Agentic commerce: The next revolution in online buying
How AI agents will transform shopping and buying—and what retailers, manufacturers and distributors need to do now to stay ahead.
The eCommerce landscape is on the brink of another seismic shift. Just as mobile commerce transformed how consumers shop, we're now entering the era of agentic commerce—where AI agents will increasingly handle purchasing decisions on behalf of consumers and businesses. Rather than relying on manual keyword queries or direct navigation, users now delegate product discovery, comparison and even purchasing to autonomous AI agents operating across platforms
For retailers, manufacturers and distributors, this isn't a distant future scenario. In recent months, we've seen major payment providers make significant moves that signal the arrival of this transformation. PayPal launched its Agentic Toolkit and partnered with Perplexity to enable AI-powered shopping directly through search results. Meanwhile, Visa and Mastercard are racing to develop payments tools that will enable AI agents to make purchases on behalf of users, with Visa introducing Intelligent Commerce and Mastercard unveiling Agent Pay.
These developments aren't experimental—they're the foundational infrastructure for a new era of commerce. The question isn't whether this transformation will happen, but how quickly—and whether your eCommerce operations will be ready.
What is Agentic Commerce?
Agentic Commerce refers to AI-powered agents autonomously searching, discovering, comparing and eventually purchasing on behalf of users. These aren't simple chatbots—they're sophisticated AI systems capable of understanding complex requirements, comparing options, negotiating terms and completing purchases.
Think of it as having a highly intelligent personal shopper that never sleeps, processes vast amounts of data instantly and learns from every interaction. These agents might operate as:
Personal shopping assistants that automatically reorder household essentials
B2B procurement agents that source materials and manage complex purchasing workflows
Enterprise purchasing systems that handle routine procurement across multiple categories
Specialized buying agents for categories like travel, insurance, or professional services
The key distinction from today's AI tools is agency—these systems don't just recommend; they act independently, on behalf of humans, within defined parameters. Amazon's "Buy for Me" feature exemplifies this shift, allowing AI agents to purchase products from third-party websites while users remain within the Amazon app, marking a clear signal that Agentic Commerce is moving from concept to reality.
The impact on eCommerce
For retail eCommerce
Consumer behavior will shift from active browsing to passive delegation. Instead of comparing products across sites, consumers will rely on AI agents for both routine and complex purchases. PayPal predicts that within five years, 20% to 30% of its customers will start their shopping through AI agents and AI tools.
This creates new dynamics:
Reduced direct traffic as agents bypass traditional storefront browsing
Increased importance of structured product data that agents can parse and compare
New competitive landscape where agent preferences determine market share
For B2B Manufacturing and Distribution
As Bain Capital Ventures notes in their analysis of the agentic commerce era, B2B commerce is particularly suited for this transformation, involving repetitive ordering, complex specifications and multi-stakeholder processes—areas where AI agents excel. The infrastructure being built by major payment providers positions AI agents as sophisticated purchasing systems for business procurement, directly impacting how manufacturers and distributors reach their customers.
Timeline: When will the shift to Agentic Commerce happen?
Predicting exact timelines for agentic commerce adoption is challenging given how rapidly the technology is evolving, but industry predictions about agentic AI provide valuable guidance for retailers, manufacturers and distributors.
OpenAI's recent update to ChatGPT's web search capabilities with personalized product recommendations and direct purchase links, alongside the simultaneous April 2025 launches of PayPal's Agentic Toolkit, Visa's Intelligent Commerce and Mastercard's Agent Pay, demonstrate that agentic commerce infrastructure is ready now. Looking ahead, Deloitte projects that 25% of enterprises using generative AI will deploy autonomous AI agents in 2025, doubling to 50% by 2027. Gartner predicts that at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028, up from virtually 0% in 2024, with 33% of enterprise software applications expected to embed agentic AI capabilities by that time.
The key insight? Winners will be determined by actions taken today, not reactions taken later.
The product data challenge
Here's the critical challenge revealed by these recent developments: AI agents don't shop like humans. They don't browse pretty pages or respond to marketing copy. They make decisions based on structured, machine-readable data that can be processed through APIs and payment systems like those being developed by major providers to enable seamless agent-driven transactions.
From SEO-optimized to human & agent-friendly
Traditional eCommerce has focused on SEO-optimized product descriptions designed to rank well in search engines, but the shift to agentic commerce requires a more sophisticated approach that serves both human shoppers and AI agents making intent-driven decisions.
Traditional SEO Description: "Stylish stainless steel coffee maker with programmable features"
Intent-Driven, Agent-Friendly Description: "12-cup programmable drip coffee maker ideal for brewing daily coffee for 4-6 people, stainless steel construction, 24-hour timer for morning automation, auto shut-off safety feature, 900W brewing power, compact countertop design (14.5"H x 11.8"W x 8.7"D), 1-year manufacturer warranty"
The key difference lies in addressing user intent rather than just keywords. When someone searches for "coffee solution for busy mornings" or "automatic coffee maker for small kitchen," AI agents need product descriptions that clearly connect features to real-world use cases. The agent-friendly version explains not just what the product is, but how it solves specific problems—brewing capacity for family size, automation for busy schedules and space efficiency for kitchen constraints.
Beyond text: Making media assets agent-readable
Product images, videos and other media assets also need to become agent-readable through structured metadata. For example, describing a sneaker as "black leather sneaker with white sole suitable for casual attire” rather than simply "black sneaker" helps AI agents understand both the aesthetic and appropriate context. Each media asset should include descriptive metadata that captures visual nuances, usage scenarios and contextual appropriateness—enabling agents to make more precise recommendations based on specific customer needs and occasions.
The cost of poor product data
In an agentic environment, poor data quality creates massive costs:
Invisible to agents: Products without structured data won't be discovered by AI systems qqn
Competitive disadvantage: Agents favor comprehensive, standardized information
Lost automation: Poor data prevents integration with new payment rails
Increased costs: Manual cleanup becomes exponentially expensive
Research shows businesses lose an average of $15 million annually due to poor data quality—costs that multiply as AI agents become primary discovery mechanisms integrated with platforms like PayPal's Agent Toolkit.
Preparing your eCommerce operations for Agentic Commerce
The competitive advantage of early action
The aforementioned recent launches demonstrate that the infrastructure for Agentic Commerce is ready now. Retailers, manufacturers and distributors who act immediately to optimize their product data and eCommerce infrastructure will gain significant competitive advantages.
As Salesforce notes in their analysis of AI agents in eCommerce, agents will naturally favor platforms with superior data quality and accessibility, creating a virtuous cycle where better data leads to more agent traffic, which drives higher sales and improves overall eCommerce performance. Early investment in agent-friendly infrastructure also enables operational efficiency through automation across inventory management, pricing and merchandising.
1. Audit and optimize product data
The foundation of agentic commerce readiness starts with a comprehensive evaluation of your current product information. With major payment providers now offering agent-specific checkout solutions, retailers, manufacturers and distributors need to conduct thorough audits of product data completeness, identifying gaps in structured attributes across their entire catalog.
This process should focus on standardizing product categorization and attribute naming conventions to ensure consistency with emerging industry standards. Implementing data quality scoring for all products creates accountability and measurable improvement targets that align with the structured data requirements of AI agent platforms.
2. Invest in product data management tools
Manual product data management simply won't scale when AI agents can process thousands of products per second through sophisticated APIs. The new Agentic Commerce infrastructure requires retailers, manufacturers and distributors to have systems that can automatically extract and standardize product information from multiple sources while validating data quality in real-time. In addition, the way consumers search will transform: searching will no longer entail just a few keywords, and results will be based on both intent and past history. As a result, product content and media need to be richer than ever before, and be readable and optimized for agents.
The right tools should be capable of enriching incomplete product records with missing attributes, maintaining consistency across product lines and supporting bulk updates with automated data synchronization. This investment becomes critical as payment platforms require standardized product information for AI agents to make purchasing decisions. Discover how Mirakl Catalog Platform and our Catalog Transformer can help do just that.
3. Develop agent-friendly infrastructure
Creating the technical foundation for agentic commerce requires building comprehensive APIs for product discovery, pricing and availability that can integrate with the new payment infrastructure being deployed by major providers. This means ensuring compatibility with systems like PayPal's Agent Toolkit, which enables integration with popular agent frameworks including OpenAI Agent SDK, LangChain and Vercel AI SDK.
Your eCommerce infrastructure must ensure real-time data synchronization across all touchpoints to prevent agents from making decisions based on outdated information. Implementing structured data markup using standards like Schema.org across all product pages makes your inventory discoverable and comparable for AI agents operating through these new payment channels.
4. Enable your organization for agent-driven sales
The emergence of agentic payment platforms means sales and marketing teams need to understand how their products will be discovered and purchased by AI agents rather than human browsers. This involves developing comprehensive training programs that emphasize data quality requirements and the business impact of structured product information in an agent-driven marketplace.
For manufacturers and distributors, this also means working with retail partners to ensure product information flows seamlessly through the supply chain. Providing tools and templates for creating agent-friendly product listings removes barriers to compliance, while implementing data quality incentives rewards teams for maintaining the complete, accurate product information that AI agents require.
The future belongs to the prepared
The recent launches by Amazon, PayPal, Visa and Mastercard represent more than new features—they're the foundation of a fundamental shift in how commerce operates. These platforms are betting billions of dollars that AI agents will become primary drivers of purchasing decisions, and they're building the infrastructure to support that future today.
As Bain Capital Ventures observes, we're at the dawn of a totally new shopping paradigm where intelligent agents will operate on each consumer's behalf. Agentic commerce will happen gradually, then suddenly. The retailers, manufacturers and distributors who invest in proper product data management now—while these platforms are still in their early phases—will be positioned to capture the first wave of AI agent-driven traffic.
The question: Will your products be discoverable and purchasable by the AI agents that will drive future commerce? The answer depends on the actions you take now.
In a world where AI agents make purchasing decisions through sophisticated payment platforms, the best product data wins.
Ready to scale with agentic commerce? Start by enhancing your product data— explore our solutions, designed to be the infrastructure powering agentic commerce. Book a demo today!
