Nov 3, 2026 | 6 minute read
written by Bryan House
B2B eCommerce is still one of the hottest areas for growth. Modern buyers expect more from digital ordering and procurement every year, and digital channels keep taking a bigger share of B2B sales. That's good news, because most B2B digital commerce storefronts are still B.S. They fail buyers and sellers alike.
Something else changed since I first wrote this. Your buyers aren't just browsing your storefront anymore. They're asking ChatGPT, Claude, and even AI assistants like Meta Muse or Instinct to find products, compare options, and sometimes start the purchase. If your catalog, pricing, and rules aren't ready for that, you're invisible at the exact moment a buying decision gets made.
I'm still in a lot of meetings with B2B sellers frustrated by their current platform. Whether they're on a legacy system like Adobe Commerce (Magento) or SFCC, or experimenting with Shopify's B2B offerings, the story is the same. They're locked into what the ecosystem says they can do. Customizing feels nearly impossible, and now they're being asked to "do something with AI" on top of it.
It's 2026, and few B2B commerce platforms understand how to solve B2B problems, let alone AI-era ones. It's time to get back to basics.
Very few companies, B2B included, have the risk tolerance to replatform their commerce systems all at once. They're boxed in by oversimplified, templated experiences on one end. On the other, they're stuck in a web of legacy complexity every time they want to change something or add a third-party tool.
I'll keep shouting this from every rooftop: a "big bang" transformation doesn't have to happen. And AI just took away the best excuse for one.
Replatforming used to mean a long program and a big budget before a single buyer saw anything work. Most of that time and money went to the same grind: building storefront components, mapping schemas, wiring integrations, and cleaning up data for migration. AI now handles a lot of that work. Implementation timelines shrink, and so does the check you have to write to find out whether a new approach works.
That's the thinking behind our team’s big, hairy, audacious goal (BHAG) to shrink implementation timelines to six weeks and $100K. We are getting much closer to standing up a working B2B commerce experience on this timeline and budget. If that sounds aggressive compared to the replatforming projects you've lived through, that's the point. The days of $6 in services for every $1 in software spend are long over.
An AI-based implementation shows the rest of the business what good looks like, even if it's one region, one brand in your portfolio, or one distributor portal. And if your team sat out the composable era because replatforming looked too risky or too expensive, the cost of finding out just dropped. You can skip straight to the good part.
Here are three ways to nail your B2B commerce implementation.
In a composable architecture, integration is a core part of the development process. It should be the first thing you evaluate for your implementation.
That's why we built Composer as the integration layer for composable commerce. It gives you a library of pre-built, no-code integrations across search, email, OMS, PIM, CRM, SSO, promotions, shipping and fulfillment, and more. You can also build your own functions and integrations, run them on fully managed infrastructure, and build, test, and monitor them in one place.
What's new is how much of the wiring AI now handles. Every Elastic Path service is exposed through RESTful APIs, documented in OpenAPI, and reachable through the Model Context Protocol (MCP). Our Developer MCP Server lets your team orchestrate APIs, generate storefront components, and query our documentation straight from MCP-aware tools and IDEs. AI co-pilots help connect ERPs, CRMs, pricing engines, and fulfillment systems using pre-built patterns instead of hand-coding. Even data migration gets easier, with AI helping clean and prepare product, order, and customer data as it moves between systems.
The point isn't fewer developers. It's developers spending their time on orchestration and differentiation instead of schema mapping.
In the best B2B implementations, core integrations happen fast so developers can focus on what makes the business different. Most B2B companies are either stuck inside a templated storefront or wading through dozens of features they don't need.
The B2B fundamentals shouldn't be custom work. That includes:
With Elastic Path, those are modular building blocks, not workarounds bolted onto a B2C engine.
Once the basics are covered, ask what would make buying easier for your customers. Would an AI assistant help buyers and sales reps navigate a complex catalog and check availability? Would buyers want to assemble and compare product configurations themselves? Pick what moves your business metrics, like conversion, average order value, and repeat purchases. Then build from there.
This is the section I'd have written in 2025 if I'd known how fast things would move with our AI capabilities. As more buying journeys start with an AI answer engine instead of your homepage or search bar, your product catalog becomes the source of truth for humans and machines alike. AI agents read attributes, hierarchies, pricing rules, bundles, and relationships to decide what a product is and when it's relevant. A catalog built only for storefront pages won't hold up.
That's where Product Experience Manager comes in. It publishes structured, LLM-optimized product, pricing, hierarchy, and bundle data, so the same trusted catalog feeds your storefront, your sales team, and AI-driven buying experiences. Because products, pricing, and catalogs are independent APIs, you're not duplicating data or building custom feeds for every new channel.
Your teams get help too. A Merchandiser Agent automates merchandising work in Shopper Admin. An AI-assisted CMS speeds up front-end generation. You don't have to adopt all of it. Pilot search, prove the value, and let each win fund the next one.
Building a great B2B digital experience shouldn't be hard. It shouldn't require ripping and replacing your existing commerce system.
Start small. Launch a distributor portal, or replace the part of your storefront that isn't working. Get your catalog structured so AI systems can actually find and recommend your products. From there, build and integrate the rest of what your buyers expect.
While other vendors overcomplicate the path to business results, Elastic Path makes it simpler than ever, for your buyers, your sales team, and the AI agents now shopping on their behalf.
Bryan House
Chief Executive Officer
Schedule a demo to see how Elastic Path delivers unified commerce for leading global brands.