Five key warnings for using GenAI in Marketing and Innovation

Companies are already using GenAI to enhance creativity and increase efficiency in their marketing activities. For example, Coca-Cola has employed it to co-create a new flavor, Coca-Cola Sugar Y3000, presumably aligning with emerging consumer preferences.

However, the marketing literature has yet to fully explore GenAI’s impact, previously focusing mainly on traditional AI applications. But GenAI is far more sophisticated: it not only supports the automation of repetitive tasks but can generate new ideas and enrich innovation processes.

In a recent paper, we posed two key questions: How will GenAI change consumer behavior? And how can companies best leverage this technology to enhance innovation?

For our study, we conducted twenty in-depth interviews with managers from various sectors, including luxury, consumer goods, and insurance services. These conversations revealed a growing interest in using GenAI in business processes, with particular attention to its capacity to support innovation. However, managers also expressed concerns about potential long-term effects, such as diminishing human creativity.

GenAI has already proven capable of transforming traditionally creative sectors like advertising by providing new tools to tailor content to target audiences. Cadbury, for example, used a GenAI-produced video featuring a Bollywood star to encourage Indian customers to visit its stores. Unilever created its own generative AI tool to write ad copy for one of its shampoos, as reported in The Verge.

Managers find that GenAI can be useful across the four stages of innovation: development, testing, communication, and consumer engagement.

• In the development phase, companies are increasingly engaging consumers via co-creation or crowdsourcing platforms. GenAI can be used to create campaigns that get consumers involved in the creative process, allowing them to contribute ideas and preferences that AI can then fine-tune.

• In the testing phase, GenAI could partially replace human participants in market research, as GenAI models can replicate real consumer behavior to some extent, reducing the time and cost of tests.

• Communication has already been impacted by GenAI, as demonstrated by the examples above. The potential of this technology lies in creating large-scale automated content and generating persuasive, tailored messages. In other words, GenAI can help companies craft more compelling, targeted communications.

• Consumer engagement refers to a company’s ability to maintain an active, voluntary relationship with its clients, fostering continuous interaction. GenAI can engage consumers in creative activities like contests or co-creation platforms. Coca-Cola launched a platform called Real Magic, using GenAI to allow users to fashion original images. Even people with minimal design skills could participate, thanks to tools like DALL·E.

GenAI can significantly improve the efficiency of marketing and innovation processes. However, managers must carefully balance automation with human elements to prevent overreliance on GenAI, which could stifle employee creativity and curb authentic consumer engagement.

The main challenges for marketing and innovation leaders can be grouped into five categories:

1. Risk of creative conformity. This occurs when employees tend to align with AI-generated ideas instead of developing original, diverse solutions. If GenAI becomes the primary source of ideas, the danger is diminishing human creative input, which may limit long-term innovation.

2. Dependence on AI models. If companies overly rely on GenAI for idea and content generation, they may cut investment in developing their teams’ creative skills, potentially lowering their capacity for independent innovation.

3. Impact on consumer engagement. Using GenAI in related initiatives may reduce the creative effort required from consumers, making participation more accessible. However, this simplification could weaken the psychological ownership consumers develop for co-created products or experiences.

4. Transparency and brand perception issues. Companies must decide whether to inform consumers that ads or products were created with AI. In some cases, disclosure could negatively impact brand perception, especially if consumers view GenAI as a threat to authenticity in interactions with companies.

5. Errors and hallucinations. Another challenge involves the possibility of errors or inaccurate content generated by GenAI, a phenomenon known as “AI hallucinations.” This poses a risk for companies using GenAI extensively without adequate human oversight.

Paola Cillo, Gaia Rubera. “Generative AI in innovation and marketing processes: A roadmap of research opportunities.”  Journal of the Academy of Marketing Science (2024). DOI: https://doi.org/10.1007/s11747-024-01044-7.