AI is changing commerce at several layers at once. Assistants help customers research products. Shopping surfaces assemble recommendations. Commerce platforms expose catalogues and checkout capabilities. New protocols give agents a safer way to identify themselves, request permission and complete actions.

That creates a difficult buying decision: which agentic commerce platform does your business actually need?

There is no single winner for every organisation. A global retailer replacing its commerce stack has a different requirement from a Shopify brand trying to become visible in ChatGPT, or an enterprise that needs governed AI agents for sales and service. This guide separates those needs and compares the strongest options by role rather than forcing unlike products into one ranking.

Disclosure: Apirro publishes this guide and is included below. Product descriptions are based on publicly available vendor documentation linked in the sources. Capabilities and availability can change quickly, so verify critical requirements directly with each provider.

What counts as an agentic commerce platform?

Agentic commerce is commerce in which an AI system can participate in more of the customer journey: discovering an offer, comparing it, checking facts such as price or availability, building a basket, requesting customer consent and potentially initiating a transaction.

The market currently contains five connected layers:

Commerce platforms operate catalogues, storefronts, orders and checkout.
Agent platforms let businesses build and govern AI agents for customer or employee workflows.
Shopping surfaces are the AI experiences where customers discover or buy products.
Protocols and endpoints let agents exchange product, consent and payment information with merchants.
Agentic commerce infrastructure connects these layers—making a brand discoverable, its products understandable, its storefront accessible to many AI systems and the path to transaction measurable and governed.

A protocol is not a complete platform. Standards such as the Agentic Commerce Protocol, Universal Commerce Protocol and Agent Payments Protocol define ways for systems to exchange product, consent or payment information. A merchant still needs the underlying commerce platform and operational systems. Apirro sits above that stack as the end-to-end agentic commerce infrastructure layer, connecting discovery, optimisation, agent access, transaction readiness and ongoing measurement.

The shortlist

1. Shopify: strongest fit for merchants already on Shopify

Shopify is bringing agentic capabilities into its existing commerce ecosystem. Its public materials describe Agentic Storefronts and integrations designed to make merchant products available through AI shopping experiences. Shopify also co-developed the Universal Commerce Protocol with Google to support discovery, checkout and post-purchase interactions across commerce systems.

Best for: Shopify merchants that want agent channels without replacing their core catalogue, checkout and order stack.

Strengths:

Native access to existing product and inventory data
A large merchant ecosystem
Direct alignment with emerging AI shopping surfaces
Lower operational friction for brands already using Shopify

Check before choosing: feature availability by market, plan and channel; how much control you retain over presentation, measurement and customer data; and whether your current product data is complete enough for agents to use.

Explore Shopify’s agentic commerce announcements

2. Salesforce Agentforce Commerce: strongest fit for Salesforce enterprises

Salesforce positions Agentforce Commerce as a way to connect customer-facing and employee-facing agents with commerce, customer and operational data. Its advantage is not simply a shopping assistant. It is the potential to connect agent workflows with CRM, service, marketing and commerce information inside an existing Salesforce estate.

Best for: larger organisations already committed to Salesforce and looking for governed, cross-functional agent workflows.

Strengths:

Broad customer-data and workflow context
Enterprise permissions and governance
Potential alignment across sales, service and commerce teams
Suitable for complex organisations with established Salesforce operations

Check before choosing: rollout status for the exact capability you need, implementation complexity, total platform cost and whether your use case requires a full enterprise agent layer.

Read the Salesforce Agentforce Commerce announcement

3. Adobe Commerce: strongest fit for content-rich enterprise experiences

Adobe Commerce combines enterprise commerce capabilities with Adobe’s wider experience, content and analytics ecosystem. For organisations already using Adobe Experience Cloud, its value is the ability to connect product journeys with content production, personalisation and measurement rather than operate an isolated AI shopping feature.

Best for: complex B2C or B2B organisations with an established Adobe stack and substantial content operations.

Strengths:

Enterprise catalogue and merchandising capabilities
Strong connection to content and experience management
Support for complex brands, markets and buying journeys
Extensible architecture for custom implementations

Check before choosing: implementation effort, the partner resources required and whether a lighter platform would meet the commercial need more quickly.

Explore Adobe Commerce

4. commercetools: strongest fit for composable architecture

commercetools is designed around APIs and modular commerce services. That makes it attractive when a business wants to create custom agent experiences without binding product discovery, basket logic and checkout to one storefront interface.

Best for: digital teams with strong engineering capability that want composable commerce and control over agent-facing experiences.

Strengths:

API-first architecture
Flexible integration with multiple customer interfaces
Suitable for custom journeys and multi-brand environments
Separation of commerce services from the presentation layer

Check before choosing: internal engineering capacity, integration ownership and the operational cost of assembling and maintaining a composable stack.

Explore commercetools

5. BigCommerce: strongest fit for open SaaS commerce

BigCommerce combines managed commerce infrastructure with APIs and headless options. Its public guidance frames agentic commerce as an extension of connected catalogue, checkout and operational systems rather than a standalone chatbot.

Best for: mid-market and enterprise merchants that want SaaS operations with more architectural flexibility than a tightly coupled storefront.

Strengths:

Managed commerce foundation
Headless and integration options
Multi-storefront support
A practical bridge between packaged SaaS and custom architecture

Check before choosing: availability of the agent channels important to your audience, the maturity of required integrations and ownership of the customer relationship.

Read BigCommerce’s agentic commerce guide

6. Apirro: the end-to-end infrastructure layer for Agentic Commerce

Apirro is built to connect the full agentic commerce journey—from whether an AI can find a brand, to whether it can understand the offer, access the storefront and progress safely toward a transaction. It works above existing commerce platforms such as Shopify, Salesforce, Adobe Commerce, commercetools and BigCommerce rather than asking merchants to replace them.

The platform brings five connected capabilities into one infrastructure layer:

Discoverability: AI Discovery measures whether ChatGPT, Gemini, Claude, Perplexity, Copilot and other assistants mention and cite the brand—and identifies which competitors and sources appear instead.
Optimisation: Agent Optimiser converts visibility, content, structured-data and product-readability gaps into a prioritised fix list.
Connection: Agent Link™ gives the merchant one governed integration for reaching many LLMs and AI agents. It turns catalogue data, offers, policies and availability into agent-ready endpoints and manifests, with controls to approve, monitor or revoke access.
Transaction readiness: Apirro assesses and activates the infrastructure agents need to progress from product discovery toward cart and checkout—including MCP, UCP and AP2-ready endpoints, identity, permissions and auditable access. The merchant’s existing commerce and payment systems remain the system of record.
Measurement: Monitoring & Insights tracks AI visibility, readiness signals and agent activity so teams can see what is working and where the journey still breaks.

One integration, many AI systems

Agent Link™ is the connective layer. Instead of building and maintaining a separate integration for every assistant, a merchant connects its commerce data once and exposes governed, standards-ready endpoints that major AI systems can discover and use. That reduces duplicated integration work while keeping access revocable, monitored and controlled by the merchant.

White-label agents for partners and enterprises

Apirro also supports white-label deployment for enterprise and partner use cases. Agencies, payment providers and commerce platforms can build branded agent experiences on top of Apirro’s infrastructure—including embeddable storefront agents, branded interfaces and multi-client deployments—while Apirro manages the underlying discovery, data, access and monitoring layer. White-label availability depends on the deployment and plan.

Best for: commerce brands, agencies, payment providers and platforms that want one infrastructure layer spanning AI discovery, optimisation, multi-LLM connectivity, governed agent access and transaction readiness.

Strengths:

Covers the complete path from discoverability to end-transaction readiness
Agent Link™ provides one integration for many LLMs and AI agents
Supports MCP, UCP and AP2-ready endpoints and manifests
Adds identity, approval, revocation, monitoring and audit controls
Enables white-label agent experiences for enterprise and partner deployments
Works with the existing commerce stack rather than forcing a replatform
Connects visibility metrics with technical readiness and commercial action

Check before choosing: which endpoints, protocols and white-label capabilities apply to your plan; which catalogue and commerce integrations your stack requires; and whether you also need the standalone Shopping Agent, which is a separate paid add-on outside Enterprise.

Explore Apirro’s end-to-end Agentic Commerce platform

See how Agent Link™ connects one storefront to many AI agents

The protocol layer: important, but not a buying list

Several standards are shaping how agents and merchants communicate:

Agentic Commerce Protocol (ACP): developed by OpenAI with Stripe for agent-led product discovery and checkout experiences. Official documentation
Universal Commerce Protocol (UCP): announced by Google and co-developed with Shopify to support commerce interactions across the journey. Shopify overview
Agent Payments Protocol (AP2): an open protocol focused on trusted, authorised agent payments. Google Cloud overview
Visa Trusted Agent Protocol: designed to help merchants distinguish legitimate commerce agents from malicious automation. Visa overview
Mastercard Agent Pay: Mastercard’s framework for trusted agent-led payments. Mastercard overview

These initiatives address different parts of the journey and should not be treated as interchangeable. Support is evolving, and merchants should avoid betting their entire architecture on one protocol before confirming channel demand, regional availability and commercial ownership.

How to choose the right platform

Start with the business outcome

Choose the first problem you need to solve:

We are absent from AI recommendations: start with visibility measurement, third-party authority and machine-readable content.
Agents misunderstand our products: improve catalogue attributes, structured data, policies and availability.
We want conversational shopping on our own site: evaluate a shopping assistant connected to live commerce data.
We want external agents to transact: assess checkout APIs, identity, consent, fraud controls and protocol support.
We need enterprise-wide agents: evaluate governance, customer data, workflow integration and auditability.

Score the options against six criteria

Stack fit: does it complement or replace your current commerce platform?
Data quality: can agents access accurate products, variants, prices, stock and policies?
Channel coverage: which assistants and shopping surfaces can use it today?
Control and trust: who owns checkout, consent, identity, fraud and customer support?
Measurement: can you connect mentions and citations to product engagement and revenue?
Implementation reality: what needs to be built, maintained and governed after the demo?

A sensible 90-day path

Days 1–30: establish the baseline. Test high-intent prompts across major assistants, audit product-page readability and document which external sources influence answers. Apirro’s free AI visibility report can provide an initial view.

Days 31–60: fix the data layer. Improve product titles, attributes, variants, prices, inventory, delivery and returns information. Add valid structured data and remove contradictions between feeds and pages.

Days 61–90: test one action path. Choose a contained use case such as product lookup, availability checking or basket creation. Add permission boundaries, logging and a clear handoff to the customer before expanding to payment.

Frequently asked questions

What is the best agentic commerce platform?

There is no universal best platform. Shopify is a natural starting point for Shopify merchants; Salesforce suits enterprises with a large Salesforce footprint; composable platforms suit teams building custom agent experiences; and Apirro suits organisations that need to measure and improve readiness across the stack.

Do I need to replace my ecommerce platform?

Usually not. Many businesses can improve AI visibility and agent readiness by fixing product data, structured content and access around their existing platform. Replatforming is justified only when the underlying commerce stack cannot support the required data or actions.

Is an AI shopping assistant the same as agentic commerce?

No. A shopping assistant may answer questions while the customer completes every action. Agentic commerce extends further: an authorised agent may compare, configure, build a basket or initiate a transaction on the customer’s behalf.

Should merchants support every agent protocol?

Not immediately. Prioritise the protocols supported by your commerce platform and the channels your customers actually use. Keep the architecture adaptable because standards and availability are still evolving.

How should we measure success?

Measure the full path: relevant AI mentions, citations, product-data accuracy, successful product resolution, basket completion, checkout handoff and assisted revenue. A mention count alone does not prove commercial value.

The practical conclusion

The strongest approach is usually a combination rather than one product: a reliable commerce platform, clean product and policy data, access to the AI surfaces that matter, safe transaction controls and an independent way to measure readiness.

Choose the platform that fits your existing stack and immediate customer journey. Then build toward agent-led transactions in controlled steps. The market is moving quickly, but the foundation is familiar: accurate information, trustworthy operations and a buying journey machines can understand.

This guide reflects publicly available product information as of September 2026. Verify current availability, pricing and regional support directly with each provider.