A new study from Victorious reveals how AI Overviews and AI Mode pull and present sources in notably different ways, with only modest overlap between them. This means visibility on one surface does not reliably predict visibility on the other, posing a clear challenge for marketers aiming to optimize across Google's AI-enabled search experiences.
AI Overviews versus AI Mode: What the findings show
When users encounter AI Overviews, Google curates a concise set of answers drawn from a selective group of sources. In contrast, AI Mode generates full, on-demand responses that assemble information from a wider array of sources. The study’s core takeaway is that these two interfaces reward different sources and different retrieval strategies, suggesting separate optimization playbooks for each surface.
Context matters as Google deepens AI integration into search. AI Overviews tend to surface vetted, summarized answers, while AI Mode builds its responses from a broader mix of references. Since these features launched, Google has reported a more than 10% uptick in overall Google usage, underscoring the growing influence of AI-driven search experiences. But this raises a key question: does ranking visibility in an AI Overview transfer to AI Mode, or do the two surfaces highlight distinct sources?
Victorious, an SEO agency focused on AI-driven discovery, examined more than 1,500 real-world queries for insights. The resulting whitepaper analyzes how often the two experiences cite the same domains and how much overlap exists in the sources they pull from. The goal was to provide marketers with a data-backed foundation for measuring visibility in AI-powered search and to understand whether common SEO practices apply equally to both surfaces.
How the study was done
The research looked at 1,540 queries covering informational and transactional intents. For each query, every domain cited by Google’s AI Overviews and by AI Mode was collected and compared. Three metrics emerged from the comparisons:
- The average number of unique URLs cited per experience
- The share of AI Overview citations that also appeared in AI Mode
- Query-level overlap ratios indicating how closely the two experiences align
Together, these measures reveal whether Google relies on a shared source pool across surfaces or uses different citations depending on the user experience.
Key patterns from the data
Victorious’ analysis identified four consistent patterns:
Overlap is partial and limited. On average, only about 30–35% of AI Overview URLs also show up in AI Mode, meaning roughly two-thirds of AI Overviews’ citations don’t carry over. For marketers, this means ranking or visibility in one surface doesn’t guarantee the same in the other.
Domain carryover is limited. A deeper dive shows 77% of all unique domains appear in only one experience, while just 23% appear in both. This implies the two surfaces often reward different authoritative sources.
AI Mode draws from a broader set of sources. On a per-query basis, AI Mode cites roughly 9 domains, whereas AI Overviews cite about 7.7 domains. That indicates AI Mode builds responses from a wider reference pool, while AI Overviews stay more curated.
Citations diverge on every query. Even when overlap is strong, the exact lists of sources do not match perfectly, reinforcing that AI Overviews and AI Mode follow distinct retrieval patterns.
Implications for SEO and content strategy
These differences suggest a few practical shifts for content optimization:
- Broaden measurement beyond rankings and traffic. Track how often content is cited across AI Overviews and AI Mode as a core visibility metric.
- Treat the two surfaces separately in reporting. Because visibility in one does not guarantee visibility in the other, provide distinct performance analyses for AI Overviews and AI Mode.
Two hypotheses worth testing in practice include:
- AI Overviews may favor more comprehensive, well-structured pages since they cite fewer sources.
- AI Mode may prefer concise, reference-friendly content due to its broader sourcing.
A useful approach is to monitor how often a brand is mentioned across both surfaces. This cross-surface visibility metric can help brands adapt in real time as Google’s AI-powered search evolves. Those who establish a disciplined, multi-surface tracking framework early will be better positioned to identify patterns and respond before competitors treat AI search as a mysterious black box.
Author and context
Enrique Jose Tabuena serves as DesignRush’s Senior Editor, bringing over a decade of experience in content strategy, creative copy, and SEO. His work focuses on bridging brands and audiences through strategic storytelling and innovative marketing techniques.
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