Demandbase Is Now Marketing to the AI That Recommends Which Software to Buy

The New Customer Is a Machine

Demandbase, a B2B marketing platform, announced a product in October designed to track and influence how AI assistants describe companies to potential buyers. Not the buyers themselves—the AI systems they ask for recommendations.

The company calls it an AEO Agent. It sits alongside two other AI products launched at Demandbase's GO conference in New York: a Campaign Agent that connects marketing campaigns to revenue goals, and an Audience Agent that builds target lists around ideal customer profiles. But the AEO Agent has a different brief. It monitors what AI systems say about a brand, including how those systems portray the company to members of a buying group.

Demandbase frames this as "business-to-agent" marketing—B2A. The underlying anxiety is specific: a company might rank well in search engines, maintain strong analyst coverage, and run expensive ad campaigns, yet still be invisible when a prospect asks an AI assistant which software to buy. Or worse, be described inaccurately.

That creates an unusual new task for enterprise marketing teams: optimize not just websites and campaigns, but the machine-generated narrative surrounding the company.

Why This Matters Beyond the Product Launch

For decades, B2B marketing has followed a human-centered funnel. Generate awareness. Capture intent. Nurture leads. Influence buying committees. Help sales close deals. Demandbase is betting that funnel is becoming partly machine-mediated.

AI assistants may now summarize vendors, compare products, identify likely suppliers, and recommend shortlists before a salesperson knows a buying process has begun. That shifts the marketing challenge. Instead of reaching decision-makers directly, companies may need to manage their reputation with algorithms—monitor what AI systems say, identify gaps or errors, and adjust public information accordingly.

The business problem is concrete. A prospective buyer asks an assistant to compare customer-data platforms, accounting systems, or cybersecurity vendors. The answer draws on documentation, reviews, public websites, community discussions, and training data. Vendors cannot assume that traditional search-engine optimization controls the result. If an AI assistant narrows a shortlist from 20 vendors to three, being omitted is not a branding problem. It removes a company from the opportunity entirely.

That matters particularly in B2B markets with long sales cycles and expensive customer acquisition. Losing a deal before the vendor knows it was ever considered is a new kind of invisible failure.

The Feedback Loop Nobody Asked For

The launch points to a broader shift in enterprise software: AI is becoming not only a feature inside business products, but also a new intermediary between businesses and their customers.

That produces an unusual feedback loop. Companies use AI tools to create marketing campaigns designed to influence other AI tools, which then advise human buyers. The result is a layer of machine-to-machine persuasion sitting on top of ordinary sales and marketing.

The risk is straightforward. Every vendor will have an incentive to optimize for AI recommendations, potentially flooding the information ecosystem with content designed less for humans than for model interpretation. The upside is equally real: companies may finally gain visibility into how automated systems misunderstand their products, misstate capabilities, or favor better-documented competitors.

What This Actually Reveals

The compelling part of this story is not that Demandbase launched another set of AI agents. Most B2B software companies are doing that. The unusual part is that a mainstream marketing platform is formalizing a new customer category: the software system that recommends what other companies should buy.

That turns the enterprise buying process into a three-sided market. Sellers, human buyers, and the AI assistants standing between them. Each participant has different needs, different information, and different ways of being influenced.

For now, this remains an experiment. But the category Demandbase is creating—business-to-agent marketing—suggests a future where enterprise vendors compete not only for human attention, but also for favorable treatment by the algorithms those humans trust to do their research.

That may sound abstract. But the first time a company loses a seven-figure deal because an AI assistant left them off a shortlist, it will feel very concrete.