AEO and GEO for food and beverage brands: getting cited in AI recipe and product answers
How food and beverage brands can position recipe and product content to be cited when someone asks AI for a recipe idea or product recommendation.
4 min read
Google's Gemini AI model increasingly powers several search-adjacent features, including AI Overviews and the more conversational AI Mode search experience, extending Google's core search infrastructure with more advanced generative and multimodal capability.
The relationship to Google's core search systems
Unlike a fully separate third-party AI platform, Gemini-powered search features are deeply integrated with Google's existing search index and ranking infrastructure — meaning the content already visible and well-ranked in traditional Google search is the same pool these features primarily draw upon.
- Gemini-powered features draw on Google's existing, unified search index rather than an entirely separate one.
- The same core ranking and quality signals that drive traditional search results also inform what Gemini-powered features surface and cite.
- AI Mode extends this with more conversational, multi-turn query handling and, in some cases, multimodal (image and text combined) query understanding.
There is no separate 'Gemini SEO' distinct from strong, well-established Google SEO — the features are extensions of the same underlying system, not a parallel one requiring an entirely separate strategy.
What AI Mode specifically adds
AI Mode, as covered in our optimising for Google AI Mode guide, supports more complex, multi-part conversational queries, meaning content that thoroughly addresses a broader topic in a genuinely conversational, complete way may be better positioned than content narrowly targeting a single keyword fragment.
Practical implications for content strategy
- Continue prioritising strong traditional SEO fundamentals as the foundation.
- Structure content to handle complex, multi-part questions thoroughly, not just single keyword phrases.
- Ensure multimodal content (images, video) is well-described and contextually connected to surrounding text, given Gemini's multimodal capability.
Frequently asked questions
Is optimising for Gemini-powered features different from optimising for traditional Google search?
Not fundamentally — since these features draw on the same core search infrastructure, the same quality and structure fundamentals that support traditional ranking also support Gemini-powered feature visibility.
Does AI Mode replace traditional Google search results?
It offers a more conversational, AI-driven alternative experience rather than fully replacing traditional search, and users can generally still access standard search results alongside or instead of AI Mode.
Should multimodal content strategy change because of Gemini's capabilities?
It is worth ensuring genuine coherence between text and visual content, as covered in our MUM explainer, since Gemini extends this multimodal understanding capability further.
If you want help optimising for Google's AI-powered search features, talk to our team.
The takeaway
Treat Gemini-powered search features as an extension of the same underlying Google ranking systems, not a separate platform to optimise for independently — the same AEO fundamentals that serve AI Overviews serve Gemini-powered features too.
Written by Fibvo — Bengaluru and Erode, India — working with clients in other time zones. Questions, or think we have it wrong? Tell us.
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