.
  • Implement Oversight: Establish review processes to catch inaccuracies or hallucinations in AI-generated content.
  • Leverage Data: Train AI models on industry-specific data to improve relevance and accuracy.
  • Test Responsibly: Regularly test AI outputs against human-created benchmarks to ensure quality and effectiveness.
  • Focus on Authenticity: Blend AI’s capabilities with genuine human input to maintain credibility and trust in consumer interactions.

By adopting these practices, businesses can harness the power of AI to enhance their marketing efforts without compromising on authenticity or trust.

This article is based on the academic publication:

Wen, Y., & Laporte, S. (2024). EXPRESS: Experiential Narratives in Marketing: A Comparison of Generative AI and Human Content. Journal of Public Policy & Marketing, Forthcoming. https://doi.org/10.1177/07439156241297973