AI Agents Are Changing Online Shopping: The Future of Agentic Commerce 2026

Introduction

Online shopping has changed dramatically over the last two decades. Customers once had to visit physical stores, but e-commerce made it possible to search for products, compare prices, read reviews, and place orders from a computer or smartphone. Now, another major transformation is beginning: AI agents are starting to shop on behalf of consumers.

This new model is commonly called agentic commerce. Instead of simply giving a recommendation, an AI agent can understand a shopping goal, research products, compare options, help build a basket, and, where supported and authorized, assist with completing a purchase. IBM defines agentic commerce as buying and selling in which AI agents can research, negotiate, and complete transactions on behalf of consumers or businesses.AI Agents

In 2026, agentic commerce is moving from an experimental concept toward real-world retail applications. Google Cloud describes the change as a move from passive digital interactions toward AI agents capable of carrying out complex, multi-step shopping activities.AI Agents

This development could change how consumers discover products, how retailers compete, how advertising works, how payments are processed, and how brands build relationships with customers.AI Agents

1. What Is an AI Shopping Agent?

An AI shopping agent is software powered by artificial intelligence that can help perform multiple steps of the shopping process. AI Agents

A traditional search engine generally provides links. A traditional recommendation system might suggest products based on previous activity.AI Agents

An AI agent can potentially go further.AI Agents

A shopper might say:

“Find me a laptop suitable for schoolwork, with good battery life, within my budget.”

The agent could interpret the requirements, search available products, compare specifications, identify suitable choices, explain the differences, and help the shopper decide.

With appropriate authorization and supported payment systems, an agent can potentially continue through checkout.AI Agents

The important difference is action.

The AI is not merely answering a question. It can potentially perform a sequence of tasks on the user’s behalf.

2. From E-Commerce to Agentic Commerce

Traditional e-commerce is largely based on human interaction.AI Agents

The shopper: AI Agents

1. Opens a website.
2. Searches for a product.
3. Filters results.
4. Reads descriptions.
5. Compares products.
6. Adds an item to a cart.
7. Enters payment information.
8. Completes checkout.

Agentic commerce changes this process.

The shopper can communicate a goal, while the AI handles more of the research and decision-making process.

Mastercard describes agentic commerce as the intersection between agentic AI and online shopping, where AI systems can reason, plan, and act on behalf of consumers.

This could make shopping less about navigating websites and more about communicating intentions.AI Agents

3. Why AI Agents Are Becoming Popular

Online shopping provides an enormous amount of choice.

That is useful, but it can also create a problem known as choice overload.

A shopper searching for headphones, shoes, computers, furniture, or other products may find hundreds or thousands of options.

Comparing all of them takes time.

AI agents can reduce this burden by narrowing the choices according to the shopper’s requirements.

Instead of asking consumers to examine hundreds of products, the AI can potentially produce a smaller list of suitable options.AI Agents

This makes shopping more efficient.

4. Personalized Shopping

Personalization is one of the biggest advantages of AI shopping agents.

An AI system can potentially consider factors such as:AI Agents

• Budget
• Product requirements
• Preferred brands
• Previous purchases
• Delivery requirements
• Product specifications
• Ratings and reviews
• Availability
• Personal preferences

For example, two people searching for a laptop may receive different recommendations.

One might prioritize gaming performance.AI Agents

Another might care more about battery life, portability, and schoolwork.

An agent can potentially understand these differences through conversation rather than requiring the user to configure dozens of filters.

5. AI Agents Can Compare Products

Comparison is one of the most time-consuming parts of online shopping.

A customer may need to open multiple websites and compare prices, specifications, delivery times, warranties, and reviews.

AI agents can potentially bring these details together.

For example, an agent might compare three smartphones according to:

• Price
• Camera features
• Battery
• Storage
• Performance
• Software support

The shopper can then make a decision based on a concise explanation rather than visiting numerous product pages.

This could make product research significantly faster.

6. Price Comparison and Deals

AI agents can also change how consumers search for discounts.

Instead of manually checking multiple stores, an agent can potentially compare prices and identify available offers.

The UK Information Commissioner’s Office has discussed the possibility of shopping agents looking for sales, sourcing financing arrangements, and even negotiating prices in the future. It also emphasizes that privacy must remain protected as these technologies develop.

If this becomes widespread, retailers may have to compete not only for human attention but also for AI recommendations.

7. The Rise of the “AI Customer”

Traditional businesses think about their customers as people.

Agentic commerce introduces another layer.

The human remains the customer, but an AI system may increasingly become the interface through which that customer shops.

This changes how retailers think about product information.

A product page written only for humans may not be enough.

Product information must also be accurate, structured, current, and understandable to AI systems.

Google Cloud describes this concept as an “invisible shelf,” where AI agents discover and recommend products outside the traditional visual shopping experience.

8. Product Data Becomes More Important

For AI agents to recommend products accurately, they need reliable information.

Important product data can include:

• Product name
• Price
• Availability
• Size
• Color
• Specifications
• Materials
• Warranty
• Delivery information
• Return policy
• Images
• Reviews

If information is incomplete or inaccurate, an AI agent may misunderstand the product.

Retailers will therefore need to improve their product data.

In the agentic-commerce era, good data becomes part of the customer experience.

9. The End of Traditional Product Search?

Traditional search is unlikely to disappear completely.

Many people will still want to browse websites, look at images, read reviews, and make decisions themselves.

However, AI agents could change how people begin their shopping journeys.

Instead of typing a short keyword such as “running shoes,” a consumer might describe a complete need.

For example:

“I need comfortable shoes for regular walking, under my budget, available in my size.”

The AI can interpret the intent and produce more relevant results.

This represents a shift from keyword search to intent-based shopping.

10. Conversational Shopping

AI makes online shopping more conversational.

Instead of navigating menus, shoppers can ask questions naturally.

They can say:

• “Which one has better battery life?”
• “Show me cheaper alternatives.”
• “Which option is better for students?”
• “Does this model have enough storage?”
• “Compare these two.”
• “Find something similar but less expensive.”

The agent can maintain context throughout the conversation.

This creates a shopping experience that feels more like talking to an assistant than operating a traditional website.

11. AI Agents and Retailers

Retailers are also developing their own AI systems.

A retailer can use AI to help customers search its catalog, answer questions, recommend products, and support customer service.

For example, Albertsons has introduced AI tools for shopping-related tasks such as finding products, planning meals, and creating shopping lists. The company says AI-assisted shoppers have shown higher average order values in some of these experiences.

This demonstrates that AI can influence not only convenience but also retail business performance.

12. AI Can Increase Basket Size

A traditional search often focuses on one product.

AI can understand the broader goal behind a purchase.

Imagine someone planning a birthday party.

Instead of simply searching for one item, an AI agent could potentially help identify decorations, food, drinks, accessories, and other relevant products.

This can create larger shopping baskets.

Retailers therefore have an incentive to develop AI systems that understand complete customer goals rather than individual product searches.

13. AI Agents and Small Businesses

Agentic commerce could create both opportunities and challenges for small businesses.

A small company may have difficulty competing with major retailers for advertising space and search visibility.

However, if its product information is accurate and its prices and customer experience are competitive, AI agents could potentially discover and recommend its products.

This creates a new type of competition.

The biggest company does not automatically have to win every AI recommendation.

Product relevance, price, availability, reviews, reliability, and data quality can all matter.

14. Marketing Is Changing

Traditional online advertising often focuses on getting humans to click.

Agentic commerce changes the process.

The AI may see a product first, evaluate it, compare it with alternatives, and then present a recommendation to the consumer.

Bain describes this as a major shift in demand generation, arguing that brands increasingly need to become visible to AI systems because agents can influence which products consumers consider.

Marketing teams will therefore need to think about both human audiences and AI-mediated discovery.

15. The New SEO: Optimization for AI

Search engine optimization has traditionally focused on helping websites appear in search results.

Agentic commerce introduces another challenge: helping products become understandable and discoverable to AI systems.

Businesses may need to focus on:

• Accurate product information
• Structured data
• Clear policies
• Reliable inventory information
• Competitive pricing
• Strong customer reviews
• Machine-readable catalogs

This does not mean traditional SEO becomes irrelevant.

Instead, product discovery may increasingly happen across multiple AI-powered systems.

16. Payments Become More Important

One of the hardest parts of agentic commerce is payment.

A human shopper normally enters payment information and confirms a purchase.

An AI agent introduces another participant into the process.

Payment systems need to know:

• Who is the customer?
• Which agent is acting?
• What purchase was authorized?
• What spending limit exists?
• Was the transaction legitimate?
• Who is responsible if something goes wrong?

Mastercard identifies intent, fraud prevention, and accountability as important challenges for agentic payments.

This means the future of shopping depends not only on AI but also on secure payment infrastructure.

17. Human Approval Still Matters

Not everyone wants an AI to make purchases independently.

Consumers may be comfortable allowing an agent to research products but want to approve the final transaction.

Research released in June 2026 found strong consumer interest in agentic shopping, while also showing that many consumers want safeguards and human approval before AI completes purchases.

This suggests that agentic commerce will probably develop gradually.

Consumers may choose different levels of automation.

18. Different Levels of Automation

Shopping agents do not have to be completely autonomous.

There can be several levels.

Level 1: Recommendations

The AI suggests products.

Level 2: Research

The AI compares products and prices.

Level 3: Basket Building

The AI selects suitable items and prepares a basket.

Level 4: Checkout Assistance

The AI guides the shopper through checkout.

Level 5: Authorized Purchases

The AI can complete purchases within rules set by the user.

Level 6: Highly Automated Shopping

The AI can handle recurring purchases and more complex shopping tasks with limited intervention.

McKinsey describes agentic commerce as an automation curve in which consumers gradually delegate more parts of the shopping process to AI.

19. Recurring Purchases

One especially useful application could be routine shopping.

For example, consumers regularly purchase household products.

An authorized agent could monitor preferences and help identify when supplies need to be replaced.

Instead of manually searching every time, the user could establish rules about what can be purchased and within what limits.

This could save time.

However, clear controls are essential to prevent unwanted purchases.

20. Trust Is the Biggest Challenge

Technology can be impressive, but consumers need to trust it.

People may ask:

• Will the AI choose the correct product?
• Will it misunderstand my request?
• Will it select the cheapest option rather than the best option?
• Is the product authentic?
• Will it make a purchase I did not intend?
• What happens if an item arrives damaged?

Trust will determine how quickly agentic commerce develops.

A powerful AI agent is not useful if consumers are afraid to give it permission to act.

21. Privacy Concerns

Shopping agents may need access to personal information to provide useful recommendations.

This can include:

• Shopping history
• Preferences
• Addresses
• Payment information
• Budgets
• Household information
• Purchase patterns

This creates privacy concerns.

Companies need strong policies explaining what data is collected, why it is collected, how long it is stored, and who can access it.

The UK ICO has specifically warned that agentic shopping should not come at the expense of data privacy.

22. Security Risks

AI agents can also create new security challenges.

An agent that can interact with websites, accounts, and payment systems needs carefully controlled permissions.

If an AI agent has excessive access, a security problem could have larger consequences.

Security systems will therefore need to distinguish between:

• The human user
• The AI agent
• The retailer
• The payment provider
• Other connected services

Strong authentication and authorization will become essential.

23. Fraud Prevention

Fraud prevention becomes more complicated when AI participates in transactions.

Payment systems need to distinguish legitimate automated activity from malicious automation.

This could require new approaches to identity, transaction authorization, and fraud detection.

AI can also help defend against fraud by analyzing transaction patterns.

The result may be an ongoing technological competition between systems attempting to automate fraudulent activity and systems designed to detect it.

24. The Role of Loyalty Programs

AI shopping could change loyalty programs.

Traditionally, retailers try to build direct relationships with customers through websites, mobile applications, rewards programs, and email marketing.

But if an AI agent becomes the main shopping interface, the retailer may lose some direct interaction with the consumer.

Reuters reported in August 2026 that retailers are increasingly concerned about losing direct customer relationships as AI shopping assistants take on more of the shopping process.

This means loyalty programs may become more important.

Retailers will need reasons for consumers to maintain direct relationships with their brands.

25. The “Invisible Storefront”

In traditional e-commerce, the storefront is a website or application.

In agentic commerce, the customer may never visit the retailer’s website.

The AI could search catalogs, compare products, and help complete the purchase through an AI interface.

This creates what can be called an invisible storefront.

The retailer still exists, but the customer interaction happens through an AI intermediary.

That could fundamentally change website traffic and digital marketing.

26. The Future of Online Reviews

Reviews are another area that could change.

AI agents may analyze thousands of reviews quickly.

Instead of a consumer reading dozens of comments, the AI could summarize common positive and negative themes.

However, this also creates a challenge: fake reviews and manipulated information could influence AI recommendations.

Retailers and AI platforms will therefore need better methods for determining whether product information and reviews are trustworthy.

27. AI Agents and Global E-Commerce

Agentic commerce could make international shopping easier.

An AI agent could potentially compare products across countries, interpret foreign-language product information, calculate costs, and help users understand delivery options.

Translation can remove one major barrier.

However, international commerce still involves taxes, regulations, shipping, returns, payment differences, and product standards.

AI can help consumers understand these issues, but users should still verify important purchase information before completing transactions.

28. The Future of Customer Service

AI agents are also changing what happens after a purchase.

An agent could potentially help with:

• Order tracking
• Delivery questions
• Returns
• Refund requests
• Warranty information
• Product troubleshooting

This could reduce the amount of time consumers spend interacting with traditional customer-service systems.

For businesses, automated customer service could reduce repetitive workloads while allowing human employees to focus on complicated cases.

29. Agent-to-Agent Commerce

A particularly interesting future possibility is communication between AI agents.

A consumer’s shopping agent could interact with a retailer’s AI agent.

One system represents the buyer.

Another represents the seller.

They could exchange product information, availability, policies, and transaction details.

McKinsey notes that emerging protocols are being developed to support interoperability, identity, and payments in agentic commerce.

This could eventually create an internet where software agents conduct many commercial interactions on behalf of humans.

30. The Economic Impact

The economic potential is significant.

McKinsey estimates that agentic AI could mediate between $3 trillion and $5 trillion of global consumer commerce by 2030 under moderate scenarios.

This is a projection, not a guaranteed outcome.

Nevertheless, it demonstrates why technology companies, retailers, payment providers, and financial institutions are investing in the area.

Agentic commerce could become a major digital business channel.

31. What Retailers Need to Do

Retailers preparing for agentic commerce should focus on the basics first.

Their product information should be accurate.

Prices should be current.

Inventory information should be reliable.

Policies should be clear.

Product descriptions should contain useful specifications.

Customer reviews should be trustworthy.

Payment and authentication systems should support secure automated interactions.

A retailer does not necessarily need a complicated AI system immediately.

It first needs reliable digital infrastructure.

32. The Importance of Machine-Readable Information

AI agents need information they can understand.

Retailers therefore need structured product catalogs and consistent information.

If one page says an item is available while another says it is out of stock, an AI system may make an incorrect recommendation.

Data quality is therefore becoming a competitive advantage.

In agentic commerce, inaccurate information can directly lead to lost sales.

33. Will Human Shopping Disappear?

Probably not.

People enjoy browsing.

They enjoy discovering new products, watching demonstrations, reading stories, comparing designs, and visiting physical stores.

AI agents are more likely to change shopping than completely eliminate human involvement.

Consumers will decide how much control to delegate.

Some may use AI only for research.

Others may allow it to manage routine purchases.

The future is likely to be a combination of human decisions and AI assistance.

34. The Future Shopping Experience

Imagine a future shopping conversation:

A customer says they need a new laptop for school.

The AI asks about budget and requirements.

It compares available models.

It checks specifications and reviews.

It explains the best choices.

The customer selects one.

The AI checks the final price and delivery details.

The customer approves the purchase.

The order is completed securely.

This experience could reduce a process that currently takes an hour to a few minutes.

That is the central promise of agentic commerce: less searching, less comparing, and less repetitive work.

Conclusion

AI agents are changing online shopping by moving e-commerce from a model based primarily on browsing and clicking toward a model based on conversation, intent, automation, and delegation.

Traditional online shopping requires consumers to search for products, compare options, navigate websites, and complete checkout themselves. Agentic commerce allows AI systems to perform increasing portions of these tasks on behalf of users.

In 2026, this transformation is already becoming visible. Retailers are experimenting with AI shopping assistants, major technology companies are developing agentic commerce infrastructure, and payment providers are working on secure ways for AI systems to participate in transactions.

The benefits could be substantial. Consumers can save time, compare products more efficiently, discover personalized recommendations, and potentially automate routine purchases. Retailers can use AI to improve customer experiences, increase basket sizes, automate service, and reach consumers through new channels.

But the challenges are equally important.

Privacy, security, fraud, inaccurate product information, unwanted purchases, accountability, and loss of direct customer relationships all need to be addressed.

The most successful agentic commerce systems will therefore not simply be the most autonomous. They will be the systems that combine convenience with control, intelligence with transparency, and automation with security.

The future of online shopping may not require consumers to visit dozens of websites and manually compare hundreds of products. Instead, people may increasingly explain what they need while AI agents handle much of the work.

The human will remain the decision-maker, but the AI could become the shopper’s digital assistant.

That is the fundamental change behind agentic commerce—and it could become one of the most important transformations in e-commerce during the next decade.