ChatGPT is seemingly everywhere, with everyone from toddlers to their grandparents asking it questions. Generative AI, specifically, has captured the imagination of advertisers and consumers alike thanks to the impressive performance of large language models (LLMs) and image generators in recent months. While advertisers and publishers are eager to see how much these tools will change how they do business, the reality is that AI has been impacting their jobs for a while now, and this technology is nothing new.
To break this down, it’s helpful to put AI into two buckets: classic AI and generative AI. Classic AI is technology like predictive analytics and optimization, which have been part of marketing initiatives for years. Generative AI can be thought of as chatbots and platforms like ChatGPT and Bing that are generating massive amounts of hype in the news cycle. Predictive AI has been used to optimize measurement, attribution and targeting, as 48% of advertisers are using it for campaign optimization and 46% are using it for audience modeling. On the other hand, advertisers are starting to experiment with generative AI for creative output or to help make business processes more efficient or develop more product offerings.
The reason why generative AI has been getting the hype it has been is largely because there’s so much uncertainty about it and the current possibilities are endless. While valuable, predictive AI is already a known use case, helping with problems like cookie deprecation and optimizing processes. Our insights show that 37% of advertisers are currently using AI and 53% plan to use it within the next six months.
Generative AI is entirely new, and advertisers are intrigued by the possibilities that it can unlock. We’re in the hype cycle right now, however, it’s important to separate the hype from what we know about it and how it works. It’s easy to get caught up in the possibilities of generative AI, but advertisers must keep their hype in check. This starts with understanding where AI currently is and what advertisers want out of it. Only from there can they unlock the possibilities this technology can provide.
Nicole Perrin is SVP Business Intelligence at Advertiser Perceptions
