The Rise of Agentic Commerce Platforms: What Every Business Needs to Know

Ecommerce is stepping into a new era where autonomous AI (artificial intelligence) agents can plan, act, and transact for shoppers and businesses. This shift, called agentic commerce, has the power to simplify complex buying journeys, cut checkout friction, and deliver personalized experiences at scale. The platforms that will come out ahead are the ones built on open, composable architectures that let teams plug in new technologies and run secure, agent-driven workflows.

The momentum’s real. The global agentic AI market will jump from about $5 billion in 2024 to nearly $200 billion by 2034, growing at more than 40% each year. Retailers are already testing shopping assistants that compare products, manage subscriptions, and even place orders without human intervention.

In this article, you’ll learn what agentic commerce really is, the tech stack and standards that make it work, and the use cases with the biggest impact. We’ll also share how BigCommerce helps brands embrace agentic commerce today. 

What is agentic commerce?

Agentic commerce is the use of autonomous AI agents that can carry out multi-step tasks such as researching, comparing, and purchasing products within defined guardrails. Unlike chatbots or simple automation tools that only respond to prompts, these agents proactively plan and execute actions on behalf of the customer.

Think of it as a three-step flow:

1. Intent: the shopper expresses a goal, like “I need a new laptop under $1,000.”

2. Planning and tool use: the agent researches options, compares features, checks availability, and applies filters.

3. Checkout: the agent builds the cart, selects shipping and payment methods, and completes the transaction.

This pattern is similar to “co-pilot” experiences many consumers already know, where AI assists but still requires human confirmation. The difference is that fully autonomous flows let the agent handle the entire process with minimal oversight. Major retailers are already piloting this approach through shopping agents that manage product discovery, subscriptions, and even repeat orders.

Why platforms must be agent ready

For agentic commerce to move from concept to reality, the underlying platform has to provide the right technical foundation. That begins with headless APIs that let agents interact with storefronts, carts, and orders programmatically. It also requires real-time inventory and pricing data so agents can make accurate decisions, along with enriched product feeds containing the detailed attributes AI depends on to compare items and match customer needs. 

On the transaction side, an extensible checkout and payments framework ensures agents can handle a wide range of methods, from digital wallets to regional alternatives, while eventing and orchestration tools allow agents to respond dynamically to changes in stock, promotions, or order status.

Just as important as technical flexibility is governance and trust. Businesses need guardrails like role-based permissions and approvals to prevent unintended purchases, as well as audit logs to track every action an agent takes. Fraud controls and data provenance systems confirm that transactions are valid and that the information agents rely on is trustworthy. These safeguards are table stakes for enabling autonomous actions at scale, ensuring that businesses can innovate with agents without sacrificing security or transparency.

Common agentic commerce use cases

Agentic commerce is already moving from concept to reality, with retailers and brands testing agents in high-value areas that directly improve customer experience and operational efficiency. Five of the most impactful scenarios include:

• Autonomous shopping assistants: A customer states their goal, and the agent researches options, compares features, applies filters, and completes the purchase.

• Replenishment and subscription agents: An agent monitors product usage or timing, automatically reorders items when stock runs low, and applies loyalty discounts or approvals when needed.

• B2B repeat orders and quoting: A business buyer can rely on an agent to rebuild carts from contract catalogs, request quotes, and route them for approval within spend limits.

• Merchandising and retail media ops: An agent tests promotions, adjusts retail media bids, and manages product feeds to reduce errors and boost discoverability across channels.

• Store operations and support: Agents assist with post-purchase tasks like tracking orders, processing returns, and answering routine service requests, reducing manual tickets while improving response times.

Each of these use cases points to measurable outcomes like faster time-to-cart, higher conversion, and fewer manual fixes, all of which strengthen ROI.

Autonomous shopping assistants.

Autonomous shopping assistants take a shopper’s intent and carry it all the way to purchase. A customer might start with a simple request like, “Find me a pair of running shoes under $120 with strong arch support.” The agent then handles the entire flow: researching product options, comparing features, checking real-time availability, and placing the order through the checkout process.

Early examples are already visible. Amazon has introduced Rufus, a generative AI assistant that answers product questions and guides discovery directly in the shopping experience. Other major retailers are piloting similar agents that not only surface recommendations but also take action by adding items to a cart, selecting preferred payment methods, and finalizing the transaction.

These assistants bring two big advantages: they simplify decision-making for shoppers who feel overwhelmed by choice, and they increase conversion rates by reducing drop-off between browsing and checkout. For merchants, they represent a new way to capture demand and build loyalty in a world where customers expect faster, more personalized paths to purchase.

Replenishment and subscription agents.

Replenishment and subscription agents automate routine orders so customers never run out of essentials. These agents monitor timing, usage patterns, or stock levels, then place orders on schedule or when supplies run low. For everyday items like household goods or office supplies, the process can run fully in the background, saving time for both the shopper and the merchant.

To maintain trust, guardrails are critical. Agents must follow preset rules such as quantity limits, spending thresholds, or loyalty program eligibility. For higher-value items, approval steps ensure that an agent doesn’t confirm a purchase without oversight — especially important in B2B settings where large orders could exceed budgets.

This balance of convenience and control makes replenishment agents a powerful tool: they reduce churn, support predictable revenue streams, and keep customers confident that every automated order aligns with their preferences and policies.

B2B repeat orders and quoting.

For business buyers, repeat purchases are often complex, involving negotiated pricing, contract catalogs, and approval workflows. Agentic commerce streamlines this by letting an agent assemble carts directly from a company’s catalog, apply the right contract pricing, and submit the order or quote for approval. Instead of manually rebuilding large carts or navigating multiple steps, buyers can simply set the intent, “Reorder last quarter’s supplies,” and let the agent do the work.

These agents respect company rules such as spend limits, role-based permissions, and multi-level approvals, ensuring compliance while cutting down on time to order. The efficiency gains are significant: even a modest 1.5–2.5% lift in conversion from streamlined repeat orders could unlock hundreds of billions of dollars in additional retail revenue globally each year.

Merchandising and retail media ops.

Merchandising teams are under constant pressure to maximize performance across channels, and agents can take on much of that heavy lifting. These agents can rapidly test promotions, optimize retail media bids in real time, and manage product feeds with far greater speed and accuracy than manual workflows allow. By monitoring performance data continuously, they can adjust campaigns on the fly to drive stronger ROI.

A product feed management system such as Feedonomics makes this possible at scale. Agents depend on clean, enriched data, like GTINs, compatibility attributes, specs, and high-quality images, to ensure products are displayed correctly across marketplaces and ad platforms. With a reliable feed backbone, agents can identify errors before they impact discovery, apply channel-specific templates, and syndicate updates quickly to every sales channel.

The result is a leaner, more agile merchandising operation: fewer feed errors, faster time-to-market for campaigns, and smarter bid strategies that help brands stay visible in crowded retail environments.

Store operations and support.

Beyond shopping and merchandising, agents can also streamline day-to-day store operations and customer support. Post-purchase service is one of the clearest opportunities: agents can confirm delivery, send proactive updates, and surface personalized care tips to build customer loyalty.

Agents can also handle routine service tasks like processing returns, generating shipping labels, or tracking orders across carriers. For customers, this means faster resolution without waiting in a support queue. For merchants, it reduces the volume of manual tickets so human teams can focus on higher-value interactions.

Other operational tasks are also in scope, from updating inventory records to flagging potential fraud signals. In each case, agents act as behind-the-scenes assistants that help keep operations smooth, consistent, and cost-efficient.

The agentic platform landscape (2025 snapshot)

The current agentic commerce landscape can be grouped into three categories. Some retailers are building retailer-native agents, such as Amazon’s Rufus, which operate entirely within their own ecosystems. Others are offering platform-embedded assistants that come bundled with commerce platforms, exposing storefront, catalog, and checkout functions through APIs. A third path is third-party agent frameworks and tools, which act as orchestration layers that connect into multiple systems and handle data, search, payments, and service through connectors and APIs.

For businesses evaluating these options, several factors should be top of mind. Data quality is critical, since agents rely on complete product attributes, accurate pricing, up-to-date inventory, and high-quality media to perform effectively. API breadth matters just as much, because agents need access to catalogs, pricing, inventory, carts, checkout, and orders, ideally supported by webhooks and events. 

Checkout security also plays a role, with tokenized payments, fraud screening, and audit trails required to keep transactions safe. Governance ensures agents act within guardrails, using permissions, approvals, and logging to prevent misuse. Finally, interoperability is essential so teams can integrate search, personalization, feed management, and support tools without the cost and rigidity of replatforming.

Taken together, these factors highlight the strengths and limitations of today’s agentic commerce platforms. When product data is clean and APIs are open, agents can automate discovery, cart building, merchandising, and customer service at scale. But when data quality is weak or platforms are closed, performance drops and integration becomes costly. Ultimately, the most successful implementations will be those that combine strong governance and security with interoperable, composable foundations that let agents operate with confidence.

How BigCommerce supports agentic commerce

BigCommerce provides the foundation brands need to embrace agentic commerce today, offering four concrete ways to enable agent-driven shopping: agent-ready storefronts, automated data feeds, composable integrations, and advanced B2B experiences.

In the sections that follow, we’ll show how BigCommerce helps merchants build storefronts optimized for agent workflows, deliver clean and enriched product data through Feedonomics, connect third-party services through APIs, and support B2B buyers with role-based permissions and approval workflows.

Convert more shoppers with agent-ready storefronts.

BigCommerce storefronts are designed to support agent-driven shopping journeys from the ground up. With headless commerce and the Checkout SDK, agents can create carts programmatically, select shipping rates, calculate taxes, and complete payments without manual intervention. This flexibility allows AI-powered shopping assistants to move seamlessly from product discovery to purchase, giving shoppers a faster, more intuitive path to checkout.

Support for accelerated wallets like Apple Pay and Google Pay, along with localized alternative payment methods, ensures agents can complete transactions using the options customers prefer in each region. Tokenization plays a critical role here, providing a secure way for agents to handle sensitive payment data while keeping the checkout experience frictionless.

BigCommerce also offers a robust set of webhooks and events for carts, checkouts, and orders. These signals let agents respond in real time to inventory changes, price updates, or promotional adjustments, ensuring the shopper always sees accurate information and can act immediately. Together, these capabilities make BigCommerce storefronts ready to convert more shoppers in an era where agents drive the transaction.

Cut operational costs with automated feeds.

Clean, consistent product data is the backbone of agentic commerce, and Feedonomics provides the infrastructure to make it happen. By handling normalization, attribute mapping, validation, and channel-specific templates, Feedonomics ensures that agents can consume reliable, structured feeds across marketplaces and ad platforms.

Agents depend on enriched fields such as GTINs and MPNs, compatibility attributes, materials, specifications, availability, price rules, high-quality images, and variant details to deliver accurate comparisons and purchase decisions. When these details are standardized and validated, agents can act with confidence and avoid errors that slow down transactions.

The before-and-after impact is clear. Businesses that move to automated feed management see fewer feed errors, faster syndication across channels, and higher product discoverability for both agents and marketplaces. Key performance indicators to track include reduced time-to-market for new products, lower manual error rates, and improved conversion from better product visibility.

Feedonomics also brings strong governance controls to agentic commerce. Features like scheduled syncs, change logs, rollback workflows, and the ability to separate staging from production feeds give merchants confidence that agents are working with the right data. Even complex product structures like bundles and variants are handled cleanly, preventing confusion and ensuring that agents always deliver accurate results.

Customize with composable integrations.

BigCommerce’s flexible architecture and APIs give merchants the ability to easily integrate AI assistants, personalization engines, and orchestration layers without the cost or disruption of replatforming. This composable approach allows teams to choose the best tools for their needs while maintaining a consistent storefront and checkout experience.

Integration possibilities are broad. For example, a product-aware RAG search can let agents surface results enriched with detailed product data. Service agents can fetch order histories or return requests directly through APIs, reducing friction for customer support. Pricing and promotion microservices give agents a reliable way to query discounts, apply rules, and keep carts accurate in real time.

Extensibility patterns make this possible at scale. Developers can rely on webhooks, functions, and the BigCommerce App Marketplace to connect services efficiently, while safeguards like scopes, OAuth, rate limits, and PII handling ensure that agent access remains secure and compliant.

When approaching integrations, teams should also weigh build vs. buy decisions. Marketplace apps are often the fastest path to value for common use cases, while custom services give more control for complex or unique workflows. By choosing the right mix, businesses can extend their platform in ways that keep agents both powerful and safe.

Build advanced B2B experiences.

BigCommerce’s B2B Edition brings agentic commerce into complex business buying by giving agents the same tools that enterprise procurement teams already use. Company hierarchies, buyer roles, spend limits, and approval workflows mean agents can assemble carts or quotes but still route them for sign-off before anything is finalized. This ensures automation improves efficiency without breaking compliance.

Agents can also work with contract pricing and catalogs, pulling items from customer-specific groups or price lists. They can accelerate repeat purchases through quick order and reorder functions, or even handle quote-to-order flows end to end, submitting drafts for approval and converting them once confirmed.

Payment flexibility is just as important. With support for purchase orders, net terms, and other B2B-specific methods, agents can transact using the same financial processes buyers already trust. Each step is backed by thresholds, permissions, and audit trails so businesses know exactly when and how orders are placed.

Together, these capabilities allow B2B agents to streamline procurement while respecting the controls large organizations require, reducing friction for buyers and lowering administrative overhead for sellers.

The final word

Agentic commerce is no longer a distant concept — it is quickly becoming a practical reality. From shopping assistants and replenishment agents to B2B quoting and merchandising automation, agents are reshaping how transactions happen across retail and wholesale. Success in this new era depends on open, composable platforms with strong APIs, reliable data, secure checkout, and governance that builds trust.

For merchants, the takeaway is clear: preparing your platform now means you can capture the benefits of efficiency, personalization, and growth as agent-driven commerce scales.

FAQs about agentic commerce platforms

What is agentic commerce and which platforms let me implement it in my business?

Agentic commerce is the use of autonomous AI agents that plan, act, and transact, handling tasks like product research, comparison, and checkout within guardrails for safety and trust.

You can enable it through three main types of platforms: retailer-native agents built by large marketplaces, commerce platforms like BigCommerce that provide APIs, secure checkout, and clean product data for agent workflows, and third-party frameworks that connect into multiple systems. For most businesses, a composable platform with strong governance and interoperability is the fastest path to adopting agent-driven shopping.

Are there SaaS platforms that support marketplaces and agentic commerce flows?

Yes. Several SaaS ecommerce platforms now support both marketplace management and agentic commerce flows. They do this by exposing APIs for product data, inventory, pricing, checkout, and orders, which agents can query to build carts, process transactions, or manage feeds across channels.

Platforms like BigCommerce combine marketplace integrations with agent-ready features such as real-time inventory, tokenized payments, and governance controls. This means agents can operate safely across multiple storefronts or sales channels while merchants keep full visibility and compliance.

For businesses running multi-channel strategies, SaaS platforms with open, composable architectures are the most practical way to bring marketplaces and agent-driven commerce together.

Why is "agent-ready" platform design critical for the future of ecommerce?

Agent-ready design ensures a commerce platform can support AI agents that shop, transact, and manage operations on behalf of customers or businesses. Without the right foundation, clean product data, broad APIs, secure checkout, and governance controls, agents cannot act reliably or safely.

As more transactions are influenced or completed by autonomous agents, platforms that aren’t agent-ready risk slower adoption, higher integration costs, and weaker customer experiences. By contrast, open and composable platforms give merchants the flexibility to plug in emerging tools and scale confidently. In short, being agent-ready isn’t optional, it’s what will separate future-proof ecommerce businesses from those left behind.

How can businesses evaluate and prepare their platform for agentic commerce readiness?

Start by assessing the essentials. Does your platform provide high-quality product data, real-time inventory and pricing, and broad API coverage for carts, checkout, and orders? Next, look at checkout security. Tokenization, fraud protection, and audit logs are critical for agents to transact safely. Governance matters too, with permissions, approval rules, and data provenance ensuring agents act within guardrails.

From there, test interoperability. Can your platform integrate easily with search, personalization, and feed management tools without replatforming? Finally, evaluate scalability by reviewing eventing, webhooks, and extensibility options that let agents react to changes instantly.

Businesses that prepare in these areas position themselves to adopt agents smoothly, reduce risk, and capture early gains from agentic commerce.

How do AI systems and intelligent agents improve the customer journey in digital commerce?

Modern AI systems and intelligent agents are transforming the customer journey by moving beyond simple bots and static automation. Powered by GenAI, machine learning, and LLMs such as ChatGPT from OpenAI or research-focused tools like Perplexity, these solutions can understand natural language and act across multiple steps of a transaction.

In practice, this means agents can deliver personalized recommendations, generate relevant product recommendations, and even manage inventory management tasks like suggesting alternatives when an item is out of stock. By analyzing customer data and metadata, AI-driven platforms can improve SEO and GEO, guide smarter forecasting, and support more resilient supply chain planning. Together, these capabilities give shoppers faster answers and businesses more reliable insights to drive growth.

Which providers offer agentic commerce capabilities today?

Several providers now embed AI-driven features directly into their platforms, from shopping agents that help with discovery to assistants that streamline supply chain and order flows. Large enterprise vendors like Salesforce have introduced artificial intelligence layers to support personalization and analytics, while independent frameworks and SaaS platforms focus on specialized areas such as feed management or conversational commerce.

What matters most is interoperability. Whether you’re leveraging ChatGPT, Perplexity, or platform-native agents, the best providers expose APIs that connect clean product data, secure checkout, and real-time inventory management. This ensures businesses can deliver personalized recommendations at scale while keeping governance and compliance in place.