{"id":18889,"date":"2026-08-06T12:04:00","date_gmt":"2026-08-06T16:04:00","guid":{"rendered":"https:\/\/advertisingweek.com\/aw360\/?p=18889"},"modified":"2026-08-06T14:35:33","modified_gmt":"2026-08-06T18:35:33","slug":"what-ai-visibility-really-looks-like-with-caroline-giegerich-vp-of-ai-at-iab","status":"publish","type":"post","link":"https:\/\/advertisingweek.com\/aw360\/news\/what-ai-visibility-really-looks-like-with-caroline-giegerich-vp-of-ai-at-iab\/18889\/","title":{"rendered":"What AI Visibility Really Looks Like with Caroline Giegerich, VP of AI at IAB"},"content":{"rendered":"<\/p>\n\n\n

Caroline Giegerich<\/a>, Vice President of AI at the IAB<\/a>, joins AI: Machine Made Marketing to discuss how the advertising industry is responding to AI through research, collaboration, and practical guidance. She explains how the IAB gathers input from leaders across brands, publishers, agencies, platforms, and ad tech to develop new frameworks for measuring AI visibility and guidance around AI disclosure.<\/p>\n\n\n\n

The conversation also explores how AI is changing the way brands and publishers are discovered, why visibility in AI requires new ways of thinking about measurement, and what marketers should be watching as AI agents become a larger part of how people and machines interact with the web.<\/p>\n\n\n\n

Five Key Takeaways<\/h3>\n\n\n\n

1. AI visibility needs its own measurement framework<\/strong><\/p>\n\n\n\n

Traditional search metrics don’t translate well to AI platforms. The IAB has developed new frameworks to help marketers understand how brands and publishers appear in AI generated responses, giving the industry a more consistent way to measure visibility. Latest<\/p>\n\n\n\n

2. The Four Ps provide a practical way to measure AI visibility<\/strong><\/p>\n\n\n\n

Rather than asking whether a brand simply appears in an AI response, the IAB recommends evaluating Presence, Prominence, Portrayal, and Persuasion<\/strong>. Together, these four dimensions help marketers understand not only if they are visible, but how they are represented and whether that visibility drives meaningful action.<\/p>\n\n\n\n

3. AI disclosure should focus on preventing deception<\/strong><\/p>\n\n\n\n

As AI generated creative becomes more common, Caroline explains that disclosure should be based on whether consumers could reasonably be misled. The discussion explores where labeling makes sense today and how emerging regulations are beginning to shape industry practices.<\/p>\n\n\n\n

4. Brands and publishers face different AI challenges<\/strong><\/p>\n\n\n\n

Both brands and publishers are adapting to AI driven discovery, but for different reasons. Brands are focused on influencing purchase decisions, while publishers are working to understand how AI changes traffic, attribution, and the value of their content.<\/p>\n\n\n\n

5. AI agents are creating the next measurement challenge<\/strong><\/p>\n\n\n\n

As AI agents account for more activity on the web, marketers will need to rethink long standing assumptions about advertising, engagement, and what meaningful attention looks like in an increasingly agent driven environment.<\/p>\n\n\n\n

AI is changing quickly, but as Caroline points out, marketers don’t have to navigate it alone. By bringing together expertise from across the advertising industry, the IAB is helping turn emerging questions around AI visibility, disclosure, and measurement into practical frameworks marketers can use today. Read the framework PDF here<\/a> on IAB’s site. <\/p>\n\n\n\n