Artificial intelligence models are rapidly transforming from standalone chatbots into comprehensive software platforms, attracting sprawling ecosystems of applications, connectors, marketplaces, and payment systems that are poised to fundamentally influence the future of ecommerce.
Services such as ChatGPT, Claude, and Gemini originally captured public attention as conversational interfaces designed to interact with large language models. Today, however, these same foundational models are evolving into robust platforms through which outside software developers, data providers, and service companies can deliver their own products. This structural shift closely mirrors the rise of earlier technological paradigm shifts, where closed systems opened their doors to third-party developers to create massive, interdependent digital economies.
A striking example of this evolution occurred in September 2026, when Anthropic launched the Claude Marketplace, granting customers direct access to more than 2,000 plugins, connectors, specialized agents, software tools, and service providers. Enterprise customers utilizing the platform can even draw upon some of their committed Anthropic spending allocations to purchase products directly through the marketplace. Such capabilities make the service look increasingly less like a traditional chatbot and more like an enterprise-grade software platform.
Connection and Standardization
One of the primary catalysts enabling this ecosystem to develop at a rapid pace is the Model Context Protocol, commonly known as MCP. Anthropic originally introduced MCP to give AI systems a standardized way to securely connect with outside software programs and external data repositories. In December 2025, Anthropic further solidified the standard by donating MCP to the Agentic AI Foundation, which operates under the umbrella of the Linux Foundation.
Block and OpenAI immediately joined the initiative as founding contributors, while other major technology leaders, including Amazon Web Services, Google, and Microsoft, also stepped forward to participate in the foundation. This move rendered MCP entirely vendor-neutral, effectively dismantling a major barrier to wider technological adoption. Consequently, software companies no longer need to build and maintain a separate, proprietary connection for every single AI platform on the market.
While standardization makes connectivity smoother, it also means the connector itself may not remain an especially valuable commodity over the long term. As basic connectivity becomes commoditized, larger economic opportunities are expected to shift toward higher-value layers of the stack, including distribution, user permissions, security protocols, specialized payments, and direct customer access.
Marketplaces and the Power of Distribution
Marketplaces are emerging as one of the most viable commercial models for this new era of artificial intelligence. The Claude Marketplace offers software developers a streamlined pathway to reach end users who are already actively engaged within Anthropic’s ecosystem. In return, these third-party integrations make Claude vastly more useful for a wider variety of complex tasks without requiring Anthropic to engineer every single software application or data connection in-house.
In many ways, this dynamic resembles the historical rise of mobile app stores and enterprise cloud marketplaces, even though the exact underlying financial economics remain to be fully determined. For instance, Anthropic has not publicly disclosed whether it takes a direct revenue share from sales generated through the Claude Marketplace.
Ultimately, distribution may matter far more than any individual marketplace transaction fee. Analyzing these structural shifts, Stratechery analyst Ben Thompson argued in a September commentary that AI agents could evolve into exceptionally powerful digital aggregators. In this scenario, everyday users may rely on a relatively small number of trusted AI agents to interact with a vast array of underlying outside services.
If consumer behavior shifts in that direction, businesses will soon find themselves competing not only for the direct attention of human customers, but also for the critical recommendation and endorsement of an AI agent. The retail and ecommerce sectors provide a clear and compelling preview of how this competition might unfold.
The Rise of Agentic Commerce
Today, consumers already routinely utilize AI tools to research products, compare alternative brands, and evaluate purchasing decisions. Industry observers often refer to this behavior as AI product discovery or, more broadly, agentic commerce. The next logical frontier in this technological evolution is seamlessly connecting those conversational discovery moments directly to merchant backend inventory and checkout systems.
Google has introduced the Universal Commerce Protocol to establish a standardized framework for commerce interactions involving AI agents. Under this system, a merchant can make its product catalog available across Google’s various AI surfaces, choosing either to support direct checkout within the AI interface or to securely transfer the fully assembled cart to the merchant’s own website for final purchase.
Stripe has pursued a similarly structured approach through the rollout of its Agentic Commerce Suite. This suite is designed to let merchants distribute comprehensive product information to multiple competing AI agents while continuing to rely on their established, trusted fulfillment and post-purchase customer systems.
Simultaneously, payment infrastructure is evolving to support these automated interactions. Agent-driven transactions introduce a series of familiar payment challenges—such as authorization protocols, fraud prevention, refund handling, and liability allocation—but introduce an entirely new participant acting dynamically between the human shopper and the online merchant. Financial institutions and technology firms, including Google, Stripe, Visa, and Mastercard, are actively developing new programs and security standards to define precisely what an autonomous agent is permitted to buy and how transactions should be authorized.
While no single industry standard has emerged victorious, the lack of a universal approach is arguably less important to merchants today than the sheer speed at which the foundational infrastructure is appearing across the market.
Economic Projections and Market Impact
Major financial and strategic institutions are already attempting to quantify the immense economic stakes involved in this transition. McKinsey & Company estimates that by the year 2030, AI agents could directly influence or drive between $900 billion and $1 trillion in U.S. consumer retail sales, alongside a staggering $3 trillion to $5 trillion globally.
At present, consumer AI shopping experiences remain primarily focused on discovery and referral rather than fully autonomous purchasing. However, an AI platform does not need to independently complete the financial transaction to exert a profound influence on the broader ecommerce landscape or individual retail storefronts. Simply by shaping which products shoppers consider, which retail websites they visit, and potentially which merchant ultimately receives the order, these platforms hold immense sway.
Navigating New Layers of Intermediation
Online merchants and digital sellers are no strangers to structural shifts that alter their relationship with buyers. Over the past few decades, the rise of search engines, social media advertising networks, and massive online marketplaces each inserted a powerful intermediary between the merchant and at least a portion of their customer base.
Now, emerging AI platforms threaten to become yet another influential layer in the digital commerce stack. The crucial difference, however, is that an advanced AI agent does more than simply route passive traffic to a website. Modern AI can deeply comprehend a shopper’s personal preferences, intelligently compare complex products across entirely different merchants, assemble a multifaceted purchase, and eventually initiate the financial transaction on the user’s behalf.
This reality introduces a series of complex strategic questions for modern businesses, forcing them to reevaluate how their digital storefronts are indexed, how their brand data is consumed by external algorithms, and how they can maintain direct relationships with consumers in an agent-driven economy.
While definitive answers to these strategic challenges remain elusive, the rapid proliferation of software applications, connectors, marketplaces, commerce protocols, and payment systems signals that the architecture of AI platforms is solidifying. For ecommerce companies and digital retailers, understanding and adapting to this emerging ecosystem may prove vital long before autonomous agents routinely begin making purchases on behalf of consumers.
