6
Marketers who adapt their customer discovery strategy for AI-intermediated search and commerce will own the next decade of customer acquisition. A little more than a year ago, Bain & Company predicted that LLM-powered search would fundamentally disrupt the buyer journey. It has. Across the US, for example, 44% of online buyers surveyed by Bain & Company mostly start their journey in an LLM or split their search between AI tools and traditional search engines.
The inflection point
Traditional search dominance in consumer discovery has gradually been hollowed out over the past decade. E-commerce marketplaces, social shopping, and video channels have each carved off a piece of search for consumers of all ages. But the rise of AI-powered search differs in kind, not just degree.
The rise of conversational, natural language interactions that allow for long, context-heavy queries has created a more personalized discovery experience for consumers. Those who still use traditional search engines are increasingly relying on AI-generated summary information rather than clicking through to links on the page. Half of online shoppers trust generative AI for initial research and product comparisons.
B2B buyers have started to embrace the bots
Turning to B2B markets, our research suggests that buyers at small and medium-size businesses have already started to build their vendor short lists inside LLMs. They’re using AI to construct the consideration set, then turning to websites, review platforms, and YouTube demonstrations to validate what the model suggests. If a vendor’s brand doesn’t surface in that first AI-generated list, it may never make it to the validation stage.
Extrapolating these buying behaviors to large companies, we expect significant dislocation in the sales and marketing funnel.
Half the battle is just showing up
Bain & Company’s work with agentic AI platforms consistently shows that the sources LLMs rely on to build recommendations overwhelmingly consist of nonbrand-owned media. Third-party review sites, industry publications, analyst commentary, social platforms, and affiliate published content dominate, not a company’s own home page, blog, or paid ads. An analysis of proprietary ScrunchAI search data spanning about 500 million citations showed that 89% of unbranded prompts are fulfilled by third-party sources.
Marketing resource and expense allocation thus requires a structural reset. Classic search optimization, search marketing, and lower-funnel conversion tactics become necessary but not sufficient. The sources LLMs trust look more like strong public relations and earned media strategy than a performance marketing dashboard. The brands making the most progress in AI-driven discovery focus their investment in three areas: category fame, accurate brand portrayal, and content freshness and LLM readability.
Organizing for a cross-functional approach
Many leading companies are starting to rethink how they organize their marketing operating model. A traditional siloed structure with SEO in one lane, public relations, marketing communications, and influencer marketing in another, and web and content generation in another cannot move at the speed or with the coherence that this shift demands.
It’s more effective to redesign ways of working cross-functionally to incorporate shared performance metrics, unified messaging governance, and rapid experimentation across earned, owned, and technical teams. In practice, this becomes less a campaign and more a capability.
Bain & Company sees leading organizations creating a playbook that ranges from no-regret optimizations to bigger structural bets: measure generative engine performance; revamp on-site content strategy for LLM readability; increase engagement with and investment in earned media, affiliate management, and influencer and reputation management; and explore application programming interface integrations and agent-powered partnerships with leading LLMs.
Of course, the models will evolve, the sources they weight will shift, and the strategies that work today will need to adapt. Companies should aim to better understand how their customers’ needs and behavior are evolving along the discovery-to-purchase journey.
To that end, CMOs should prioritize three questions: Where are we acquiring our next set of customers? What is our current presence across the AI engines our buyers use? If AI is constructing our buyers’ short list, are we shaping that short list or are our competitors?