Inside the AI Boom: How Hidden Platforms Are Building an Unstoppable Ecosystem

Ever wonder what happens when AI stops being just a clever chatbot and starts acting like a bustling digital marketplace? Well, buckle up because artificial intelligence models like ChatGPT, Claude, and Gemini aren’t just smart assistants anymore—they’re transforming into powerful platforms that pull in a whole ecosystem of apps, plugins, marketplaces, and even payment systems. It’s a bit like watching a quiet neighborhood suddenly turn into a buzzing city with businesses flocking to set up shop. This evolution reminds me of the early days of tech giants: first, they nab users with a handy product; then, developers and entrepreneurs arrive in droves; finally, infrastructure sprouts up to keep the whole thing humming—and yes, to maybe take a slice of the action. Just look at Anthropic’s Claude Marketplace launched in September 2026, which hands over access to over 2,000 plugins and connectors, turning a simple chatbot interface into a bona fide software platform. So, what does this all mean for ecommerce? Could AI platforms become the next big layer between sellers and buyers—handling everything from product recommendations to checkout, maybe even deciding who wins your business? It’s a thrilling, slightly daunting landscape that’s unfolding right before our eyes. Ready to dive deep? LEARN MORE.

Artificial intelligence models are becoming platforms, attracting an ecosystem of applications, connectors, marketplaces, and payment systems that could eventually influence ecommerce.

ChatGPT, Claude, Gemini, and similar services started primarily as chatbots, or more specifically, as interfaces for interacting with large language models. Now, these same models are becoming platforms through which outside companies can provide software, data, and services.

This shift resembles the rise of earlier technology platforms.

• A useful product attracts users.
• Those users attract developers and businesses.
• Eventually, infrastructure emerges to connect the participants, govern access, move money, and perhaps take a cut of the activity.

Anthropic offered a recent example in September 2026 when it launched Claude Marketplace, giving customers access to more than 2,000 plugins and connectors, along with agents, software, and service providers.

The Claude Marketplace is an early and visible example of the ecosystem growing around AI models.

Enterprise customers can also use some of their committed Anthropic spending to purchase products through the marketplace. That looks less like a chatbot and more like a software platform.

Connection

The Model Context Protocol (MCP) is one reason this ecosystem can develop relatively quickly.

Anthropic introduced the MCP for AI systems to connect with outside software and data. In December 2025, Anthropic donated MCP to the Agentic AI Foundation under the Linux Foundation.

Block and OpenAI joined as founding contributors. Amazon Web Services, Google, Microsoft, and other technology companies also participate in the foundation.

The move made MCP vendor-neutral and reduced one obstacle to adoption. As a result, software companies may not need to build a separate connection for every AI platform. That does not necessarily make the connector itself especially valuable.

As connectivity becomes standardized, larger economic opportunities may shift elsewhere, including distribution, permissions, security, payments, and customer access.

Marketplaces

Marketplaces provide one possible model.

Claude Marketplace gives software companies a way to reach customers already using Anthropic. In return, those integrations make Claude useful for more tasks without requiring Anthropic to build every application or data connection itself.

In a way, the model resembles app stores and cloud marketplaces, although the economics are not yet clear. For example, Anthropic has not disclosed whether it receives a share of sales made through Claude Marketplace.

Distribution may ultimately matter more than the marketplace fee. Stratechery analyst Ben Thompson argued in September that AI agents could become powerful aggregators because users may rely on a relatively small number of agents to interact with many outside services.

If that happens, businesses could compete not only for customers, but also for an agent’s recommendation. Ecommerce provides a useful example.

Ecommerce

AI tools already help shoppers research products, compare alternatives, and decide what to buy. Call it AI product discovery or agentic commerce.

The next step is connecting those conversations to merchant systems.

Google’s Universal Commerce Protocol provides a standard for commerce interactions involving AI agents. A merchant can make products available to Google’s AI surfaces and either support checkout there or send the assembled cart to its own website.

Stripe has taken a similar approach with its Agentic Commerce Suite, which lets merchants make product information available to multiple AI agents while continuing to use their existing fulfillment and post-purchase systems.

Payment infrastructure is developing too.

Agent transactions create familiar payment problems, including authorization, fraud, refunds, and liability, but with an additional participant acting between the shopper and merchant.

Google, Stripe, Visa, Mastercard, and others are developing programs to define what an agent can buy and how to authorize a transaction.

No single approach has won, but that fact may be relatively less important for merchants today than the fact that the pieces are appearing.

Growth

McKinsey & Company estimates that by 2030 AI agents could influence or drive $900 billion to $1 trillion in U.S. consumer retail sales and $3 trillion to $5 trillion worldwide.

For now, AI shopping is primarily about discovery and referral, not autonomous purchasing. But an AI platform does not need to complete the transaction to influence ecommerce generally or individual shops specifically. It can affect which products shoppers consider, which retailers they visit, and perhaps eventually which merchant receives the order.

New Layers

Online sellers have experienced similar shifts before.

• Search engines were a key source of product discovery when online selling was in its infancy.
• Later, ecommerce marketplaces aggregated buyers and sellers.
• More recently, social networks became channels for advertising and shopping.

Each shift or change inserted another company between the merchant and at least some customers. Now, AI platforms could become another such layer.

The difference, however, is that an AI agent could do more than send traffic. AI can, to a degree, understand the shopper’s preferences, compare products across merchants, assemble a purchase, and eventually initiate a transaction.

That fact raises several business questions, for example:

• Which merchants and products will an agent recommend?
• Who controls the customer relationship?
• Where will checkout occur?
• Will platforms charge merchants for access to demand?
• What happens to advertising when an agent chooses among products before a shopper sees a search results page?

No one has all the answers yet, but apps, connectors, marketplaces, commerce protocols, and payment systems are beginning to form around AI platforms. For ecommerce companies, that emerging ecosystem may matter long before autonomous agents routinely make purchases.