The Silent Shopper: How AI Agents Are Rewriting the Rules of Commerce

SAN FRANCISCO, CA – January 19, 2026 – The future of online shopping may no longer involve a human browsing a website. Instead, it will be a conversation between machines. This vision of “agentic commerce” took a significant step forward today as AI infrastructure company Deeplumen announced the release of its open-source SDK for Java, designed to connect enterprise systems to Google's new Universal Commerce Protocol (UCP).

The move comes just a week after Google, in a landmark announcement, unveiled UCP as an open standard to create a “common language” for AI-driven transactions. With the commercial AI race heating up, this development signals a tectonic shift in how products are discovered, marketed, and sold, moving the primary point of contact from a human consumer to an autonomous AI agent.

Deeplumen’s launch specifically targets the vast, often unseen backbone of global e-commerce. By providing a Java-based toolkit, the company is building a critical bridge for established enterprises, allowing them to plug their existing infrastructure directly into the burgeoning ecosystem of AI shoppers without having to rebuild their systems from scratch.

A New Language for Digital Storefronts

At the heart of this transformation is Google's Universal Commerce Protocol. Co-developed with a formidable roster of industry giants including Shopify, Etsy, Target, and Walmart, UCP aims to standardize the entire commerce lifecycle. It provides the technical foundation for AI agents—like those powering Google’s Gemini or its AI-infused Search—to not only discover products but also negotiate details and execute purchases directly and securely.

This protocol is Google’s answer to a fundamental challenge: how to make the world’s fragmented retail landscape legible to machines. For AI agents to fulfill a user's request like “find me the best waterproof running shoes for under $150 available for next-day delivery,” they need to query countless vendors, compare structured data, and process transactions seamlessly. UCP is designed to be the universal translator that makes this possible.

Industry analysts see this as a pivotal moment. The creation of a shared standard endorsed by leaders like Mastercard, Visa, and The Home Depot gives UCP immediate weight and accelerates a future where a significant portion of online spending is directed by AI. Projections from Morgan Stanley estimate that agentic shoppers could command up to $385 billion in U.S. e-commerce spending by 2030, while McKinsey forecasts a staggering global market of $3 trillion to $5 trillion orchestrated by these autonomous systems within the same timeframe.

From Persuading Humans to Informing Agents

The rise of agentic commerce necessitates a radical rethinking of marketing itself. For decades, brand success has been built on emotional storytelling, visual appeal, and persuasive advertising designed to capture human attention and desire. Deeplumen frames the new paradigm as “Marketing to AI” (M2AI), a strategy focused on data, not drama.

“Traditional marketing is about optimizing for 'perception.' AI agents optimize for parameters,” stated Joy Wu, COO at Deeplumen, in the company’s announcement. “In the M2AI era, the goal isn't to create 'brand illusions,' but to provide high-fidelity, structured data that allows AI agents to discover, verify, and execute transactions seamlessly.”

This means the new battleground for brands will be fought over the quality, clarity, and reliability of their product data. An AI agent tasked with purchasing a product will prioritize verifiable specifications, real-time availability, shipping speed, and price over a clever tagline or a visually stunning ad campaign. In this world, a brand’s structured data becomes its most valuable marketing asset. The focus shifts from influencing perception to providing irrefutable facts that an algorithm can process and trust.

Java's Role in the AI Revolution

While much of the modern AI landscape is built on Python, Deeplumen’s decision to launch its first UCP software development kit (SDK) for Java is a strategic masterstroke. A vast portion of the world's enterprise commerce infrastructure—including enterprise resource planning (ERP), massive retail platforms, and order management systems—runs on the mature and robust Java programming language.

For these companies, the prospect of integrating with cutting-edge AI systems often presents a daunting and expensive challenge, typically requiring a complete overhaul of legacy technology. Deeplumen’s Java SDK acts as an adapter, allowing these businesses to make their products and services “agent-ready” without tearing down their existing tech stack. This plug-and-play approach dramatically lowers the barrier to entry, enabling large-scale retailers and brands to participate in the agentic economy far sooner than previously thought possible.

By ensuring that these established Java environments can speak the language of UCP, Deeplumen is positioning a technology often seen as traditional squarely at the center of the AI commerce revolution. It is a pragmatic solution that acknowledges the reality of enterprise IT while embracing the future of retail.

The Promise and Perils of Autonomous Shopping

The transition to an AI-driven marketplace is not without significant hurdles and risks. While a 2025 eMarketer survey found that 75% of retailers believe AI agents will be crucial for competitiveness, other reports highlight a severe lack of preparedness. One recent study indicated that only 27% of retailers currently possess the technological infrastructure to support agentic shopping at scale, with many still operating on “brittle, patched-together stacks” that will be invisible to AI agents.

Beyond technical readiness, a host of complex challenges loom. Security and fraud liability are chief among them. When an autonomous agent executes an erroneous or fraudulent transaction, who is accountable—the user, the agent’s developer, or the merchant? This “accountability gap” presents new legal and financial risks that the industry is only beginning to grapple with.

Furthermore, data privacy remains a major barrier, with 55% of businesses citing it as a significant concern in AI adoption. The level of personal data access required for an AI agent to shop effectively on a user's behalf raises profound questions about trust and transparency. Experts in AI ethics also warn of the potential for algorithmic bias to creep into product recommendations, reinforcing existing inequalities or limiting consumer choice.

For brands, the shift could also mean a loss of direct customer relationships and the erosion of brand loyalty, as AI agents prioritize utility and price over brand affinity. The future of commerce is rapidly being built, but its foundations must be laid with a deep consideration for the security, fairness, and trust required to place our wallets in the hands of a machine.