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Home ›› E-Commerce & Marketplaces ›› Agentic Commerce Battle Misses the B2B Prize

Agentic Commerce Battle Misses the B2B Prize

Tech giants are locked in a race to own AI-powered shopping, but focus on consumer discovery and checkout is misplaced. According to Bryan House, CEO of Elastic Path, the real breakthrough for agentic commerce lies in B2B procurement, where complexity and data quality give AI agents the clearest edge.

iG
iGEN Editorial
June 12, 2026
Agentic Commerce Battle Misses the B2B Prize

The biggest players in tech have been locked in a race to own the future of shopping, according to TechRadar. OpenAI rolled out shopping features, pulled back, and reintroduced them. Perplexity launched a buy button. Amazon built "Buy for Me," much to the chagrin of retailers who did not opt in. Google redesigned shopping around AI answers. Yet, despite constant pivoting, nobody has a clear win. The reason, argues Bryan House, CEO of Elastic Path, is that everyone is focused on the wrong problem.

The Consumer AI Shopping Hurdle

The conversation about agentic commerce has almost entirely centered on consumer discovery and checkout — how AI helps someone find a gift, compare mattresses, or click "buy" through a chatbot. House contends this is the hardest possible place to start and potentially the last place AI will deliver value. When AI rewrites a checkout flow, it inherits years of painstaking optimization. Brands have spent enormous resources perfecting the moment between "I want this" and "I bought this" — every upsell, loyalty touchpoint, and data capture moment. An AI agent makes that optimization irrelevant, ignoring carefully designed product pages, email capture, or recommendation engines.

Early data backs this up, according to TechRadar. Walmart reported a 66% drop in conversions when agents intermediate the buying experience. Amazon's "Buy for Me" triggered backlash from retailers because it optimized for buyers at the explicit expense of sellers. Some argue consumers don't trust AI to shop for them, yet people hand their credit card to Temu without blinking despite FBI warnings of data risks. The problem, House suggests, is that no one has built a consumer AI commerce experience that clearly beats the existing one.

B2B Procurement: A Different Animal

B2B buying is a completely different process built around complexity, not convenience. TechRadar outlines the scenario of a mid-market manufacturer trying to buy routine industrial fasteners. They might use approved vendor lists, negotiated contract pricing differing by account, compatibility requirements, complicated approval workflows varying by order size, or a purchase order generation process that touches an ERP. "Somewhere buried in all of the complexity is the specific screw they need, and they probably need a sales rep to get it."

House argues that most of what those sales reps do isn't strategic judgment — they're applying institutional knowledge to a decision tree that, if properly encoded, would run itself. That is exactly where AI agents can give sales reps superpowers. The boring, unglamorous world of B2B procurement sits largely unexamined, and that's where agents have the biggest potential to break through first.

Why B2B May Lead Consumer for the First Time

Throughout tech history, consumer products achieved massive scale before enterprise versions followed — social media was Facebook before it was Slack. Agentic commerce may flip that model because B2B organizations have better data. But that doesn't always mean cleaner data: most B2B product catalogs are a disaster of PDFs, legacy ERP exports, and specs living in silos. Despite this, the structured nature of B2B procurement — with its rules, approvals, and negotiated terms — makes it a more natural fit for AI intermediaries than the chaotic, emotionally driven world of consumer shopping.

Aspect Consumer AI Commerce B2B AI Agent Commerce
Primary challenge Optimized checkouts, brand trust Complex approval workflows, product data quality
Conversion impact -66% (Walmart) Not yet measured at scale
Data environment Clean but huge legacy systems Messy catalogs but structured decision trees
Likely adoption speed Slow because barriers are high Faster because problem is painful

What Sellers Need to Do

For B2B sellers and marketplace operators, House's analysis suggests a strategic pivot. Rather than chasing consumer-facing AI features that degrade conversion, invest in encoding institutional rules, cleaning product catalog data, and building AI-ready procurement workflows. The competitive advantage will go to those who make their product data and approval processes machine-readable. This is a compliance and operational upgrade, not a customer-facing gimmick.

As TechRadar notes, the conversation has been almost entirely centered on consumer discovery and checkout. But the unglamorous world of B2B procurement — with its approved vendor lists, contract pricing, and ERP integrations — is where agentic commerce can deliver immediate, measurable value. The winners will be those who focus on the boring infrastructure first.


Sources: TechRadar – Main Feed

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