Marketers Must Get Better at Training AI for On-Brand Content Creation

Seventy-seven percent of marketers explore GenAI, but only 44% realize significant benefits, indicating that challenges remain in harnessing this technology effectively, according to a survey by Gartner. 

The Gartner survey of 418 marketers from July through September 2024 found that creative tool providers offer numerous ways for CMOs and their teams to customize content generators to produce branded content, but gaps remain in their ability to generate on-brand, commercially publishable media at scale.

We spoke with Andrew Frank, Distinguished VP Analyst, in the Gartner Marketing practice to provide actionable insights for marketing leaders looking to train GenAI models to adhere to brand guidelines and leverage the technology for scalable, personalized and on-brand content.

Journalists who would like to speak with Andrew regarding this topic can contact Elizabeth.Bishop@Gartner.com. Members of the media can reference this material in articles with proper attribution to Gartner.

A: AI agents can significantly enhance the efficiency and creativity of marketing teams by automating repetitive tasks and enabling the rapid generation of personalized content at scale. These agents can be trained to conform with brand guidelines and consumer preferences, allowing them to produce tailored content that resonates with specific audience segments. 

By leveraging AI agents, marketing teams can quickly assemble and organize content for various channels, freeing up human creatives to focus on higher-level strategic thinking and ideation. This not only accelerates the content creation process but also allows for more dynamic and responsive marketing strategies because AI agents can adapt content based on consumer interactions and feedback.

However, there are potential limitations to relying on AI agents. While these tools can efficiently handle large volumes of content, they may struggle with capturing the nuanced emotional and cultural aspects that human creatives naturally incorporate into their work. 

This can lead to content that, while technically proficient, lacks the depth and authenticity that consumers expect from a brand. Additionally, AI agents require substantial initial setup and ongoing oversight to ensure they remain aligned with evolving brand strategies and ethical standards. 

Without careful management, there is a risk of over-reliance on AI, which could result in a disconnect with the brand's unique voice, goals and values. Therefore, while AI agents offer powerful capabilities, they should be integrated as complementary tools within a broader creative strategy that values human insight and oversight.

A: To address consumer perception and authenticity challenges when using GenAI for content creation, organizations should prioritize transparency and align AI usage with their brand values. Clearly disclosing AI-generated content builds consumer trust and demonstrates ethical practices. Brands can use AI for efficiency and personalization while ensuring that final outputs are refined by human creatives to maintain the brand's personality and authenticity.

Engaging in regular audience feedback loops helps brands understand consumer perceptions and adjust their creative processes accordingly. Additionally, implementing oversight mechanisms to monitor and mitigate biases in AI models ensures diverse and inclusive representations. 

By focusing on transparency, human oversight, audience engagement, and bias mitigation, organizations can effectively manage consumer perceptions and maintain trust in their AI-driven content strategies.

A: CMOs must approach the customization of GenAI models with a holistic view, weighing the pros and cons across several dimensions. 

• Ethically, it is crucial to use models trained on licensed or public-domain datasets for commercial content to ensure creators are recognized and rewarded. 

• Aesthetically, detailed brand guidelines design principles must be consistently applied to ensure the AI-generated content aligns with brand standards and sensibilities.

• Technically, CMOs should choose the right model type—whether end-user application models, dedicated media models, enterprise cloud-provider models, or open-source community models—based on their organization's specific needs and resources.

• Financially, while GenAI can reduce traditional production costs, the computational expenses can be high, necessitating careful cost management and possibly leveraging enterprise licensing arrangements. 

By understanding these trade-offs and collaborating with IT, legal, and creative teams, CMOs can make informed decisions that align with their brand's strategic goals.

Gartner clients can learn more in the report: How to Teach AI About Your Brand.