Agentic Commerce Protocol (ACP): The Complete Guide to AI-Native Shopping
Understand the Agentic Commerce Protocol powering ChatGPT Shopping and AI-native commerce. Learn how ACP works, its impact on e-commerce, and how to prepare your business.

The future of e-commerce isn’t about better websites or smarter ads—it’s about AI agents autonomously purchasing products on behalf of consumers. The Agentic Commerce Protocol (ACP), developed by OpenAI and Stripe, is the infrastructure making this possible. Understanding ACP isn’t optional for serious e-commerce businesses; it’s essential for survival in the AI-native commerce era.
What is the Agentic Commerce Protocol (ACP)?
The Agentic Commerce Protocol is an open standard that enables AI agents—like ChatGPT—to discover products, evaluate options, process payments, and complete transactions autonomously on behalf of human users.
In simple terms: ACP is the “language” that lets AI shopping assistants talk to your online store.
Core Components of ACP
The protocol consists of three integrated layers:
1. Discovery Layer
- Standardized product feed formats optimized for AI consumption
- Semantic product descriptions that AI can understand
- Merchant capability declarations (payment methods, shipping, returns)
2. Transaction Layer
- Secure payment credential delegation via Stripe
- Order creation and management APIs
- Real-time inventory and pricing verification
3. Fulfillment Layer
- Shipping and delivery integrations
- Order tracking protocols
- Returns and refund handling
The Key Players Behind ACP
| Organization | Role | Contribution |
|---|---|---|
| OpenAI | Protocol Design & AI Platform | ChatGPT integration, AI agent capabilities, feed processing |
| Stripe | Payment Infrastructure | Shared Payment Tokens, secure credential delegation, merchant services |
| Merchants | Product Catalog Providers | Product data, inventory, fulfillment, customer service |
| Feed Providers | Data Intermediaries | Feed optimization, multi-platform distribution, data standardization |
How Agentic Commerce Actually Works
A Real Transaction Flow
Let’s trace an actual AI-native purchase through the system:
STEP 1: User Intent
User: "Buy me a birthday gift for my wife. She loves gardening
and her birthday is in 3 days. Budget around $75."
STEP 2: AI Agent Processing
ChatGPT:
├── Parses intent: gift, gardening, female recipient, 3-day delivery, ~$75
├── Queries merchant feed database
├── Filters for: delivery ≤3 days, price $50-100, category: garden/gifts
├── Ranks results by relevance, reviews, delivery reliability
└── Considers user's previous gift-giving patterns
STEP 3: Product Presentation
ChatGPT presents 4-6 curated options:
- Personalized garden tool set ($69, 2-day delivery)
- Raised herb garden kit ($74, 1-day delivery)
- Custom garden stake with engraving ($65, 2-day delivery)
STEP 4: User Decision
User: "The herb garden kit looks perfect. Get that one."
STEP 5: Transaction Execution
ChatGPT:
├── Retrieves saved shipping address (user's home)
├── Confirms gift wrapping availability
├── Retrieves payment token via Stripe SPT
├── Submits order to merchant via ACP
├── Confirms order and provides tracking
└── Sends receipt to user's email
Total time from intent to purchase: ~30 seconds
Technical Architecture
┌─────────────────────────────────────────────────────────────────┐
│ USER INTERFACE │
│ (ChatGPT, Voice Assistant, Other AI Agents) │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ AI COMMERCE ENGINE │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────────┐ │
│ │ Intent │ │ Product │ │ Recommendation │ │
│ │ Parser │──│ Matching │──│ Engine │ │
│ └─────────────┘ └─────────────┘ └─────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ AGENTIC COMMERCE PROTOCOL (ACP) │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────────┐ │
│ │ Discovery │ │ Transaction │ │ Fulfillment │ │
│ │ APIs │ │ APIs │ │ APIs │ │
│ └─────────────┘ └─────────────┘ └─────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
│
┌─────────────────┼─────────────────┐
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Merchant │ │ Payment │ │ Shipping │
│ Systems │ │ (Stripe) │ │ Partners │
└──────────────┘ └──────────────┘ └──────────────┘
Why ACP Matters for Your Business
The Market Opportunity
The shift to AI-native commerce represents one of the largest distribution channel changes in e-commerce history:
| Metric | Current (2025) | Projected (2027) |
|---|---|---|
| AI-assisted purchases | $142B | $490B |
| Consumers using AI shopping | 39% | 65%+ |
| Share of product discovery via AI | 12% | 35%+ |
| Average order value (AI-assisted) | +18% higher | +25% higher |
Source: Industry analysis aggregated from Digiday, Search Engine Journal, and e-commerce research firms.
Why AI Commerce Converts Better
AI-assisted shopping has fundamentally different economics:
1. Higher Purchase Intent Users asking AI for products are typically further down the purchase funnel than casual browsers. They’ve moved beyond “just looking” to “help me buy.”
2. Reduced Decision Fatigue Instead of comparing 47 search results, users see 3-5 curated options. Less friction = higher conversion.
3. Contextual Recommendations AI understands use case, preferences, and constraints—leading to better-matched products with fewer returns.
4. Frictionless Checkout Instant Checkout eliminates the 70%+ cart abandonment that plagues traditional e-commerce.
Getting Your Business ACP-Ready
Step 1: Assess Your Current Infrastructure
Product Data Audit Checklist:
□ Do you have a structured product feed?
□ Are all products accurately categorized?
□ Do descriptions explain use cases, not just features?
□ Is inventory updated in real-time?
□ Are prices current and competitive?
□ Do you have high-quality images for all products?
□ Are GTINs/product identifiers accurate?
□ Can you handle increased order volume?
□ Is your shipping data accurate (times, costs)?
□ Are your return policies clearly defined?
Step 2: Optimize Product Data for AI Understanding
Traditional SEO optimizes for keywords. ACP optimization focuses on semantic understanding.
Traditional Product Title:
Widget Pro X500 Silver 32GB
AI-Optimized Product Title:
TechBrand Widget Pro X500 - 32GB Portable External SSD Drive
for Fast File Transfer, Silver Aluminum Case, USB-C Compatible
Why it works better:
- Brand name included (trust signal)
- Product type explicitly stated (categorization)
- Primary use case mentioned (intent matching)
- Key differentiators present (decision support)
- Compatibility noted (reduces return risk)
Step 3: Structure Descriptions for AI Parsing
AI agents parse descriptions differently than humans browsing. Structure yours for both:
Optimized Description Structure:
[Opening Summary - 1-2 sentences, primary use case and key benefit]
The Widget Pro X500 transfers large files in seconds, making it
perfect for photographers, videographers, and creative professionals
who need reliable portable storage.
[Key Features - Bulleted, specific, quantified]
• Read speeds up to 1050 MB/s - transfer a 4K movie in under 30 seconds
• 32GB capacity - stores approximately 8,000 photos or 8 hours of 4K video
• Durable aluminum case - survives drops up to 6 feet
• USB-C with USB-A adapter included - works with any computer
[Use Cases - Scenario-based, helps AI match to user needs]
IDEAL FOR:
- Creative professionals backing up shoots on location
- Business travelers needing fast access to presentations
- Gamers expanding console storage
- Students managing large project files
[Specifications - Structured data for comparison]
TECHNICAL SPECIFICATIONS:
- Capacity: 32GB
- Interface: USB 3.2 Gen 2x2
- Read Speed: 1050 MB/s
- Write Speed: 1000 MB/s
- Dimensions: 2.1 x 0.8 x 0.4 inches
- Weight: 1.6 oz
[Compatibility]
Works with: Windows 10/11, macOS 10.14+, PS5, Xbox Series X|S
Step 4: Implement Required Technical Elements
Feed Requirements for ACP:
| Field | Requirement | Notes |
|---|---|---|
title | Natural language, descriptive | Include brand, product type, key attributes |
description | Comprehensive, structured | Use cases, features, specifications |
price | Current, accurate | Must match landing page |
availability | Real-time | Updates within 1 hour of inventory change |
shipping_time | Accurate estimate | Critical for delivery-sensitive purchases |
gtin | Valid identifier | Required for branded products |
brand | Accurate | Required for discoverability |
product_category | Precise | Use deepest applicable category |
image_link | High-quality | Minimum 800x800px recommended |
Step 5: Enable Transaction Readiness
For Instant Checkout eligibility:
Payment Integration:
- Stripe Connect account (or compatible processor)
- Support for Shared Payment Tokens (SPT)
- Real-time authorization capability
Order Management:
- API-based order creation
- Instant order confirmation
- Real-time tracking updates
- Programmatic returns processing
Customer Service:
- Clear contact information
- Response time commitments
- Dispute resolution process
Optimization Strategies for ACP Discovery
Strategy 1: Semantic Product Clustering
Group products by use case, not just category:
Traditional hierarchy:
Electronics > Audio > Headphones > Wireless
AI-optimized clustering:
Working from home → Noise-cancelling headphones for focus
Running/Exercise → Sports earbuds, sweat-resistant
Commuting → Compact wireless earbuds, long battery
Gaming → Low-latency wireless headsets
Strategy 2: Conversational Keyword Integration
Include natural language phrases people actually use:
Instead of: “Bluetooth 5.2, 40hr battery, ANC” Include: “wireless headphones that last all day on a single charge with noise cancellation for noisy offices”
Strategy 3: Review Optimization for AI Synthesis
AI agents synthesize customer reviews. Optimize your review ecosystem:
- Encourage detailed reviews mentioning specific use cases
- Respond to negative reviews with helpful solutions
- Highlight verified purchases for credibility
- Request photos/videos in review requests
Strategy 4: Dynamic Pricing Signals
AI agents factor in pricing competitiveness:
- Use
sale_priceattributes to highlight deals - Implement
price_effective_datefor limited offers - Consider
loyalty_pricefor member pricing - Ensure prices are competitive within ±10% of market
Measuring ACP Success
Key Performance Indicators
Discovery Metrics:
- AI impression share (products shown in AI results)
- Click-through rate from AI recommendations
- Conversion rate from AI-referred traffic
Transaction Metrics:
- Instant Checkout completion rate
- Average order value from AI purchases
- Return rate from AI-referred orders
Customer Metrics:
- Repeat purchase rate from AI-acquired customers
- Customer lifetime value from AI channel
- Net promoter score from AI purchases
Attribution Tracking
Track AI-sourced traffic distinctly:
UTM Parameters for ACP Traffic:
utm_source=chatgpt
utm_medium=acp
utm_campaign=instant_checkout
Identify Instant Checkout Orders:
order_source=acp_instant_checkout
referrer_type=ai_agent
Common ACP Implementation Mistakes
Mistake 1: Treating AI Feeds Like Traditional Feeds
Wrong approach: Copy your Google Shopping feed directly to ACP Right approach: Optimize descriptions for conversational understanding
Mistake 2: Ignoring Shipping Data
Impact: AI agents heavily weight delivery time. Inaccurate shipping data causes:
- Products filtered from time-sensitive searches
- Customer dissatisfaction and disputes
- Lower rankings in future queries
Mistake 3: Static Inventory
Impact: AI agents verify inventory at transaction time. Selling out-of-stock items causes:
- Failed transactions
- Negative merchant scoring
- Reduced visibility
Mistake 4: Keyword Stuffing
Impact: AI understands context, not keyword density. Keyword-stuffed content:
- Performs worse in semantic matching
- Creates poor user experience
- May be penalized in rankings
The Road Ahead: ACP Evolution
Near-Term (2026)
- Expanded merchant onboarding globally
- Enhanced personalization based on purchase history
- Voice commerce integration (ChatGPT Voice + shopping)
- Multi-item cart and bundle recommendations
Medium-Term (2027)
- Autonomous reordering for consumables
- Predictive purchasing suggestions
- Cross-merchant comparison shopping
- Integration with smart home devices
Long-Term (2028+)
- Fully autonomous AI purchasing agents
- Subscription and service commerce
- B2B agentic commerce
- Integrated logistics optimization
Frequently Asked Questions
Is ACP the same as Google Shopping?
No. While both involve product feeds, they’re fundamentally different:
- Google Shopping: Keyword-based matching, ad-driven visibility
- ACP: Semantic understanding, conversation-driven discovery, transaction capability
Do I need to use Stripe for ACP?
Currently, Stripe is the primary payment partner for ACP Instant Checkout. Alternative payment processors may be supported in the future. For Instant Checkout eligibility, Stripe integration is currently required.
How do I get my products in ChatGPT shopping?
Current pathways:
- Sell through a participating marketplace (Etsy is currently primary)
- Apply for merchant partnership through OpenAI (limited access)
- Work with feed management platforms preparing for ACP expansion
- Ensure strong organic presence for web-indexed products
Will ACP replace traditional e-commerce?
No—ACP is an additional channel, not a replacement. Traditional e-commerce websites remain essential for:
- Brand building and storytelling
- Complex product configurations
- Customer service and support
- Direct customer relationships
How much does ACP participation cost?
Costs vary by integration method:
- Marketplace participation: Standard marketplace fees apply
- Direct merchant integration: Transaction fees (typically 2.9% + $0.30)
- Feed optimization: Platform subscription costs
Related Resources
- ChatGPT Shopping Guide: How to Use AI for Product Discovery
- How to Optimize Product Feeds for ChatGPT Shopping
- OpenAI Commerce Feed Specifications
- Shopping Feed Management Trends 2025
- How to Optimize Feeds for AI Search Platforms
Prepare for Agentic Commerce with AI Shopping Feeds
The merchants who prepare for AI-native commerce today will dominate tomorrow’s market. AI Shopping Feeds is building the infrastructure to help you capture this opportunity.
Why Choose AI Shopping Feeds for ACP Readiness
AI-Native Feed Optimization:
- Semantic product descriptions optimized for AI understanding
- Natural language title enhancement
- Use-case-based categorization
- Conversational keyword integration
Multi-Platform Distribution:
- Optimize once, distribute everywhere
- ChatGPT, Google Shopping, Facebook, TikTok, Amazon
- Automatic format conversion for each platform
- Single source of truth for all channels
Future-Proof Infrastructure:
- Early preparation for ACP expansion
- Continuous updates as protocol evolves
- Ready for emerging AI commerce platforms
- Transaction-ready feed optimization
Measurable Results:
- 35% improvement in AI discovery rates
- 80% reduction in feed management time
- 95%+ product approval rates
- Early mover advantage in AI commerce
Get Started Today
The window to establish AI commerce presence is narrowing. Early movers are already capturing disproportionate market share.
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