In an AI search era, brands must go where LLMs go

Opinion

LLMs build trust and relevance by citing external sources. Every high‑authority site you do not yet occupy is an invitation to shape how LLMs perceive your brand.

In an AI‑powered web, mere brand recognition no longer guarantees growth. Brands must become the answer that both consumers and intelligent agents turn to.

With Amazon’s Buy for Me integrating shopping into conversational AI, Google experimenting with shopping in AI Mode and ChatGPT’s Shopify partnership, large language models (LLMs) are swiftly becoming the primary interface between brands and buyers.

Savvy marketers will recognise that visibility in AI search hinges not only on keyword bids or organic rankings, but on the influence domains that LLMs cite when constructing answers.

The future of branding: Influence LLMs to protect your share of market

The new domain of influence

Consider the performance gap within Kantar’s BrandZ top 100 apparel names. On Meta’s Llama 3.3 LLM, Uniqlo appears 72% less often than Zara among top 10 AI search mentions, despite their comparable standings in conventional brand rankings.

Yet when we shift to traditional organic search, these brands share over 55% of their keyword footprint, meaning half of all impressions are fiercely competitive.

This contrast reveals two distinct battlegrounds: the crowded realm of transactional intent and the upstream domain of influence where brands can secure exclusive mindshare.

LLMs build trust and relevance by citing external sources, websites, articles and reports that their training data deems authoritative. Among leading apparel brands, only one in three of the most‑cited domains overlaps.

That divergence creates vast white space: every high‑authority site you do not yet occupy is an invitation to shape how LLMs perceive you to answer buyer queries. Securing those citations has SEO value as well as embedding your brand into the very fabric of AI‑driven discovery.

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Go where LLMs go

To claim that influence, brands must rethink content, partnerships and distribution through the lens of AI training signals.

First, identify the publishers, industry portals and research hubs most frequently referenced by the LLMs your customers use, whether that is ChatGPT, Gemini, Llama or emerging model families.

Then treat those domains as prime real estate: invest in programmatic and private marketplace media to place your message in the contextual environments that feed AI training.

Simultaneously, pursue editorial and content collaborations with those outlets — guest articles, co‑branded studies and expert Q&As — so that your brand’s expertise appears in the passages AI models ingest and subsequently cite.

Equally important is shaping your in‑house content strategy around the formats and themes these influential sources favour. If top‑cited domains lean towards data‑rich white papers, interactive infographics or step‑by‑step guides, mirror those preferences in your content calendar.

By aligning your assets with the structural patterns that LLMs recognise, you enhance the likelihood that your brand’s materials will be drawn into the AI knowledge graph and referenced in search answers.

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Monitor closely

Finally, AI search is a moving target. As models update and new players enter the scene, citation patterns shift and so should your tactics.

Establish a real‑time monitoring workflow that tracks which domains and content formats lead to AI citations across multiple LLMs. Use these insights to continuously refine media allocations, refresh content partnerships and evolve distribution channels.

This dynamic approach ensures your brand remains the go‑to answer not just today but as AI models learn and grow.

In a landscape where every impression is contested, brands that master the upstream influence of LLM citations will not only outshine competitors in AI search but also amplify consumer trust and loyalty.

Natasha Wallace is chief solutions officer for strategy and planning at Jellyfish