Elastic Path CEO Bryan House on Product Data, Pricing, and Owning AI Intelligence for Manufacturers and Distributors

Product Data Is the Foundation for AI-Driven Discovery

King opened by observing that much of what AI requires of B2B companies is the foundational work the industry has discussed for years, now done faster and with better tools. House agreed and pointed to product data as the starting point. The quality of a company's product data has always shaped its product detail page (PDP), the page that shows a single item's specifications, images, and price. It now also shapes whether an AI model outside the seller's control recommends that product at all.

House was direct about the effort involved: "product data quality is a hard problem to solve." He expects AI tools to make that work more manageable by identifying gaps and helping fix them, and he believes product data will move from a supporting task to a requirement for staying competitive. Practitioners such as SPI's Nichole Hess have made a similar case in how master data powers B2B eCommerce for manufacturers and distributors.

Renting Intelligence Versus Owning It

King described how AI compresses the traditional buying funnel of awareness, consideration, and conversion into a single prompt. Instead of fifty search results, a buyer now receives what King summarized as "here are the best three options to address your very unique needs." That shift raises what King called "the question of who owns the intelligence itself."

House explained the difference. Renting intelligence means supplying product data feeds to frontier models (the large, general-purpose AI systems built by companies such as OpenAI, Google, and Anthropic) in exchange for visibility when buyers ask relevant questions. "I give you data, you bring me customers," he said. Owning intelligence means running an AI-powered experience on the company's own site, such as natural language or semantic search (search that interprets the meaning of a question rather than matching exact words), with full control over what buyers see. "I think the days of keyword search are over," House said.

He used the ball bearing industry to illustrate why ownership matters in B2B. Buyers may need bearings rated for specific temperatures, fluid viscosity, and operating environments, and a seller can guarantee that depth of detail in its own environment. House also pointed to NVIDIA's agreement to acquire Hugging Face, the open source model repository, as a sign that the tools for companies to train and run their own models are maturing. B2BEA has also explored how AI-powered search is transforming eCommerce for manufacturers and distributors.

Customer Relationships Remain With the Seller

King compared the moment to the rise of marketplaces. "Anybody dealing with Amazon knows you're giving up control for access and for distribution, for volume," he said. House sees a different path for B2B sellers, whose relationships rest on negotiated contracts, procurement processes, and purchase orders. "AI is gonna fit within the confines of that contractual relationship you have," he said. He expects procurement agents to take on routine tasks such as repurchasing, a direction supported by Gartner's prediction that 90% of B2B buying will be intermediated by AI agents by 2028, representing more than $15 trillion in spending.

Encode the Intelligence, Keep the Judgment

House offers organizations a simple framework. "Intelligence is all the information," he said, while judgment is the experience a team uses to put that information to work, such as which markets to pursue, when to run promotions, and how to structure contracts. His guidance is to capture every piece of intelligence in a structured format, including product details stored in PDFs, spreadsheets on sales team laptops, and contract pricing, and make it available through an API (a standard connection that lets software systems share data). The goal, in his words, is to "encode as much intelligence as you can," which gives companies the flexibility to automate workflows, win customers, and lower costs.

For specialized markets such as industrial supply, medical devices, and food service, House sees an opportunity for industry associations to help build shared data that general AI models do not yet have. Shared market information, he explained, benefits every participant without giving away a company's competitive advantage. "It's actually raising the tide for all of us in a particular industry," he said.

Bringing Customer-Specific Pricing Into AI Experiences

Pricing is one of the most complex parts of B2B eCommerce, and House described how Elastic Path's architecture prepared it for this moment. The company separated products, pricing, and catalog organization into independent services, so a single product catalog can support many customer agreements. "If you have a thousand customers, you can have a thousand price books," House said, referring to the customer-specific price lists that reflect negotiated terms. Salsify co-founder Rob Gonzalez discussed related catalog strategy in The Hidden Engine of E-Commerce.

In an owned intelligence model, an AI assistant can recognize the buyer and return that customer's negotiated price alongside search results. House also described automatically generated quotes routed for approval based on each buyer's spending limits. A purchase order process that once took two weeks "could happen literally in a matter of minutes," he said. That speed aligns with buyer expectations, as a 2026 Gartner survey found that 67% of B2B buyers prefer a rep-free buying experience.

Lowering the Cost of Modernization

Many B2B companies built their own eCommerce platforms because off-the-shelf software could not handle complex catalogs and pricing. When these companies size a replacement project, the estimate can reach two years and several million dollars. House said "the biggest three areas of cost in a new implementation are front-end development, integrations with back end systems, and then data modeling and data migration," and all three can be accelerated with AI.

Elastic Path is building AI tooling into its product and implementation services toward an ambitious internal goal of "six weeks and a hundred thousand dollars. And we're not there yet." Reaching that target would turn a full digital transformation project into something closer to an onboarding fee. The approach builds on composable commerce, an architecture that assembles a commerce system from separate, connected services, a topic Novatize CEO François-Jérôme Gosselin examined in his conversation on composable commerce and B2B product data.

The Website Continues to Evolve

Asked whether the traditional website will exist in five years, House said websites still carry a company's story and identity, and AI will increasingly augment them so visitors can ask questions as they browse. King shared that when B2BEA launched its own AI agent, visitors were unsure what to ask, which led the team toward guided navigation. House has seen the same pattern. "The first thing we do is we create a bunch of sample prompts that you could use to get started," he said.

Leading Through a Generational Technology Shift

House compared this period to his experience at Acquia, which launched the day Lehman Brothers collapsed and went on to build and manage whitehouse.gov. He described the AI era as a similar moment of rethinking how business operates, at a much larger scale. For manufacturers and distributors, he advised that leaders "have to build an executive team around you that is willing to understand the moment" and form a clear view on every opportunity.

Inside Elastic Path, AI has made ambitious projects feasible and reshaped how the company goes to market. House reported that AI-assisted prospect outreach, trained on how Elastic Path wants to engage, now outperforms manual messages, and that "the cost of experimentation has gone down so dramatically." King connected that to customer experience design. With automation handling repetitive work, companies can revisit the experiences they always wanted to build. "The experiences can be dreamt," King said.

About Bryan House

Bryan House is CEO of Elastic Path, where he leads go-to-market, customer success, global services, and product teams. He previously served as Chief Commercial Officer at Neural Magic and was a founding team member at Acquia, where he served as Senior Vice President of Worldwide Account Management. He has also led product marketing for content management solutions at EMC Documentum. House holds an MBA from Harvard Business School and a degree in brewing from the Siebel Institute of Technology, and he brewed beer professionally for eight years.

About Justin King

Justin King is the Chief AI Officer of the B2B eCommerce Association and host of The B2B eCommerce Show, where he speaks with practitioners and leaders shaping digital transformation for manufacturers and distributors.