Generative AI’s Genius: Why Chat GPT is Only the Beginning
As a company focused on providing clients with deep learning to predict consumer behavior, we were honored to gather top advertising and marketing executives at “Neural Networking” in New York City last week, an exclusive event focused on the latest breakthroughs in generative AI and the rapid advancements this technology has enabled for advertisers. Over the course of the evening, we discussed the boundless potential of generative AI, and what’s next on the horizon.
The panel, moderated by Pam Zucker, Chief Strategy Officer at IAB, welcomed Daniel Thomann, VP and Group Media Director at Mediahub Global, Gabrielle Scarpa, Director of Integrated Investment at UM Worldwide, and myself as we deconstructed generative AI’s potential. Below are the key takeaways.
The Benefits of Generative AI
Artificial intelligence has been around for decades, whether many realize it or not. Remember Clippy? The intelligent Office assistant featured in the early days of Microsoft Word? This use case of AI was created to help users acclimate to the program.
In essence, generative AI is helping to achieve the same thing: helping users source information in a matter of seconds. Apply this to the day-to-day of advertisers and marketers, and time is immediately available to focus on the analysis and creative components (aka the best parts).
Where the Opportunity Lies
Advertisers are constantly seeking innovation in terms of reaching consumers, digitally. For example, personalization can make or break an ad experience when building brand affinity and influencing purchase behavior. AI can strengthen that approach in regard to creative optimization. What is the best creative to serve alongside an ad, but also taking into account the best creative to serve to that specific person, alongside the right content, and the difference of how it might resonate with that person at 9am versus 5pm.
Bias and Limitations in AI
AI shouldn’t be about replacing people, but enabling people. A human element is still required at the beginning and end. AI requires an input or a prompt, and then a human needs to put the output into action. The human element will always be needed to level up how artificial intelligence is being used and applied.
Especially when we consider bias that can influence results or the information derived from AI. Already today we have many tools available to help recognize and remove bias in artificial intelligence training models. Due to limited time and resources, we can sometimes be biased in marketing. For example, marketers at a cosmetics brand may target women, ages 18-34 because this is their core demographic, but will neglect demographics outside of their core customer base due to the complexity in identifying them. Artificial intelligence can help recognize who is likely to purchase this product regardless of age or gender.
We are at the precipice of artificial intelligence supporting various jobs across industries, creating efficiencies, and unleashing endless opportunities. Personally, I could not be more excited for the future of AI (self-driving cars, anyone?), particularly the countless advancements in advertising and marketing. At last, marketers are entering a new golden age: one where unprecedented personalization, optimized marketing budget and ad expenditure, higher levels of engagement with the right audiences, and boundless ideation is within our grasp.