The Rise of AI Shopping Agents: How Agentic Commerce Will Transform E-Commerce in 2025

Imagine a customer who never visits your website. They never browse your product pages, read your descriptions, or click your carefully crafted CTAs. Instead, they tell their AI assistant what they need, and the AI handles everything—finding your products, comparing options, negotiating prices, and completing the purchase—all without human intervention.

This isn't science fiction. Agentic commerce is emerging as the next major structural shift in digital retail, and it's happening faster than most merchants realize. According to recent BCG research, AI agents will fundamentally change how customers discover, shop, and buy across the entire e-commerce ecosystem within the next 18–24 months.

In this guide, we'll explore what agentic commerce means, how AI shopping agents work, and most importantly—how to prepare your store for a future where your primary customer might be an algorithm.

What Is Agentic Commerce?

Agentic commerce refers to the use of AI agents that autonomously perform shopping tasks on behalf of consumers. Unlike traditional AI assistants that simply answer questions or provide recommendations, agentic AI takes action—searching for products, comparing prices, reading reviews, making purchase decisions, and completing transactions without requiring human approval for each step.

Think of it as the difference between asking a friend for restaurant recommendations versus having a personal assistant who books the reservation, orders your usual meal, and handles payment—all based on knowing your preferences.

The Evolution from Search to Agents

E-commerce has evolved through distinct phases:

We're now entering the Agent Era, where the customer journey may happen entirely within AI systems, with your website serving as a data source rather than a destination.

How AI Shopping Agents Work

Understanding the mechanics of AI shopping agents helps you prepare for their impact. Here's what happens when a consumer uses an AI agent to shop:

Step 1: Intent Understanding

The user expresses a need in natural language:

• "I need running shoes for trail running, under $150, with good arch support"
• "Find me a birthday gift for my mom who likes gardening"
• "Reorder my usual coffee beans when I'm running low"

The AI parses this into structured requirements: product category, features, price constraints, preferences, and urgency.

Step 2: Product Discovery

The agent searches across multiple sources:

• Product databases and catalogs
• E-commerce platform APIs
• Website content and structured data
• Review aggregators
• Price comparison services

This is where your product data becomes critical. Agents can only find and recommend products they can understand.

Step 3: Evaluation and Comparison

The AI evaluates options against user criteria:

• Feature matching against requirements
• Price analysis including shipping and taxes
• Review sentiment analysis
• Brand reputation assessment
• Availability and delivery timing

Agents don't get distracted by flashy design or emotional marketing. They evaluate based on data.

Step 4: Decision and Purchase

Based on evaluation, the agent either:

• Recommends options for human approval
• Makes autonomous purchases within pre-set parameters
• Negotiates with merchants for better terms
• Schedules purchases for optimal timing

The level of autonomy depends on user preferences and purchase significance.

Step 5: Post-Purchase Management

Agents continue working after purchase:

• Tracking shipments
• Handling returns if needed
• Providing feedback to improve future recommendations
• Reordering consumables automatically

Why Agentic Commerce Matters Now

Several converging factors are accelerating the shift to agentic commerce:

AI Capability Explosion

Large language models can now:

• Understand nuanced product requirements
• Navigate complex websites and APIs
• Make reasoned decisions based on multiple factors
• Learn from outcomes to improve over time

The technology has crossed the threshold from "interesting demo" to "practical tool."

Consumer Demand for Convenience

Modern consumers are overwhelmed by choice. The average online shopper:

• Visits 3–5 websites before purchasing
• Spends 15+ minutes researching products over $50
• Abandons 70% of shopping carts
• Experiences decision fatigue regularly

AI agents eliminate this friction by handling the research and comparison work.

Platform Investment

Major technology companies are investing heavily in shopping agents:

• Google is integrating shopping capabilities into AI assistants
• Amazon is developing Alexa-based autonomous purchasing
• Apple is building shopping features into Siri
• OpenAI and Anthropic are enabling agent capabilities in their models
• Startups are creating specialized shopping agents

When the biggest tech companies align on a direction, adoption follows quickly.

Early Adoption Signals

BCG research indicates that European e-commerce players must prepare now, as adoption is accelerating faster than expected. Early movers have a narrow window to establish advantage before agent-optimized competitors capture market share.

Impact on E-Commerce Businesses

Agentic commerce will reshape every aspect of online retail. Here's what changes:

Customer Acquisition Transforms

Traditional customer acquisition relies on:

• SEO to appear in search results
• Paid ads to capture attention
• Social media to build awareness
• Email marketing to nurture leads

In agentic commerce, you're not acquiring customers—you're acquiring agent recommendations. This requires:

• Structured product data that agents can parse
• API accessibility for agent queries
• Competitive pricing that survives algorithmic comparison
• Strong reviews that influence agent evaluations
• Reliable fulfillment that maintains agent trust

SEO Evolves to AEO

Search Engine Optimization becomes Agent Engine Optimization. Instead of optimizing for Google's ranking algorithm, you optimize for AI agent evaluation criteria:

The merchants who master AEO first will capture disproportionate agent-driven traffic.

Pricing Becomes Dynamic

When AI agents compare prices in real-time across competitors, static pricing becomes a liability. Successful merchants will need:

• Dynamic pricing algorithms that respond to market conditions
• Value-based positioning that justifies premium pricing
• Bundle strategies that complicate direct comparison
• Loyalty programs that create switching costs

Price transparency increases, but so does the opportunity for merchants who compete on value rather than cost alone.

Product Data Becomes Critical

Your product data is your storefront in agentic commerce. Agents evaluate:

• Completeness: Every relevant attribute filled
• Accuracy: Specifications match reality
• Freshness: Inventory and pricing current
• Structure: Machine-readable formats
• Richness: Detailed features and benefits

Poor product data means agents can't find you, can't evaluate you accurately, or can't recommend you confidently.

Reviews Gain Influence

AI agents heavily weight review data in their evaluations. They can:

• Analyze sentiment across hundreds of reviews
• Identify patterns in complaints or praise
• Weight recent reviews more heavily
• Detect fake or incentivized reviews

Authentic positive reviews become even more valuable, while negative reviews become more damaging.

Preparing Your Store for Agentic Commerce

The transition to agentic commerce is happening whether you prepare or not. Here's how to position your store for success:

Step 1: Audit Your Product Data

Start by evaluating your current product information:

Completeness Check:

• All products have titles, descriptions, and images
• Technical specifications are filled for relevant products
• Pricing includes all costs (shipping, taxes where applicable)
• Inventory status is accurate and real-time
• Category and attribute data is complete

Structure Check:

• Using schema.org Product markup
• Structured data validates without errors
• Product identifiers (GTIN, MPN, SKU) are present
• Variant relationships are properly defined

Quality Check:

• Descriptions are accurate and detailed
• Images show products clearly
• Specifications match actual products
• No conflicting information across fields

Step 2: Implement Structured Data

Ensure your store uses proper schema markup that agents can parse:

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Trail Running Shoe Pro X",
  "description": "Professional trail running shoe with enhanced arch support...",
  "brand": {"@type": "Brand", "name": "YourBrand"},
  "offers": {
    "@type": "Offer",
    "price": "129.99",
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.7",
    "reviewCount": "234"
  }
}

AI-native platforms like Runner AI generate this structured data automatically, ensuring your products are agent-ready from day one.

Step 3: Build API Accessibility

Consider how agents will access your product data:

• Product feeds: Maintain updated feeds for major platforms
• API endpoints: If possible, provide programmatic access to catalog
• Sitemap optimization: Ensure all products are discoverable
• Data freshness: Update inventory and pricing in real-time

Step 4: Optimize for Agent Evaluation

Think about how an AI would evaluate your products:

Competitive Positioning:

• How do your prices compare to alternatives?
• What unique features differentiate your products?
• Why should an agent recommend you over competitors?

Trust Signals:

• Do you have sufficient reviews?
• Is your return policy clear and favorable?
• Do you have trust badges and certifications?

Fulfillment Reliability:

• Can you deliver on promised timelines?
• Is your shipping cost competitive?
• Do you have a track record of successful deliveries?

Step 5: Cultivate Authentic Reviews

Reviews will heavily influence agent recommendations:

• Request reviews from satisfied customers
• Respond to negative reviews professionally
• Never fake reviews—agents will detect patterns
• Encourage detailed reviews that mention specific features
• Monitor review sentiment and address recurring issues

Step 6: Choose an Agent-Ready Platform

Your e-commerce platform determines how easily you can adapt to agentic commerce. Look for:

• Automatic structured data generation
• Real-time inventory synchronization
• API-first architecture for agent access
• Dynamic pricing capabilities
• AI-native features that understand the agent ecosystem

Runner AI is built for this future—with AI infrastructure that ensures your store is optimized for both human shoppers and AI agents from the start.

The AI-Native Advantage

Stores built on AI-native platforms have inherent advantages in agentic commerce:

Automatic Optimization

AI-native platforms continuously optimize your store for both human and agent visitors. They understand what agents look for and ensure your data meets those requirements automatically.

Structured Data by Default

Instead of manually implementing schema markup, AI-native platforms generate comprehensive structured data as part of normal operations. Every product is agent-ready without extra work.

Real-Time Synchronization

AI-native systems maintain real-time accuracy across all channels—inventory, pricing, product details—ensuring agents always have current information.

Intelligent Pricing

Built-in AI can help you price competitively while maintaining margins, responding to market conditions that agents will evaluate.

Continuous Learning

As agent behavior patterns emerge, AI-native platforms adapt automatically, keeping your store optimized for evolving agent preferences.

Timeline: When Will Agentic Commerce Matter?

Based on current adoption curves and technology development:

The window to prepare is now. Merchants who wait until agents are mainstream will find themselves playing catch-up against competitors who optimized early.

Common Concerns About Agentic Commerce

"Will agents eliminate the need for branding?"

No, but branding's role shifts. Agents will still consider brand reputation, customer loyalty, and unique value propositions. Strong brands that deliver consistent quality will earn agent trust and recommendations. However, brands can't rely on emotional marketing alone—they need substance that agents can verify.

"Will this commoditize all products?"

For truly commodity products, yes—agents will optimize purely on price and availability. But for products with genuine differentiation, agents will recognize and communicate that value. The key is having real differentiation, not just marketing differentiation.

"What about the shopping experience?"

Many consumers enjoy browsing and discovering products. Agentic commerce won't eliminate this—it will coexist with traditional shopping. Some purchases (routine, utilitarian) will shift to agents while others (experiential, emotional) will remain human-driven.

"How do I compete with Amazon?"

Agents level the playing field in some ways. They evaluate all merchants against the same criteria, potentially surfacing smaller merchants who excel in specific areas. Your advantage lies in specialization, unique products, superior service, or niche expertise that agents can recognize and recommend.

Action Steps: Start Preparing Today

Don't wait for agentic commerce to arrive. Start preparing now:

This Week:

1. Audit your product data completeness
2. Check your structured data implementation
3. Review your competitive positioning

This Month:

1. Fill gaps in product information
2. Implement or improve schema markup
3. Develop a review generation strategy

This Quarter:

1. Evaluate your platform's agent-readiness
2. Consider migration to an AI-native platform
3. Build processes for maintaining data quality

Ongoing:

1. Monitor agent commerce developments
2. Test how agents find and evaluate your products
3. Optimize based on emerging best practices

Conclusion: The Future Belongs to the Prepared

Agentic commerce represents the most significant shift in e-commerce since the smartphone. The merchants who prepare now—optimizing their data, choosing the right platforms, and building agent-friendly operations—will thrive as AI shopping agents become mainstream.

The merchants who ignore this shift will find themselves invisible to a growing segment of commerce, watching competitors capture sales they never knew they lost.

Runner AI is built for this future. With AI-native architecture, automatic structured data, and continuous optimization, your store is ready for both today's human shoppers and tomorrow's AI agents.

The question isn't whether agentic commerce will transform e-commerce. It's whether you'll be ready when it does.

Frequently Asked Questions

What are AI shopping agents?

AI shopping agents are artificial intelligence systems that autonomously perform shopping tasks on behalf of consumers. Unlike simple chatbots or recommendation engines, agents can search for products, compare options, make purchase decisions, and complete transactions—handling the entire shopping journey without requiring human intervention for each step.

How will agentic commerce affect small businesses?

Agentic commerce can benefit small businesses by leveling the playing field. AI agents evaluate all merchants against objective criteria like product quality, pricing, reviews, and fulfillment reliability—not marketing budget. Small businesses that excel in their niche can earn agent recommendations alongside larger competitors. The key is having excellent product data and genuine differentiation.

When should I start preparing for AI shopping agents?

Now. While mainstream adoption is still 1–2 years away, the merchants who optimize early will establish advantages that compound over time. Start by auditing your product data, implementing structured markup, and ensuring your platform can adapt to agent requirements.

Do I need to rebuild my store for agentic commerce?

Not necessarily, but your platform matters. Stores on AI-native platforms like Runner AI are automatically optimized for agent discovery. Traditional platforms may require significant manual work to implement proper structured data, maintain real-time accuracy, and meet agent requirements.

Ready to future-proof your store for agentic commerce? Try Runner AI free and build on a platform designed for both human shoppers and AI agents.