Zero-click commerce arrives: AI agents set to intermediate $15 trillion in B2B purchases by 2028

A single Gartner forecast is reframing urgency across B2B commerce: AI agents will intermediate $15 trillion in business purchases by 2028, according to projections cited by commercetools and reported by MarketScale. That figure represents not a distant horizon but a three-year window in which the foundational mechanics of B2B procurement — supplier discovery, product evaluation, order execution — shift from human-navigated processes to autonomous machine action.

The market these agents are entering

The scale of B2B commerce gives the agentic shift its weight. According to Grand View Research data compiled by Creatuity, the global B2B e-commerce market reached $20.4 trillion in 2024 and is projected to hit $36.1 trillion by 2031. The Digital Sales Institute puts the 2026 global B2B e-commerce GMV at $36 trillion, growing at a 14.5% compound annual rate, with projections ranging as high as $62.2 trillion by 2030 depending on the methodology applied.

Inside that market, digital channels have already become the default. The Digital Sales Institute cites research showing 80% of B2B sales interactions now occur through digital channels, and McKinsey finds that 30–38% of B2B organizations now generate the bulk of their revenue through e-commerce. The infrastructure supporting that volume is now being restructured around AI.

From pilot to production: where AI stands today

Adoption data collected by Creatuity from McKinsey, Salesforce, and others shows the enterprise AI story has moved decisively past the experimentation phase. McKinsey's 2025 State of AI report found that 72% of organizations had adopted AI in at least one business function, up from 55% in 2023. Salesforce data puts 65% of B2B companies using or piloting AI specifically for commerce operations — pricing, recommendations, search, and personalization.

The use cases generating the most deployment activity, per Salesforce data cited by Creatuity, include personalized product recommendations (56% of B2B commerce teams), dynamic pricing and discount optimization (49%), and demand forecasting and inventory management (44%). AI-powered conversational interfaces for order management account for 42% of deployments, according to Gartner data in the same compilation.

Yet concentration of early deployment does not mean the market is saturated. Boston Consulting Group research cited by Creatuity finds only 18% of B2B companies describe their AI commerce maturity as advanced — meaning the majority still have significant ground to cover before AI is genuinely core infrastructure rather than a layer of pilots.

The buyer arriving before the seller does

B2B buyer behavior has shifted in ways that compound the pressure on sellers. The Digital Sales Institute reports that 91% of buyers are already familiar with a vendor before the first meeting, 85% have largely set their purchase requirements before speaking to sales, and 61% — a figure Gartner attributes directly — now prefer a rep-free buying experience. Separately, Forrester data cited by Creatuity finds 73% of B2B buyers prefer researching online before engaging a sales representative at all.

The preference for autonomy extends to transaction size. The Digital Sales Institute notes that 73% of buyers are now willing to place orders over $50,000 through self-service channels. Meanwhile, 94% of B2B buyers use generative AI as a core research tool, a figure that directly connects buyer behavior to the agentic infrastructure being built on the sell side.

B2B e-commerce isn't catching up to B2C. It already dwarfs it — and it's accelerating. — The Digital Sales Institute

Zero-click commerce and what it demands of sellers

MarketScale, citing commercetools analysis, identifies the logical endpoint of these behavioral and technological trends as zero-click commerce — a category in which the click, historically the atomic unit of digital retail measurement, ceases to be the defining event in a purchase journey. An AI agent working for a procurement team could identify, compare, and order components from a supplier without a human buyer ever navigating the vendor's website. The vendor that wins the order is the one whose data the agent can read, trust, and act on.

This dynamic elevates Answer Engine Optimization — AEO — from a theoretical discipline to an operational priority. Where conventional SEO is built to attract and persuade human readers scanning a results page, AEO requires sellers to structure product data, content, and technical documentation so that AI systems can accurately interpret and surface their offerings inside automated decision flows. For organizations that have spent years refining keyword strategies and conversion-rate optimization for human visitors, the AEO pivot is a significant strategic reorientation.

The infrastructure implications extend into the technology stack. Platforms must be capable of exposing product catalogs, pricing, and inventory data in formats that AI agents can consume programmatically. APIs, structured data standards, and machine-readable product information shift from back-office technical requirements to competitive differentiators — a point that also informs the broader framework OpenText lays out in its Agentic AI Genome, which describes enterprise memory, orchestration layers, and governed agent architecture as the structural prerequisites for operating autonomous AI at scale.

Governance and the human element

OpenText's Agentic AI Genome, authored by Shannon Bell, Tom Jenkins, and Steve Wagstaff, frames the organizational challenge beyond technology selection: as agents take on execution across workflows, the central question becomes how enterprises govern and collaborate with an expanding digital workforce. The authors argue the future of the agentic enterprise will be defined not by automation alone, but by how successfully organizations balance autonomy with accountability, and speed with trust.

That governance dimension is particularly acute in B2B procurement, where purchase decisions carry financial, regulatory, and supplier-relationship consequences. Deploying agents that can commit to contracts or release payment without human checkpoints introduces risk exposure that most enterprise compliance frameworks have not yet addressed.

Three years to build the infrastructure

The 2028 timeline embedded in the Gartner forecast reported by MarketScale gives B2B organizations a narrow runway. Sellers that treat agentic commerce as a future concern rather than a present investment risk ceding purchasing volume to competitors whose catalogs, APIs, and content are already machine-readable. For commerce platform providers, systems integrators, and B2B technology buyers, the near-term priority is closing the gap between the 18% of companies with advanced AI commerce maturity and the 82% still building toward it.