How AI Agents Are Changing E-commerce in 2026: Open Protocols Explained (Complete Guide)

According to eMarketer (December 2025), AI platforms are expected to account for $20.9 billion in retail spending in 2026, nearly quadrupling 2025's figures. AI shopping agents are no longer theoretical. They are live on ChatGPT, Google Gemini, Microsoft Copilot, and Perplexity, and they are completing real purchases for real consumers. The critical question for e-commerce brands is no longer whether AI agents will change shopping, but how the open protocols powering these agents determine who gets discovered and who gets skipped.

This guide explains the connective tissue behind the AI agent economy: the open protocols that enable agents to find products, negotiate transactions, and complete checkouts across platforms. If you understand what agentic commerce means, this article takes you one level deeper into the infrastructure that makes it work.

What You'll Learn

• How AI shopping agents discover and purchase products through open protocols

• What UCP, MCP, and A2A do and how they work together as layered infrastructure

• Why open protocols prevent vendor lock-in and democratize e-commerce access

• How the shift from keyword SEO to product feed optimization changes your marketing strategy

• A practical checklist for preparing your brand for AI agent discovery in 2026

Summary: Key Statistics on AI Agents and E-commerce Protocols

Metric	Value	Source
AI platform retail spending (2026)	$20.9 billion (1.5% of retail)	eMarketer, 2025
Global agentic commerce opportunity by 2030	$3-5 trillion	McKinsey, 2025
AI-referred traffic growth on Black Friday 2025	805% year-over-year	Adobe via MetaRouter, 2026
MCP monthly SDK downloads	97M+	Anthropic, 2026
Active public MCP servers	10,000+	Anthropic, 2026
A2A technology partners	50+	Google Developers, 2025
UCP co-development partners	Shopify, Etsy, Wayfair, Target, Walmart + 20 endorsed	Google, 2026
Copilot shopping purchases within 30 min	53% more with Copilot	Microsoft, 2026
AI-referred shoppers purchase likelihood	38% more likely to buy	eMarketer, 2025
E-commerce via agentic channels by 2030	15-25% of total online retail	Bain via MetaRouter, 2026

Why Are AI Shopping Agents Transforming E-commerce?

AI shopping agents are fundamentally different from the product recommendation engines and chatbots that preceded them. According to OpenAI (September 2025), "Agentic commerce is where ChatGPT doesn't just help you find what to buy, it also helps you buy it." These agents do not simply display search results. They interpret natural-language requests, evaluate products across merchants, compare attributes, and complete transactions, all within a single conversation.

The scale of this shift is substantial. According to McKinsey (October 2025), agentic commerce could redirect $3 to $5 trillion in global retail spend by 2030, with nearly $1 trillion coming from the U.S. alone. According to Bain via MetaRouter (January 2026), 15-25% of total online retail sales could flow through agentic channels by the end of this decade.

Consumer behavior is already following this trajectory. AI-referred traffic to U.S. retail sites grew 805% year-over-year on Black Friday 2025, according to Adobe data cited by MetaRouter (January 2026). According to Previsible (January 2026), traffic from AI sources surged 1,200% while traditional search traffic declined 10%. These are not marginal increases. They represent a structural reallocation of discovery and purchase behavior from traditional search to AI-mediated conversations.

Key Finding: Shoppers arriving from AI services are 38% more likely to buy than those from traditional channels. --- eMarketer, 2025

The agents driving this transformation are deployed across every major AI platform. ChatGPT now enables U.S. users to buy directly from Etsy sellers, with over a million Shopify merchants coming soon, according to OpenAI (September 2025). Microsoft Copilot Checkout is live in the U.S. with Shopify, PayPal, Stripe, and Etsy integrations, according to Microsoft (January 2026). Google's Business Agent, powered by UCP, connects merchants to users on AI Mode in Search and Gemini. Shopify's Agentic Storefronts enable brands to sell across ChatGPT, Perplexity, and Microsoft Copilot simultaneously, according to Shopify (January 2026).

For a deeper look at the foundations of agentic commerce, including consumer adoption data and market projections, see our complete guide.

What Are Open Protocols and Why Do They Matter for AI Agents?

Open protocols are standardized communication frameworks that define how AI agents interact with merchants, payment systems, and each other. Without protocols, every AI platform would require custom integrations with every merchant, a bespoke approach that does not scale.

Consider the analogy of the early internet. Before HTTP became the standard protocol for web communication, each network required its own proprietary connection method. HTTP did not make any single website successful, but it made the entire web possible by creating a shared language for communication. Open protocols for AI commerce serve a similar function: they create the shared infrastructure that enables any agent to interact with any merchant that implements the standard.

Three protocols have emerged as the foundational layer for AI commerce, each addressing a different part of the agent workflow. For a detailed UCP vs MCP comparison and decision matrix, see our protocol comparison guide. Here is a brief overview of their roles:

Protocol	Full Name	Primary Role	Key Use Case
UCP	Universal Commerce Protocol	Commerce transactions	Agent discovers products, initiates checkout, manages orders
MCP	Model Context Protocol	Tool and data access	Agent connects to product databases, inventory systems, pricing APIs
A2A	Agent-to-Agent Protocol	Agent communication	Multiple specialized agents coordinate to fulfill complex requests

According to The Register (January 2026), an emerging consensus has formed: "MCP for tool integration, A2A for agent communication, UCP + AP2 for e-commerce." These protocols are not competing standards. They are complementary layers that work together to enable the full agent commerce workflow.

Pro Tip: Open protocols are not interchangeable. Each solves a specific problem in the agent workflow. Implementing the right combination ensures your products are discoverable across multiple AI platforms without platform-specific engineering for each one.

The "open" designation is critical. UCP was co-developed with Shopify, Etsy, Wayfair, Target, and Walmart, and has been endorsed by 20+ partners including Adyen, American Express, Best Buy, Mastercard, Stripe, and Visa, according to Google (January 2026). MCP was donated by Anthropic to the Agentic AI Foundation to ensure vendor-neutral governance, according to Anthropic (January 2026). A2A was contributed by Google to the Linux Foundation with support from 50+ technology partners, according to Google Developers (April 2025). This open governance prevents any single company from controlling the standard, which is what makes multi-platform agent discovery possible.

How Do AI Agents Discover Products Today?

Understanding how AI agents discover products requires understanding the difference between the traditional e-commerce funnel and the agent-mediated discovery flow. Traditional e-commerce discovery follows a predictable path: a consumer types a keyword, reviews a list of search results, clicks through to product pages, and eventually completes a purchase. AI agents compress this entire funnel into a single interaction.

When a consumer asks an AI agent, "Find me waterproof hiking boots under $150 with good ankle support," the agent does not simply search for "hiking boots." Research on query fan-out shows that AI systems decompose a single user request into multiple retrieval sub-queries. An agent might simultaneously query for boot waterproof ratings, ankle support specifications, price comparisons across retailers, and user review sentiment, all before presenting a recommendation.

This agent discovery flow follows a four-step process that the open protocol layer enables:

Step 1: Query Interpretation. The agent parses the natural-language request and identifies product attributes (waterproof, hiking, under $150, ankle support). This requires structured product data that maps to conversational attributes, not just keyword-optimized titles.

Step 2: Protocol Discovery. The agent queries merchant endpoints via UCP to identify which businesses can fulfill the request. According to the Google Developers Blog (January 2026), "Agents query business profiles to identify available services and negotiate supported features, reducing the need for bespoke integrations." The agent dynamically discovers what each merchant offers without needing a pre-built integration.

Step 3: Data Retrieval. Using MCP, the agent accesses product catalogs, inventory levels, pricing, and availability data in real time. According to Neontri (December 2025), "An agent might query price and inventory 50 times a second across thousands of SKUs to optimize a bundle."

Step 4: Transaction Execution. Once the agent selects the best match, UCP handles the checkout flow, including cart creation, payment processing (via AP2), and order confirmation. According to UCP.dev (January 2026), "UCP defines building blocks for agentic commerce--from discovering and buying to post purchase experiences--allowing ecosystem to interoperate through one standard."

Watch Out: Without protocol implementation, your products are invisible to AI agents. As Presta (January 2026) warns, "If an AI agent cannot 'read' your store via UCP, it will likely bypass your products in favor of a competitor who provides structured, agent-friendly data."

What Role Does Each Protocol Play in the Agent Economy?

Each protocol addresses a distinct layer of the agent commerce stack. Understanding their individual roles clarifies how they combine into a functioning system. For readers evaluating which protocols to implement, our protocol comparison and decision matrix provides a detailed implementation roadmap.

Universal Commerce Protocol (UCP): The Commerce Layer

UCP is an open standard designed specifically for commercial transactions between AI agents and merchants. According to the UCP specification (January 2026), UCP "defines building blocks for agentic commerce--from discovering and buying to post purchase experiences--allowing ecosystem to interoperate through one standard."

UCP's architecture enables agents to dynamically discover merchant capabilities without pre-configured integrations. A merchant publishes a business profile describing its services, supported features, payment options, and fulfillment capabilities. Any agent on any platform can query this profile and initiate a transaction if the merchant can fulfill the request. According to Google (January 2026), UCP "unlocks access to users on surfaces like AI Mode in Search and Gemini web."

UCP also has built-in support for A2A, MCP, and AP2 (Agent Payment Protocol), making it the integration point for the full protocol stack. For a comprehensive technical guide on implementation, see our Universal Commerce Protocol guide.

Model Context Protocol (MCP): The Data Access Layer

MCP provides the standardized interface that AI agents use to access external tools and data sources. According to Anthropic (January 2026), "MCP has emerged as the de facto standard for tool-calling protocols," with 97M+ monthly SDK downloads, 10,000+ active public MCP servers, and 75+ connectors in the Claude directory.

In the commerce context, MCP enables agents to connect to product databases, inventory management systems, CRM platforms, and analytics tools. While UCP handles the commerce transaction itself, MCP provides the underlying data plumbing that feeds product information, availability, and pricing to the agent in real time.

Anthropic donated MCP to the Agentic AI Foundation to ensure vendor-neutral governance and prevent any single company from controlling the standard. This open governance structure means merchants can build MCP integrations once and have them work across Claude, ChatGPT, Copilot, and other platforms implementing the protocol.

Agent-to-Agent Protocol (A2A): The Coordination Layer

A2A addresses a challenge that UCP and MCP do not: how do multiple AI agents communicate with each other? In complex commerce scenarios, a consumer's request may require coordination between a shopping agent, a logistics agent, a payment agent, and a returns-processing agent. A2A provides the standardized communication protocol for this inter-agent coordination.

According to Google Developers (April 2025), "A2A is quickly becoming the de facto standard for how agents should talk to one another," with support from 50+ technology partners at launch.

How Protocols Work Together

These three protocols are not alternatives to each other. They are complementary layers of a single stack:

Layer	Protocol	Function	Analogy
Commerce	UCP	Manages the transaction lifecycle (discovery, checkout, fulfillment)	The storefront and cash register
Data	MCP	Provides access to product data, tools, and backend systems	The warehouse and inventory system
Coordination	A2A	Enables multi-agent collaboration for complex tasks	The team of specialists coordinating
Payment	AP2	Secures payment authorization and processing	The payment terminal

Key Finding: UCP has built-in support for MCP, A2A, and AP2. This means merchants implementing UCP automatically gain compatibility with all three coordination protocols. --- UCP.dev, January 2026

What Do AI Agents in Action Look Like? Real Case Studies

The theoretical protocol stack becomes concrete through the real implementations already live in the market. Each major AI platform has adopted a distinct approach to agentic commerce, and their strategies illustrate how protocols enable cross-platform discovery.

Google Shopping Agent + UCP

Google's Business Agent, announced at NRF in January 2026, enables merchants to use their existing Merchant Center product feeds to power AI-driven commerce. According to Google (January 2026), merchants can "use your existing Merchant Center account shopping feeds to capture high-intent customers during discovery."

Walmart (January 2026) is an early partner, launching an experience that pairs Google's Gemini with Walmart and Sam's Club inventory. UCP enables this integration without requiring Walmart to build a custom connector for Gemini. The same UCP implementation that powers Walmart's Gemini experience can serve any other agent implementing the protocol.

ChatGPT Instant Checkout + Agentic Commerce Protocol (ACP)

OpenAI launched ChatGPT Instant Checkout with Etsy as its first merchant partner in September 2025, according to OpenAI (September 2025). U.S. ChatGPT Plus, Pro, and Free users can buy directly from U.S. Etsy sellers, with over a million Shopify merchants (including Glossier, SKIMS, Spanx, and Vuori) coming soon.

As OpenAI describes it, "ChatGPT simply acts as the user's AI agent--securely passing information between user and merchant, just like a digital personal shopper would." Orders, payments, and fulfillment remain with the merchant using their existing systems.

Microsoft Copilot Checkout

Microsoft Copilot Checkout launched in the U.S. in January 2026 with integrations for Shopify, PayPal, Stripe, and Etsy, according to Microsoft (January 2026). Shopify merchants are automatically enrolled (with an opt-out window).

Microsoft's data shows significant conversion impact. According to Microsoft (January 2026), Copilot users are 53% more likely to make a purchase within 30 minutes and 194% more likely to result in a purchase when shopping intent is present. Critically, as Microsoft states, "Merchants stay the merchant of record, own the transaction, the customer data, and the relationship."

Shopify Agentic Storefronts

Shopify's Agentic Storefronts, launched in January 2026, provide the clearest example of the multi-platform promise of open protocols. According to Shopify (January 2026), "Shopify Agentic Storefronts help brands on Shopify instantly and accurately get discovered on AI platforms" including ChatGPT, Perplexity, and Microsoft Copilot. One setup in the Shopify admin enables selling everywhere AI conversations happen.

PayPal's Multi-Channel Bet

PayPal's acquisition of Cymbio in January 2026 signals the payment industry's commitment to agentic commerce infrastructure. According to PayPal (January 2026), Cymbio helps brands sell across agentic surfaces including Microsoft Copilot and Perplexity. PayPal's position is clear: "There should be no difference in available data from consumer between order placed on merchant's website and third-party platform."

How Do Open Protocols Change E-commerce Marketing Strategy?

The protocol-mediated agent economy creates a fundamental paradigm shift in how e-commerce marketing works. Traditional e-commerce marketing optimized for human behavior: keyword rankings, meta descriptions, click-through rates, and landing page design. Agent-mediated discovery optimizes for machine-readable data quality, structured product attributes, and protocol accessibility.

As Microsoft (February 2026) states: "It's not about keywords or backlinks anymore. Instead, agentic AI systems ingest, reason over, and recommend products in real-time conversations."

This shift manifests in several concrete ways. In the era of zero-click search visibility, traditional SEO metrics like keyword rankings and click-through rates are already under pressure. AI agents accelerate this trend by removing the human from the discovery loop entirely. When a purchase happens inside an AI conversation, there is no pageview to track, no session to measure, and no last-click to attribute, according to Previsible (January 2026).

From Keywords to Product Feeds

According to Kevin Indig of Growth Memo (January 2026), "In the GEO world, marketing is data architecture. It's about feeding AI the clearest, richest, and most trustworthy data possible." Product feeds, not webpages, now determine who gets discovered by AI agents.

According to Amsive (January 2026), "If inventory or pricing isn't machine-readable, agents will skip your store because they cannot verify its accuracy." This means product data quality, including natural-language descriptions, real-time pricing, accurate inventory, and structured attributes, has become the primary marketing asset.

The Strategy Shift

Traditional E-commerce Marketing	Protocol-Mediated Agent Marketing
Keyword-optimized product pages	Machine-readable structured product data
Meta titles and descriptions for humans	Product attributes and capabilities for agents
Click-through rate optimization	Protocol endpoint accessibility
Landing page design	API response speed and data accuracy
Google Ads bidding	Product feed completeness and freshness
Backlink building	UCP business profile quality
Session-based analytics	Agent interaction metrics

Pro Tip: Your product feed is now your primary storefront. Every attribute, description, and specification in your product data is a potential answer to an agent's query. Invest in enriching product data with conversational attributes that answer natural-language questions, not just keyword-optimized titles.

How Do Open Protocols Prevent Vendor Lock-In?

One of the most significant implications of open protocols is their potential to democratize e-commerce access. Without standards, each AI platform would create proprietary integration requirements, forcing merchants to build and maintain separate connections for ChatGPT, Gemini, Copilot, Perplexity, and every future agent platform. This creates vendor lock-in where the largest merchants with the most engineering resources have an insurmountable advantage.

Open protocols invert this dynamic. According to Mastercard (January 2026), "UCP provides single standard that all parties can implement, dramatically reducing integration costs and time-to-market." When a merchant implements UCP once, that implementation works across every agent platform that supports the protocol. A small Shopify merchant gains the same protocol-level access as Walmart or Target.

The governance structures of these protocols reinforce this democratization. MCP was donated to a neutral foundation specifically to prevent Anthropic from controlling it. A2A was contributed to the Linux Foundation with multi-vendor governance. UCP was co-developed with five major retailers but designed to be implementable by any merchant regardless of size.

Key Finding: Shopify's Agentic Storefronts enable any Shopify merchant to be discoverable across ChatGPT, Perplexity, and Microsoft Copilot with one setup. This is only possible because open protocols create a shared integration layer.

This accessibility has implications for competitive dynamics. In traditional e-commerce, large retailers dominated through advertising budgets, SEO teams, and marketplace presence. In the agent economy, discovery depends on data quality and protocol readiness, areas where smaller merchants with better product data can compete effectively against larger competitors with weaker data architecture.

According to BigCommerce (December 2025), "Platforms require real-time inventory and pricing data so agents can make accurate decisions." This requirement is data-driven, not budget-driven, leveling the competitive playing field for merchants who invest in product data quality.

How Can You Prepare Your Brand for AI Agent Discovery?

Preparing for AI agent discovery requires action across three areas: product data optimization, protocol implementation, and organizational alignment. The following checklist provides a practical framework for e-commerce brands at any stage of readiness.

Product Data Readiness

Product data is the foundation of agent discovery. Without machine-readable, accurate, and attribute-rich product information, no protocol implementation will make your products discoverable.

• Audit product feed completeness. Every SKU should include: title, description, price, availability, images, category, brand, condition, shipping details, and return policy. Missing fields mean missed discovery opportunities.

• Add conversational attributes. AI agents process natural-language queries. Add fields that answer common questions: "Is this waterproof?", "What material is this?", "Does this run true to size?" These attributes help agents match your products to conversational queries.

• Ensure real-time accuracy. According to BigCommerce (December 2025), "Platforms require real-time inventory and pricing data so agents can make accurate decisions." Stale pricing or inaccurate inventory causes agents to skip your store or present incorrect information that damages trust.

• Implement schema markup. Structured data using Product, Offer, and Review schema helps agents understand your product information in a machine-readable format.

Protocol Implementation Priority

For brands evaluating which protocols to implement first, the priority depends on your platform and scale. For detailed implementation guidance, see our UCP guide.

Priority	Action	Platform	Timeline
1 (Immediate)	Enable Agentic Storefronts	Shopify merchants	Now (one-click setup)
2 (Q1 2026)	Optimize Merchant Center feed for UCP	All merchants	2-4 weeks
3 (Q2 2026)	Implement MCP endpoints for product data	Mid-market and enterprise	4-8 weeks
4 (H2 2026)	Add A2A support for multi-agent workflows	Enterprise only	8-12 weeks

Organizational Alignment

• Bridge marketing and engineering. Protocol implementation requires collaboration between marketing teams (who own product data) and engineering teams (who build API endpoints). These functions must work together.

• Rethink attribution models. Traditional last-click attribution breaks when purchases happen inside AI conversations. Develop measurement frameworks that account for agent-mediated discovery.

• Monitor agent visibility. Track how your products appear in AI agent recommendations across platforms. This requires new tooling beyond traditional SEO analytics.

Watch Out: Many merchants focus exclusively on UCP while neglecting product data quality. Protocol implementation without data readiness is equivalent to building a storefront with empty shelves. Data comes first, protocols come second.

What Does the Future of Agent-Mediated Commerce Look Like?

The trajectory of agent-mediated commerce is moving from early adoption to mainstream infrastructure across a clear timeline.

2026: Discovery Phase. AI agents are live on major platforms, but merchant adoption of protocols is still early. According to eMarketer (December 2025), AI platforms account for $20.9 billion in retail spending, representing 1.5% of total retail. Early adopters who implement protocols now gain a competitive advantage in agent discovery. According to Very Good Security (January 2026), "Consumer demand for AI shopping is real, but conversion lags because merchant infrastructure was not built for agents."

2027-2028: Adoption Acceleration. Protocol standards mature and consolidate. MCP, A2A, and UCP implementations become standard features in major e-commerce platforms. Agent-referred traffic grows from niche to significant channel. Multi-agent workflows become common, with shopping agents coordinating with logistics, payment, and customer service agents via A2A.

2030: Structural Shift. According to McKinsey (October 2025), "Agentic commerce could redirect $3-$5 trillion in global retail spend by 2030." According to Bain via MetaRouter (January 2026), 15-25% of total e-commerce could flow through agentic channels, fundamentally changing how products are discovered and purchased.

TL;DR:

• 2026: Protocol implementation is a competitive advantage

• 2027-2028: Protocol implementation becomes table stakes

• 2030: Merchants without protocol support are invisible to a significant share of commerce

The implications extend beyond discovery to the entire merchant-customer relationship. As Previsible (January 2026) notes, "In 2026, AI stops recommending and starts buying, with the user never leaving the conversation." This means the merchant's relationship with the customer is increasingly mediated by AI agents. Open protocols protect this relationship by ensuring, as Microsoft (January 2026) states, "Merchants stay the merchant of record, own the transaction, the customer data, and the relationship."

Frequently Asked Questions

What are open protocols in AI commerce?

Open protocols are standardized communication frameworks (UCP, MCP, A2A) that define how AI shopping agents interact with merchants, access product data, and coordinate with each other. They function like HTTP for the web: they do not make any single merchant successful, but they make the entire agent commerce ecosystem possible by providing a shared language. Open governance ensures no single company controls these standards.

How do AI agents discover products using protocols?

AI agents discover products through a four-step protocol-mediated flow: (1) the agent interprets a natural-language request and identifies product attributes, (2) the agent queries merchant UCP endpoints to discover available products and capabilities, (3) the agent retrieves real-time data via MCP including pricing, inventory, and specifications, and (4) the agent executes the transaction through UCP's checkout primitives. This entire process happens in seconds without the consumer visiting a website.

What is the difference between UCP, MCP, and A2A?

UCP (Universal Commerce Protocol) handles commerce-specific functions like product discovery, checkout, and post-purchase management. MCP (Model Context Protocol) provides the data access layer that connects agents to product databases and backend tools. A2A (Agent-to-Agent Protocol) enables multiple specialized agents to coordinate on complex tasks. These are complementary layers, not competing standards. UCP has built-in support for both MCP and A2A.

Do I need to implement all three protocols?

Not immediately. Priority depends on your platform: Shopify merchants can enable Agentic Storefronts with one click (which handles UCP exposure through Shopify's infrastructure). Non-Shopify merchants should prioritize optimizing their Merchant Center product feeds for UCP, then consider MCP endpoints for direct data access. A2A is currently most relevant for enterprise merchants with complex multi-agent workflows. See our protocol comparison and decision matrix for detailed guidance.

How do protocols prevent vendor lock-in?

Open protocols ensure that a single integration works across multiple AI platforms. When a merchant implements UCP once, that implementation serves Google Gemini, ChatGPT, Microsoft Copilot, and any future platform that adopts the standard. Without protocols, merchants would need separate custom integrations for each platform, giving the largest companies with the most engineering resources an unfair advantage. Open governance (via foundations like the Linux Foundation and Agentic AI Foundation) prevents any single company from controlling the standards.

What is the business impact of AI shopping agents?

According to McKinsey (October 2025), agentic commerce could redirect $3-5 trillion in global retail spend by 2030. In the nearer term, eMarketer estimates AI platforms will account for $20.9 billion in retail spending in 2026. Microsoft reports that Copilot users are 53% more likely to make a purchase within 30 minutes and 194% more likely when shopping intent is present. Shoppers arriving from AI services are 38% more likely to buy than those from traditional channels.

How does agentic commerce change SEO strategy?

Agentic commerce shifts the primary discovery mechanism from keyword-optimized web pages to structured product data accessed through protocol endpoints. As Microsoft (February 2026) states, "It's not about keywords or backlinks anymore. Instead, agentic AI systems ingest, reason over, and recommend products in real-time conversations." Merchants must shift investment from traditional keyword SEO to product data optimization, real-time inventory accuracy, and protocol implementation.

Which merchants benefit most from protocol adoption?

Merchants with high product data quality benefit disproportionately, regardless of size. Open protocols level the playing field by making discovery dependent on data quality rather than advertising budgets. A small Shopify merchant with complete, accurate, attribute-rich product data can be discovered by AI agents as easily as a large retailer with poor data. Early adopters gain a competitive advantage while merchant infrastructure for agents is still developing.

Sources

1. Google (January 2026). "New tech and tools for retailers to succeed in an agentic shopping era." https://blog.google/products/ads-commerce/agentic-commerce-ai-tools-protocol-retailers-platforms/

2. Google Developers (January 2026). "Under the Hood: Universal Commerce Protocol (UCP)." https://developers.googleblog.com/under-the-hood-universal-commerce-protocol-ucp/

3. OpenAI (September 2025). "Buy it in ChatGPT: Instant Checkout and the Agentic Commerce Protocol." https://openai.com/index/buy-it-in-chatgpt/

4. Shopify (January 2026). "Introducing Shopify Agentic Storefronts." https://www.shopify.com/news/winter-26-edition-agentic-storefronts

5. Anthropic (January 2026). "Donating the Model Context Protocol and Establishing the Agentic AI Foundation." https://www.anthropic.com/news/donating-the-model-context-protocol-and-establishing-of-the-agentic-ai-foundation

6. Google Developers (April 2025). "A2A: A New Era of Agent Interoperability." https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/

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8. eMarketer (December 2025). "AI shopping tools gain traction, but retailer pushback could cloud 2026 progress." https://www.emarketer.com/content/ai-shopping-tools-gain-traction-retailer-pushback-could-cloud-2026-progress

9. MetaRouter (January 2026). "Agentic Commerce Trends and Statistics for 2026." https://www.metarouter.io/post/agentic-commerce-trends-statistics

10. The Register (January 2026). "Deciphering the alphabet soup of agentic AI protocols." https://www.theregister.com/2026/01/30/agnetic_ai_protocols_mcp_utcp_a2a_etc/

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12. Microsoft Retail (February 2026). "Why agentic commerce is the new front door to retail." https://www.microsoft.com/en-us/industry/blog/retail/2026/02/09/how-agentic-commerce-is-becoming-the-new-front-door-to-retail/

13. Walmart (January 2026). "Walmart and Google Turn AI Discovery Into Effortless Shopping Experiences." https://corporate.walmart.com/news/2026/01/11/walmart-and-google-turn-ai-discovery-into-effortless-shopping-experiences

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16. PayPal (January 2026). "PayPal to Acquire Cymbio, Accelerating Agentic Commerce Capabilities." https://newsroom.paypal-corp.com/2026-01-22-PayPal-to-Acquire-Cymbio,-Accelerating-Agentic-Commerce-Capabilities

17. Kevin Indig, Growth Memo (January 2026). "How do you compete in Agentic Commerce?" https://www.growth-memo.com/p/how-do-you-compete-in-agentic-commerce

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