Amazon Business reaches $60 billion in annualized gross sales as agentic AI rewrites B2B discovery

Amazon Business has reached $60 billion in annualized gross sales, according to Digital Commerce 360, a figure that places it firmly among the most consequential platforms in enterprise procurement. The milestone arrives as the mechanics of B2B buying are undergoing a structural change: agentic AI systems are starting to handle product discovery and supplier evaluation tasks that human buyers previously owned, and most supplier catalogs are not ready for the shift.

A $60 billion benchmark and what it demands of suppliers

The Amazon Business number matters not just as a revenue signal but as a concentration risk for every distributor, manufacturer, and wholesaler that still treats the platform as a secondary channel. When a single marketplace accounts for that volume, the standards it sets for product data, pricing transparency, and fulfillment speed effectively become market standards. Suppliers that fall short of those standards lose discoverability, regardless of catalog depth or account relationship history.

Forbes reports that B2B ecommerce continues to outpace B2C in total transaction value, reflecting the scale of enterprise purchasing moving online. The Amazon Business figure is consistent with that broader trajectory, and it raises the floor for what buyers expect from any digital channel, whether a first-party marketplace or a supplier's own site.

Fastenal's Q2 results, reported by Digital Commerce 360, offer a parallel data point. The industrial distributor posted continued growth in digital sales even as it navigated a CEO transition, a sign that digitally mature distributors are sustaining momentum regardless of internal change. The contrast with less digitally advanced peers is widening.

Agentic AI is changing who, and what, does the searching

The more disruptive development for procurement and operations leaders may not be marketplace scale but the rise of agentic AI in B2B discovery. Digital Commerce 360, citing Deloitte research, reported in July 2026 that AI agents are increasingly capable of conducting supplier searches, comparing product specifications, checking pricing and availability, and initiating purchase requests without a human clicking through a catalog. The implication is direct: if an AI agent is doing the buying, then the product page designed for a human buyer may never be seen at all.

Agentic systems rely on structured, machine-readable data. A rich product description written for a category manager's eyes may be invisible to an AI agent that is parsing structured attributes, API-fed pricing, and real-time stock signals. Suppliers whose data architectures were built for search-engine optimization rather than machine consumption face a meaningful discoverability gap as these agents scale.

Deloitte's framing, as reported by Digital Commerce 360, points to catalog data quality, API availability, and schema consistency as the variables that will determine which suppliers get surfaced by AI buying agents and which get bypassed. For procurement leaders evaluating their supplier base, those same criteria are becoming a new dimension of vendor qualification.

Amazon Pharmacy and eNavvi show what embedded procurement looks like in practice

A concrete early model of agentic-style procurement is already live in healthcare. Amazon Pharmacy announced an integration with eNavvi that embeds real-time drug pricing and availability directly into clinical prescribing workflows, as reported by Digital Commerce 360. A clinician can see cost and formulary data at the point of prescribing rather than sending a patient through a separate lookup process. The purchasing signal is embedded in the workflow itself.

That architecture, a buying trigger embedded in an operational workflow rather than accessed through a separate procurement interface, is precisely what agentic AI promises to replicate across other verticals. In industrial supply, for example, a maintenance management system that surfaces real-time pricing and availability from pre-qualified suppliers at the point of a work order is the same structural model. The eNavvi integration is not a healthcare curiosity; it is an early production instance of workflow-embedded procurement that operations teams in other sectors should be studying.

What operations and procurement teams need to do now

The convergence of Amazon Business's scale, agentic AI's growing role in discovery, and live examples like the eNavvi integration compresses the timeline for action. Suppliers waiting for agentic buying to mature before updating their data infrastructure are already late. Buyers evaluating their supplier panels should be adding data readiness to the scorecard alongside price and lead time.

Digital Commerce 360 has highlighted catalog data quality, structured pricing feeds, and real-time availability as the three operational levers most directly tied to AI-agent discoverability. For distributors and manufacturers, that means auditing product data against machine-readable standards, not just human-browsing standards. For procurement teams, it means asking suppliers which of those capabilities they currently support.

The B2B ecommerce market is large and still growing, according to Forbes. But the growth is now splitting into two lanes: platforms and suppliers that are machine-legible and those that are not. The $60 billion Amazon Business figure shows where volume concentrates when discovery is easy. Agentic AI will apply that same logic at a more granular level, routing transactions toward suppliers whose data can be parsed, priced, and confirmed in real time, and away from those that cannot.