When users enter questions into AI search engines like ChatGPT or Google’s AI Mode, the responses come from a blend of several online sources, interpreted through AI’s training data and system prompts. This emerging competition for visibility in AI search results is known as Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO), signaling a shift that is replacing traditional SEO. Although GEO is still nascent with evolving best practices, its rapid growth attracts both media companies and marketers seeking to become authoritative answers or key input sources to AI-generated responses.
The rewards from traditional search rankings—such as direct traffic and conversions—contrast with GEO, where being cited serves more as reputation management and brand advertising. Publishers might block AI crawlers to avoid their content being used without direct benefit, but appearing in AI answers bolsters a publication’s authority. Losing out to competitors in AI citations means missing crucial brand exposure to relevant audiences.
A major challenge with AI answers is the propagation of incorrect or damaging information, which is harder to remedy than in traditional search. AI amalgamates content from multiple sources, including high-profile platforms like Wikipedia and Reddit, which wield growing influence through deals with AI companies. This new reputational risk is prompting increased attention from marketers.
Monetization in AI search is emerging, with ad placements starting to appear and companies experimenting with revenue-sharing models that credit original content contributors. While advertising in AI search raises skepticism about prioritizing monetization over user benefit, there is cautious optimism that this growth market may fairly distribute rewards among participants in the AI content ecosystem.
