Search is no longer just a page of links to scroll. Increasingly, it's a single answer chosen by an AI agent, and the brands that understand how that choice gets made are the ones that end up recommended. With AI agents now completing purchases inside closed ecosystems, without a human ever visiting a product page, brands that aren't built for machine-readable decision-making risk being absent from those workflows.

So what decides whether yours gets mentioned?

In this session, Jean Dejsuvan, Organic Performance Director at MG OMD, covers:

- Why LLMs don't behave like traditional search engines, and why "AI ranking" is the wrong mental model

- What actually makes a brand visible and citable to them, from structured data to consistency across the sources models read

- The common mistakes quietly draining brands' time and budget

If you own SEO, content or digital strategy, you'll leave knowing exactly where to focus before your competitors catch on.

AI search teams now have access to more data than ever: prompts, citations, competitors, mentions, sources, visibility scores, and more. But more data does not automatically mean better decisions.

This session will show how to build a practical AEO program around the data that actually matters, so your team knows what to track, what to ignore, and what to work on next.

Attendees will learn how to:
- Choose the right prompts and customer journeys to track
- Find where competitors are winning and why
- Separate useful signals from vanity metrics
- Prioritize the opportunities most likely to improve visibility
- Turn insights into an execution plan the team can actually run
- Use automation where it helps, without replacing human judgment

The goal is simple: less noise, better priorities, and a clearer path from AEO data to action.