The Reality of Agentic Search
In 2023, I wrote "How Do You Market to an AI Agent?" exploring how the shift from active searches to AI-driven recommendations would fundamentally reshape marketing. Now that agentic search is here, I'm seeing something that most marketers are still missing entirely.
The Multi-Agent Reality We're Actually Getting
Everyone's talking about AI agents, but here's the crucial misunderstanding: the agent you'll be marketing to isn't the friendly LLM you chat with.
Look at OpenAI's new agent model. It's not one AI doing everything - it combines three distinct technologies:
ChatGPT for communication
Deep research capabilities
Web search functionality
This pattern is everywhere in AI solutions now. What we're getting isn't a single superintelligent agent - it's multiple specialized agents working in concert:
Communication agents that interact with humans (friendly, conversational)
Management agents that determine task completion and workflow progression
Execution agents that actually perform searches, evaluations, and purchases
The Execution Agents: Your Real Target Audience
Here's what most marketers don't realize: the search and purchase agents won't be friendly like ChatGPT.
These execution agents will be mechanical, robotic, almost insect-like in their behavior. They'll be crawling, slithering, searching as efficiently as possible to resolve human or organizational needs. They're optimized for speed and accuracy, not conversation.
Because of this fundamental difference, the way they consume information is completely different from how humans (or communication agents) process content.
Where These Agents Are Actually Looking
AI engineers are telling us these agents search deep into web content - not the top-ranking Google results everyone obsesses over, but the longer, deeper, more detailed pages.
This is why everyone's saying "write more content" and "create Q&As." But I think they're missing the bigger picture.
The real goldmine is backend product catalog information.
These mechanical search agents are going to be reading through structured product data, but they need much more than basic specifications. They're looking for a comprehensive matrix of information - like individual cubbie holes for each attribute they can use to determine best fit.
What agents need includes:
Detailed product/service descriptions and specifications
Usage scenarios and contexts
User demographics and behaviors
Performance data and results
Legitimate research data - brands sponsoring statistically significant, academically robust research
Raw qualitative survey data and analysis with outcomes
Brand values and attributes for values alignment matching
Problem-solution mappings
The agents will examine multiple different attributes of both the product and brand to match the needs of the consumer, organization, or process they're serving. This includes everything from functional product attributes to alignment of values between the consumer and the brand.
The Amazon Advantage
Having comprehensive catalog information on Amazon is probably more critical now than ever before. Amazon's structured data format is exactly what these search agents need - detailed specs, categorization, reviews, and outcome data all in a standardized format.
This connects directly to what I predicted in 2023: "having your product information fed into and referenced across various databases will be key." Amazon has become the dominant product information database that AI agents will reference, and they're probably closest to creating a comprehensive stream of product attributes specifically designed for search agents.
Amazon already has catalog information for such a large percentage of available goods, giving them a massive advantage in creating the matrix of product information, usage data, specifications, brand values, and research that agents need to make optimal matches.
While everyone else is trying to figure out how to structure information for AI agents, Amazon already has the infrastructure these agents will consume. All this information must be accessible to agents crawling the web today, but in the future, someone (likely Amazon) is going to create a dedicated stream of product attributes specifically optimized for search agent consumption.
What to Watch For
Keep your eyes open for new services creating dedicated data streams for AI agents. When someone builds a platform that provides constant feeds of product and service information specifically formatted for agent consumption (JSON, APIs, structured data), that's where you'll want to be.
As I noted in my 2023 piece: "Whether it's a profit-driven database, an institutional one, or an awards-based repository, the broader the coverage across these platforms, the higher the likelihood of your product being recommended by AI agents."
The agents will know exactly where to go for reliable, standardized product intelligence.
The Strategic Shift
This isn't about writing better blog posts or climbing Google rankings. This is about preparing for a fundamentally different type of search entity - one that doesn't care about your brand story or marketing copy, but obsessively focuses on matching solutions to needs with mechanical precision.
The companies that understand this distinction - and structure their product information accordingly - will have a massive advantage as agentic search becomes the dominant discovery method.
The question isn't whether this future is coming. It's whether you'll be ready when these mechanical search agents come crawling through your data.