Artificial intelligence is evolving quickly, with products like ChatGPT being estimated to have reached 100 million active users in just two months. For comparison, another recent growth curve was TikTok, which took nine months to reach the same volume. This rapid growth and use in daily and business life is resulting in terminology and concepts being partially defined or incompletely understood. It’s with this in mind that Tech Lab’s Board of Directors decided to work together on a primer, to help lay foundations on AI in Advertising.
The Board of Directors decided to create a subcommittee to produce this Primer, which features significant contributions from, Michael Palmer, GroupM, Trey Griffin, Raptive, Aaron Brown, Madhive, David Caragliano, Google, Rebecca Gleason, Meta, and Jordan Rogers-Smith, Meta.
The document aims to set out a baseline understanding about artificial intelligence to support discussions and documentation about how this technology will affect advertising in the future.
In the business of advertising, two activities are fundamental:
- the scientific pursuit of optimization, and
- the art of creating persuasive media
Artificial Intelligence intersects remarkably with both domains. Intelligence applied to business automates processes, heralding a future where the labor-intensive aspects of digital advertising are significantly reduced. AI not only holds the potential to revolutionize the way we derive insights for marketers and measure performance in a privacy-safe way, but it also paves the way for agencies to explore new creative avenues, and is poised to empower publishers with the ability to craft deeply personalized media experiences.
The primer aims to distinguish between the LLMs/foundation models and ad products that are powered by those models. It also focuses on the use cases for the models themselves. We also explore how these models are currently being used for advertising use cases.
The primer doesn’t make big predictions about the future of AI powered advertising, with the rate of evolution in AI, we didn’t want it to be obsolete as soon as it was published. Instead, we focus on the tools, the current use cases and what we’ve seen so far. We hope the industry finds this a fruitful place to start. In all standards work, we’ve found it’s important to have a common understanding of the current landscape before diving forward into what’s next.
If you have proposals about what should be in the next edition of the Primer please email support@dev.iabtechlab.com