AI has the power to transform industries, but it can also deepen existing inequalities, especially when it comes to gender and access to opportunity.

In this talk, Azahara Corrales will explore how large language models (LLMs) and AI-driven tools can unintentionally widen the gap between those who build AI, those who use it, and those excluded from its benefits. From biased training data to the lack of diversity among developers and users, we’ll examine how imbalance at every stage, design, data, and adoption, shapes who AI truly serves.

But this isn’t a story about fear; it’s about empowerment. Azahara Corrales will share how we can all play a role in closing this gap, by ensuring balanced, representative data, encouraging diverse teams to develop and deploy AI, and helping more people feel confident using it.

Because if the people building AI don’t reflect everyone, and the data feeding it doesn’t include everyone, then the future it creates won’t either.

Search no longer behaves as a single system. Ranking-based results and AI-driven answers surface different pages, cite different sources, and interpret authority in different ways.

In this talk, Tamara will present a data-backed study comparing large-scale datasets from traditional SERPs and AI-cited pages, showing where these systems align, where they diverge, and why the same SEO work can produce different outcomes—then translating the findings into practical guidance for authority, content, and link strategy in modern search.