How Can Businesses Work With Agentic Commerce Platforms Going Into 2027?

Commerce is changing faster than many businesses expected. For years, online selling was built around websites, mobile apps, search bars, product pages and checkout screens. Customers had to visit a platform, compare products, make decisions and complete the purchase themselves.

That process is now beginning to change.

AI agents can now search for products, compare options, understand customer preferences and, increasingly, complete transactions on behalf of users. This shift is commonly described as ‘agentic commerce’. Visa defines it as a model where AI agents can browse, compare, follow user preferences and make payments within defined rules.

Stepping into 2027, businesses will need to think beyond simply adding AI to their websites. They will need to prepare their products, data, payments and operations so that AI agents can understand and interact with their businesses.

What Does Agentic Commerce Mean for Businesses?

Traditional ecommerce depends heavily on customers navigating a business's digital storefront. Agentic commerce changes the starting point. Instead of asking customers to find the right product themselves, an AI agent may understand what they want and search across different businesses to find an appropriate option.

For example, a customer could tell an AI assistant that they need dinner for four people, want vegetarian food, have a particular budget and need delivery within 40 minutes. The agent could then search available restaurants, compare menus, check delivery times and potentially place the order.

The same idea can apply to retail, travel, grocery, healthcare services and many other sectors.

This means businesses will increasingly need to become understandable not only to humans, but also to machines acting on behalf of humans.

Make Your Business Data Ready for AI Agents

The first practical step is to improve the quality of business data.

AI agents need reliable information to make decisions. Product names, prices, descriptions, availability, delivery areas, specifications, return policies, reviews and payment information should be accurate and structured.

Poor data can create poor recommendations. If a product is shown as available when it is actually out of stock, or if the delivery information is unclear, an AI agent may simply choose another business.

Businesses should therefore review their digital information and make it easy for software systems to access and understand.

This is particularly important for marketplaces where hundreds or thousands of sellers may have different products, prices and availability.

Build an AI-First Commerce Infrastructure

The next step is to look at the technology behind the storefront.

Businesses should start moving from platforms designed only for human browsing toward systems that can also support machine-to-machine interaction. This does not mean replacing websites or mobile applications. Instead, businesses can build an additional intelligence layer that allows AI agents to interact with existing commerce systems.

Google's Universal Commerce Protocol, or UCP, is one example of how the industry is moving in this direction. Google describes UCP as an open standard designed to connect consumer surfaces, businesses and payment providers across discovery, purchasing and post-purchase activities.

For businesses, this points toward an important change: the future storefront may not always be a webpage.

Sometimes, the storefront could be an AI agent communicating with another AI agent.

Prepare Marketplaces for AI-Led Buying

Marketplaces have an especially important role to play because they already bring multiple sellers, products, payments and fulfilment services together.

An AI-first multivendor marketplace can take this model further by allowing intelligent systems to understand products across different sellers and help customers find suitable options based on their actual requirements.

Imagine a customer looking for a laptop under a certain budget, with a particular processor, screen size and delivery deadline. Instead of manually opening multiple product pages, an AI agent could compare products from different sellers and create a shortlist.

For marketplace operators, this creates a new opportunity. The goal is not simply to make the marketplace searchable. It is to make the marketplace understandable to AI.

That requires structured product information, accurate inventory, seller reliability data, transparent pricing and APIs that allow approved systems to interact with the marketplace.

Connect AI With Payments and Checkout

Discovery is only one part of agentic commerce, and that too a small one. The actual transformation happens when an AI agent can move from recommendation to transaction. Businesses therefore, need to consider how their checkout systems will work when an AI agent is involved.

It may address questions like- Who authorised the purchase? What spending limit has been set? Which payment method can the agent use? Can the transaction be verified? What happens if the agent makes an incorrect purchase? And, will the agent be able to split the payment as well?

These questions are becoming increasingly important as payment networks develop infrastructure for AI-led transactions. Mastercard, Visa and other financial technology companies are working on systems designed to bring authentication, permissions and security into agentic payments. Mastercard has specifically highlighted the need for businesses to distinguish legitimate AI agents from malicious bots and verify that an agent has been authorised to act and it does so in the same way as intended.

Hence, businesses preparing for the future should work closely with their payment providers and technology partners rather than treating AI checkout as simply another website feature.

Give AI Agents Real-Time Access to Operations

An AI agent cannot provide a reliable customer experience if it only knows what was true an hour ago. As a result, real-time information will become increasingly important.

Businesses should connect AI systems with operational data such as:

• Live product and menu availability
• Current pricing and promotions
• Inventory levels
• Delivery locations and estimated times
• Order status
• Store timings
• Seller performance
• Returns and cancellation policies

Consider food delivery. A customer does not want an AI agent to recommend a restaurant simply because its menu looks suitable. The agent also needs to know whether the restaurant is currently accepting orders, whether the selected items are available and whether delivery is possible to the customer's location.

This is where an AI-first food delivery software platform can become particularly valuable. Instead of using AI only for customer support or recommendations, the platform can connect intelligence with restaurant discovery, menu availability, order management, delivery and fulfilment.

The same principle applies to almost every on-demand business viz groceries, medicines, accessories, or stationary, besides others.

Build Trust Before Giving Agents More Control

Agentic commerce will not succeed simply because AI can perform more tasks. Customers need to trust what the agent is doing.

Businesses should make permissions clear and provide customers with visibility into important actions. Customers should be able to understand what the agent has searched, what it has selected, how much it will spend and when an order has been placed.

Security is equally important. Businesses will need systems that can identify authorised agents and separate them from harmful automated activity.

Recent developments in the industry show why this matters. Visa has introduced a Trusted Agent Protocol designed to help merchants verify AI agents and support safer agent-driven transactions.

Trust should therefore be treated as part of the customer experience, not just a technical security issue.

Start With Practical Use Cases

Businesses do not need to make every process autonomous overnight.

A better approach is to identify areas where agents can genuinely reduce effort for customers or employees.

Useful starting points could include:

1. Product discovery and recommendations
2. Automated reordering for frequently purchased products
3. Customer service and order tracking
4. Inventory monitoring and replenishment
5. Personalised offers
6. Restaurant and food recommendations
7. Travel and appointment bookings
8. Post-purchase support and returns

Once these use cases are working reliably, businesses can gradually allow agents to perform more complex tasks.

The Business Website Will Still Matter

Agentic commerce does not mean websites and applications will disappear.

They will continue to provide the brand experience, detailed information, customer support and direct relationship that businesses need. What changes is how customers may arrive at those experiences.

A customer might discover a business through an AI assistant rather than a traditional search engine. The agent may compare several options before presenting the business to the customer.

This makes brand information, product quality, reviews, pricing and service reliability even more important.

Businesses will have to compete not only for human attention, but also for inclusion in AI-generated recommendations.

What Businesses Should Do Before 2027

The transition to agentic commerce should begin with preparation rather than a complete technology overhaul.

Businesses should review their current commerce infrastructure, identify where their data is stored, check whether their systems provide real-time information and assess whether their APIs can support controlled external access.

They should also speak with technology and payment partners about emerging agentic commerce standards.

The companies that prepare early will have more time to test what works, establish security controls and understand how customers respond to AI-assisted buying.

The Road Ahead

Going into 2027, commerce is likely to become less dependent on customers manually moving through every step of the buying journey.

The basic idea is simple: customers express intent, AI understands that intent, businesses provide the right information and systems work together to complete the transaction.

For businesses, the opportunity is much bigger than adding a chatbot to a website. It is about creating commerce infrastructure that can communicate with intelligent agents while maintaining control, security and customer trust.

Agentic commerce will continue to develop as standards, payment systems and AI capabilities mature. Businesses that start preparing their data, technology and operations now can enter this new phase of commerce with a stronger foundation and a clearer understanding of where AI can create real value.