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Agentic Commerce and the next phase of online retail
Agentic commerce introduces a new way for AI systems to interact with online retail. We're looking at the role of the Universal Commerce Protocol in that shift.
Agentic commerce introduces a new way for AI systems to interact with online retail. We're looking at the role of the Universal Commerce Protocol in that shift.
Ecommerce has entered a phase of transformation that looks very different from earlier waves of automation and personalisation.
Early AI tools helped sort inventory, optimise search results, and automate routine tasks. The next phase goes beyond assistance and enters a new paradigm where intelligent systems act on behalf of customers and businesses.
This is the promise of agentic commerce, supported by emerging technologies that enable AI agents to handle discovery, checkout, and even post-purchase interactions without constant human intervention.
A key development driving this transition is the Universal Commerce Protocol (UCP). This new open standard creates a common language for AI agents, merchants, and payment systems to work together more seamlessly.
It marks a shift in how digital commerce operates, from siloed systems and bespoke integrations to an interoperable ecosystem where machines can act autonomously on a customer’s behalf.
What this means for the future of ecommerce is worth unpacking — especially for those aiming to harness these advances in a way that delivers value beyond experimentation.
At its core, UCP addresses a significant architectural problem in ecommerce.
Today, merchants and marketplaces rely on custom integrations to connect search engines, storefronts, payment gateways, and fulfillment partners. This fragmentation creates friction and slows down innovation.
UCP introduces a standardised set of primitives and communication patterns that allow AI agents to:
The idea is that any AI agent that understands UCP can interact with any compliant merchant or platform without bespoke coding or integration work. This interoperability reduces the technical burden on businesses and encourages broader participation in agent-enabled experiences.
By decoupling agent behaviour from proprietary backend interfaces, UCP shifts the focus from point-to-point engineering work to shared standards and flexible commerce flows.
For ecommerce platforms and brand leaders, this raises the possibility of true scale in agentic commerce rather than isolated pilots.
One of the most visible impacts of agentic commerce will be on how customers interact with brands and products online.
Traditional ecommerce depends on users navigating search bars, menus, filters, and comparison tables. Under an agentic model, a shopper might express intent in natural language (spoken or typed) and an AI agent will take that intent and act on it.
Imagine a customer telling an agent: Find a gift for my partner’s birthday under a certain budget and have it delivered by next Friday. An agent operating over UCP could locate inventory, compare offers across merchants, build a cart, complete checkout, and trigger delivery — with the entire process handled in a conversational interface.
This capability changes the nature of engagement. Merchants will have to consider:
These considerations are not incremental tweaks but shifts in how user journeys are designed, measured, and optimised.
The true value for customer experience lies in reducing friction and time to purchase while preserving clarity, trust, and brand authenticity — not in replacing human choice with automated decisions.
Agents should act as proxies for user preferences, not as black boxes that obscure why certain recommendations or purchase decisions were made.
Integration of agentic commerce has implications across the ecommerce ecosystem, not just at the storefront layer. The value of UCP extends to areas like supply chain, inventory visibility, and marketing orchestration.
Since UCP standardises interactions across discovery, checkout, and payments, it therefore encourages businesses to align their inventory and pricing systems with real-time, machine-readable APIs rather than batch feeds or manual exports. This alignment brings benefits such as more accurate stock levels and dynamic offer delivery — capabilities that were traditionally siloed or available only in narrow contexts.
Marketing teams will also need to rethink how promotions and engagement signals are delivered in an agentic world. Standard marketing channels often rely on customers actively visiting a site, browsing, or clicking through curated campaigns.
In contrast, agentic commerce surfaces intent and offers in conversational flows where context and timing matter more than fixed landing pages.
Operationally, leaders will want to factor the following into their roadmaps:
By addressing these areas ahead of wide adoption, organisations can avoid retrofitting core systems under pressure — a common challenge in technology transitions.
From a strategic advantage perspective, early adopters of agentic commerce could see improvements in:
The open-source nature of UCP is also significant. By licensing the protocol under an open standard, companies can build on shared infrastructure rather than competing in fragmented proprietary silos. This openness can accelerate ecosystem growth and lower barriers to entry for smaller businesses.
However, there are real challenges:
These challenges are not trivial but are not unique to this moment. They reflect the broader evolution of ecommerce from handcrafted integrations to programmable, standards-based platforms.
For businesses willing to invest in the underlying infrastructure, agentic commerce with UCP can shift ecommerce from a product-centric model to an intent-driven ecosystem.
It is tempting to view agentic commerce and the Universal Commerce Protocol as distant innovations. In practice, what is happening is already influencing how search engines, marketplaces, and large platforms design their shopping experiences. Features like integrated checkout in AI search surfaces and conversational assistants that complete tasks on behalf of users are gaining traction.
Businesses need to grasp that this is not just another layer of automation. It is a change in how transactions are initiated, evaluated, and executed.
Agentic commerce reframes shopping from a manual sequence of interactions to a dialogue between user intent and machine capability — and UCP makes that dialogue actionable across the entire commerce stack.
This matters strategically because:
The organisations that navigate this transition well will not only streamline operations but will also build systems that are resilient to future shifts in technology and customer behaviour.
Before the FAQs, here are the core insights from this article:
These questions reflect real queries we hear from ecommerce leaders and technical teams evaluating the shift toward agentic commerce.
Agentic commerce refers to systems where AI agents autonomously handle parts of the shopping journey — from product discovery and comparison to checkout and payment — based on user intent and preferences. It moves beyond recommendation engines to actionable execution by software.
Traditional ecommerce integrations are custom and point-to-point. UCP standardises the commerce journey, enabling any compliant agent to interact with a merchant without bespoke engineering for each platform or agent type.
No. UCP is a protocol, not a marketplace. It standardises communication so agents can work with existing systems more efficiently, preserving merchant autonomy over their storefronts and customer relationships.
Yes. The protocol has been introduced and is supported by major platforms and partners, but widespread adoption will depend on merchants updating their systems to be agent-ready.
Agents can still work in limited ways without UCP, but organisations that implement the protocol will be more discoverable and easier to transact with across agentic commerce surfaces.
Start with structured product data, API readiness, and internal alignment on how agentic interactions fit into your commerce strategy. Consider customer trust, data governance, and measurement approaches that reflect intent-driven behaviour.
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