Microsoft unveils tools to build infrastructure for agentic web

· Source: Dataconomy · Field: Technology & Digital — Artificial Intelligence & Machine Learning, E-commerce & Digital Commerce, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

Microsoft has launched a suite of tools and standards to build the "agentic web," where AI agents can autonomously conduct transactions. This initiative includes supporting the Universal Commerce Protocol in Microsoft Merchant Center, a standard co-developed with Google and Shopify and backed by over 20 companies like Visa and Mastercard. Shopify's product catalog, including real-time pricing and inventory, is now integrated into Microsoft Copilot via its commerce API. New advertising tools, such as AI Max for Search campaigns, "Offer Highlights" ad formats, and an audience generation tool, were also introduced. Microsoft reports that automated traffic is growing 8,000 percent year-over-year, significantly outpacing human traffic. Early partners like Target and brands such as Keen are already using Copilot Checkout, which launched in January 2026 and reportedly shortens AI-assisted shopping journeys by 33%.

Key takeaway

For entrepreneurs and CTOs evaluating future e-commerce strategies, your teams should prioritize integrating with agentic web protocols and AI commerce platforms like Copilot. The rapid growth of automated traffic and the efficiency gains from tools like Copilot Checkout (33% shorter shopping journeys) indicate that early adoption of these standards will provide significant compounding advantages as the agent-driven economy scales.

Key insights

The agentic web, driven by AI agents, is rapidly expanding and requires new commerce infrastructure.

Principles

Method

Integrate commerce APIs with AI assistants, adopt universal commerce protocols, and utilize AI-enhanced advertising tools to facilitate autonomous agent transactions.

In practice

Topics

Best for: Investor, Entrepreneur, CTO, AI Engineer, AI Product Manager, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Dataconomy.