AI Use Case Map Charts New Paths for Advertising and Marketing Innovation

Mapping the Future of AI in Advertising

Caroline Giegerich, vice president of AI and marketing innovation at the Interactive Advertising Bureau (IAB), has introduced an interactive tool aimed at helping advertisers and marketers make sense of artificial intelligence (AI) applications across advertising and marketing sectors.

The tool, named the AI in Advertising Use Case Map, resembles a periodic table by organizing AI use cases into categories that show their relationships and potential outcomes. This format helps marketers identify patterns and trends by combining different AI tasks within the advertising ecosystem.

How the AI Use Case Map Works

The map breaks down AI applications by company segment, including analytics, agencies, ad servers, and publishers. For example, publishers focus on how large language models (LLMs) are trained on their data to improve monetization and click-through rates. When these goals are not met, the map helps users understand the implications.

The map visually distinguishes between established and emerging AI uses. Hovering over each use case reveals detailed definitions and descriptions. Areas covered include:

• Measurement and analytics, such as performance forecasting and AI-driven attribution.
• Media buying and activation, including autonomous pacing, spend optimization, and rules-based media agents.
• Emerging technologies, indicated by a crystal ball icon, highlighting new AI applications.

Applying AI Effectively in Advertising

Giegerich advises marketers to start by identifying specific problems within their organizations. This targeted approach allows teams to prove AI’s return on investment and achieve faster, more effective results. For instance, a music company might focus on AI strategies that drive streaming numbers, directly impacting revenue.

Before joining IAB, Giegerich led AI and immersive media campaigns at Warner Music Group, working with artists and integrating technologies like generative AI, augmented reality, and near-field communication.

Challenges and Opportunities

The advertising industry often struggles with siloed teams—creative, media, and measurement functions operate separately. AI has the potential to bridge these gaps by integrating workflows and improving communication. For example, AI agents could surface relevant information across teams, helping align strategy, buying, and measurement efforts.

While the idea of including vendor lists for AI tools was discussed, maintaining neutrality and keeping such information current is challenging due to the fast pace of new companies entering the market.

Next Steps for Marketers

Marketers interested in applying AI can use this map as a starting point to explore practical solutions tailored to their specific roles and challenges. For those seeking to expand their AI skills in marketing, exploring specialized courses can provide deeper insights and hands-on experience.

Explore relevant AI courses and certifications for marketing professionals at Complete AI Training.