A four-step guide to navigate the world of agentic commerce

With AI agents becoming integral to commerce, businesses must focus on implementing seamless single-click purchase journeys with AI-driven personalization and customer service.

What Is Agentic Commerce? 

Agentic commerce refers to the next evolution of ecommerce where AI agents handle product discovery, comparison, and purchase decisions on behalf of consumers. It’s the foundation of a world where buying becomes seamless, personalized, and almost invisible. 

The agentic commerce era

Businesses must prepare to be discoverable, transactable, and trusted—by AI agents and human shoppers. 

According to Precedence Research, the AI in e-commerce market is growing fast, from USD 7.25B in 2024 to a projected USD 64B by 2034, at a CAGR of 24%. We are rapidly moving toward an agentic commerce era where AI agents will shop on customers’ behalf, making the whole shopping transaction invisible. Instead of customers sifting endlessly through websites, comparing options, and navigating checkouts, an agent will handle the entire shopping process, from finding products to facilitating payments. Companies embracing digital commerce strategies can redesign their platforms to blend innovation and customer-centricity for seamless experiences. Will the future of shopping shift more toward AI search engines with direct buying options, like Perplexity’s Buy with Pro, or marketplaces like Amazon offering fully automated purchases? Will brand websites adapt to support agentic commerce themselves? Or will entirely new players emerge? The questions are many, but one thing is certain: traditional commerce models will be heavily challenged. The whole ecosystem is gearing toward it, with strategic moves both from large and niche players.

What businesses must do 

Here’s a four-step guide to get ready for the era of agentic commerce.

1. Build agentic storefronts and interfaces: User journeys will change, and there will be a need for parallel agentic journeys for existing engagement platforms (marketing, commerce, and service). A significant portion of commerce will occur through AI assistants. Organizations must develop new journeys and front-end interfaces for agentic commerce, where AI assistants enable voice or image searches, price and product comparisons, and streamline the checkout process by guiding users through each step or handling it on their behalf.
2. Introduce AI assistants for product discovery: Advanced search with filters (by price, brand, rating, etc.) is a must for any ecommerce website. However, this still overwhelms customers due to the numerous filters and search parameters and must change. AI shopping assistants converse in natural language to understand unique customer needs by asking the right questions. They use that context along with customer profile insights to instantly surface best-fit products for shoppers, simplifying discovery for complex product sets.
3. Enable always-on customer service with agents: With virtual assistants and AI agents buying on customers’ behalf, they will also need to provide post-purchase support for a wide range of tasks, including order tracking and returns. Additionally, brands will need to enable their customer service agents to facilitate agent-to-agent communication. For instance, integrating Siri into all other apps, such as Uber and Amazon, on a mobile device could create a unified interface for users to interact with for any queries and support needs across apps.
4. Optimize for machine-to-machine (M2M) decision-making: As the trend of users utilizing AI for product discovery and research grows, the content must change, since what is relevant to display for humans doesn’t work with bots. Leveraging commerce managed services can help optimize backend operations and ensure reliable AI-driven transactions. This will require content to have deep product understanding, quick, digestible information, and direct answers. Apart from the need to redesign and recreate their content, organizations will have to make their existing websites and mobile content more visible to GenAI search engines and shopping assistants. Expose product or service data via structured, machine-readable formats (e.g., schema.org, APIs) and create agent-friendly APIs for ordering, inventory, and fulfillment.

Real-World Examples of Agentic Commerce in Action.

From search engines to AI assistants

Discovery to delivery made seamless while inspiration turns to checkout—with a single click.

Google AI Mode, built on top of Gemini and the Shopping Graph (which contains over 50 billion product listings), enables browsing and searching for products through natural language conversation. Google can tap into its broader data ecosystem to surface shopper insights and help users browse for inspiration. This easily integrates into functionality for tracking prices, virtual try-ons, and buying on the shopper’s behalf. All this can be done on Google’s platform itself.

Perplexity’s “Buy with Pro” is a feature available to Perplexity Pro subscribers that allows them to purchase products directly within the Perplexity AI search engine. It enables a one-click checkout for eligible products and offers free shipping on these purchases.

Support for agentic payments

Real-world use cases that use tokenized, rule-based systems.

Mastercard: Agent Pay focuses on making AI-driven payments secure and straightforward. Through the introduction of agentic tokens, verified AI agents can complete purchases safely, following rules and preferences set by the consumer. This tech can handle one-off payments, recurring expenses, subscriptions, and more, all underpinned by verification and trust.

Visa: Intelligent Commerce is a suite of integrated APIs plus a commercial partner program that helps developers connect to consumers through AI. Their tokenization technology is framed as “AI-ready cards” with set spending limits and controls, leaning on solid security to ensure transactions are legit.

Marketplaces and commerce platforms’ adoption

Getting ready for agentic commerce requires a fundamental shift in the engagement model across the purchase journey.

Amazon’s Buy for me: Allows shoppers to buy products from other brand sites while staying entirely in the Amazon experience, and the agent completes the commerce transaction in the background.

SAP CX AI Toolkit: Enhances ecommerce experiences by facilitating natural language interactions via an AI shopping assistant. Customers can inquire about product details, availability, pricing, and compatibility through conversational queries and receive context-aware responses that streamline the shopping process.

Salesforce’s Agentforce: Delivers personalized shopping experiences by analyzing customer behavior, recommending products, managing inquiries, processing returns, suggesting alternatives, and providing tailored promotions.

In essence, agentic commerce will need businesses to transform their ecommerce landscape end-to-end by retooling their tech stack, focusing on content clarity, and embracing M2M interactions. We are already seeing multiple new tools and solutions in this space. Organizations should run this as a focused initiative with teams focusing on all four areas: agentic storefronts, shopping assistants for product search and discovery, agentic customer service, and content transformation for M2M interactions.