When media agencies delve into the realm of generative AI strategies, their focus extends beyond mere content creation to encompass the broader implications for their data strategies.
At the recent Digiday Media Buying Summit in Nashville, media agencies explored the practical applications of AI, particularly in optimizing existing media channels. During her presentation at the summit, Amanda Moore, the chief growth officer at iProspect, a Dentsu-owned agency, highlighted the utilization of publicly available data such as weather information to enhance message personalization without compromising individual privacy.
Moore emphasized the shift towards practical AI implementations this year, distinguishing it from purely generative AI. She underscored the importance of testing and learning from specific instances to leverage data effectively while mitigating inherent biases and potential errors.
IPG took initial steps by providing its 13,000 employees with a tailored version of ChatGPT, fostering a better understanding of generative AI even before engaging with clients.
Graham Wilkinson, the chief innovation officer at Kinesso, an IPG subsidiary, stressed the significance of organizing a brand’s documentation as a foundational element in crafting an AI strategy. Prior to delving into AI outputs, Wilkinson advised brands to establish a cohesive brand strategy and solidify their data architecture. Understanding elements such as tone of voice, brand hierarchy, target audience, and brand safety standards is crucial in laying the groundwork for an effective AI strategy.
Media agencies are exploring how generative AI can enhance audience insights. For instance, some have developed tools that leverage first-party data to construct synthetic audiences for targeted inquiries. However, the development of proprietary AI tools in-house has proven resource-intensive for some agencies, requiring significant time and manpower.
While some industry executives express concerns about the authenticity of AI-generated audio content, citing potential drawbacks in audio ad personalization, others have witnessed positive outcomes. Studies, such as one conducted by Veritonic, have shown that AI-generated audio ads can significantly impact brand favorability and purchase intent, underscoring the potential benefits of personalized audio content.
Amidst the advancements in AI technology, agencies remain vigilant about issues of diversity, representation, and algorithmic bias. Stakeholders emphasize the importance of accurate representation in AI applications, highlighting the need for cultural sensitivity and awareness in data processing and model development.
In conclusion, as the landscape of AI continues to evolve, media agencies are navigating the complexities of integrating AI technologies responsibly and ethically to drive innovation while addressing challenges related to cultural authenticity, diversity, and bias in advertising practices.
