Agentic commerce is here. Is your business ready?

Eric Shea

Commerce Lead, PwC US

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Moving from clicks to commands

For decades, humans drove digital commerce. They searched. They researched. They compared products and checked out. Brands competed fiercely for visibility at each step of that journey. But today, a new layer is emerging—agentic commerce—where AI agents are taking the wheel, directed by humans, occupying an important space between customer intent and commercial execution.

Retail and consumer packaged goods (CPG) brands sit squarely at the center of this structural revolution. AI agents aren’t just a new interface or feature; they represent an entirely new channel. As such, there are new opportunities for breakthrough business models and competitive advantages, but there can also be plenty of risks.

When AI agents enter the journey

As the structure of digital commerce changes, retailers are already navigating powerful new forces helping drive consumer behavior. Digital-native behaviors are collapsing the journey from "want it" to "bought it." Culture is acting as shelf space—trends today show up in shopping carts tomorrow, not next quarter. Generational shifts are changing the way brands should think about identity, loyalty, and customer expectations.

As these factors converge, AI agents are becoming an increasingly powerful participant in the buying process, helping consumers navigate choices and make decisions. In an agentic commerce world, AI agents can act on behalf of customers to find products, compare options, and even, in some cases, complete transactions.

It’s an entirely new model of digital buying, and the shift is already measurable. According to PwC’s 2025 Holiday Outlook, 68% of people say they’re likely to use AI to compare flights, while 57% say they’re likely to use it to book travel. Younger generations are diving in even faster—76% of millennials say they’re likely to use AI for travel recommendations. In other words, even if AI-enabled purchasing lags slightly behind, consumers already are very comfortable using an AI agent to discover products and make plans.

Discovery is moving upstream, taking place before customers even reach a traditional digital shelf. Instead of scrolling product grids or scanning links, many consumers are querying language models and trusting AI systems to evaluate options, weigh tradeoffs, and guide decisions.

The flow is changing:

Customer expresses intent
Agent synthesizes options
Agent routes demand
Transaction executes

In response to this new era in digital commerce, brands are already experimenting with ways to engage shoppers earlier in the commerce journey. Some have introduced AI-enabled creative experiences, such as design tools, that invite consumers to co-create products and share their designs across social platforms, deepening engagement well before a purchase begins. Others have started applying AI to hyper-personalize messaging and content across channels, driving stronger engagement and repeat customers.

Still others have deployed conversational AI assistants that help guide customers through product selection. Product listings themselves are increasingly auto-generated or enhanced by AI. This makes it easier for buyers to discover relevant items. Together, these efforts signal a broader shift: AI-enabled experiences are reshaping the earliest stages of commerce, from discovery and inspiration to decision-making and demand routing.

Agents are sitting between intent and transaction, evaluating structured data, fulfillment reliability, pricing logic, interoperability, and trust signals. They’re also routing demand based on machine-readable consistency, not visual merchandising alone. So, how brands show up within AI agents could very well change their competitive equation more than any front-end redesign.

What shifts when agents decide?

AI’s increasing role in discovery and execution challenges several long-standing assumptions in commerce. Here are a few trends to watch:

Discoverability is in flux. In this new environment, traditional search optimization and digital shelf tactics only get you so far. Structured, consistent, and authoritative data is becoming the primary signal. Being machine-readable matters just as much as being visually compelling. We're not just talking about basic product details like color, size, or material. AI agents need richer, more structured data to effectively serve shoppers asking questions like, "Is this the healthier option?", "Will this hold up over time?", or "Am I getting the most value for my buck?" Most e-commerce systems weren’t built to handle that kind of nuance.
Loyalty is changing. Agents enhance reliability, performance, and interoperability. They interpret things like fragmented product data, rigid checkout logic, and inconsistent fulfillment signals as friction. Over time, agents may develop preferred supplier patterns based on system-level trust signals, not just brand affinity.
The cycle is speeding up. AI systems are increasingly responding to demand signals in real time, which means the loop between intent, signal, and execution is tightening. Enterprises that rely on lagging indicators risk reacting only after upstream systems have made important routing decisions. Suddenly, quarterly planning cycles are feeling sluggish.

For retail and CPG leaders, the question isn’t whether AI will influence commerce—it is already. The real question: Where is your business most exposed to a decision layer you don't directly control? It’s also important to ask: Which parts of your growth model assume human browsing behavior? Where are your systems enhanced for presentation rather than interoperability? How resilient is your architecture if demand begins to flow through autonomous intermediaries?

Two sides of the same system

Agentic commerce is often described as a front-end phenomenon. But in our experience, that only accounts for half the system. On one side, AI agents act on behalf of consumers, interpreting intent and forming demand across owned properties and AI-native environments. On the other, enterprises should translate that demand into execution across inventory, pricing, fulfillment, and store operations.

The bottom line: Agentic commerce shapes demand formation. Agentic store operations enable demand execution. Together, they form a closed loop.

When a synthetic signal identifies rising interest in a specific attribute or product, execution systems should respond dynamically. When an agent routes a transaction, pricing logic, availability, and fulfillment should resolve without friction.

The moment before normalization

Agentic commerce won’t arrive as a single launch event. It’s already embedding itself across search, AI assistants, enterprise platforms, and brand-owned experiences. As adoption scales, routing decisions may increasingly occur upstream of traditional digital shelves.

The opportunity is significant, but so is the exposure. Industry leaders should direct their teams to redesign their platforms for interoperability, structured trust, and real-time execution. Those who act now can grab priority as agents interpret and route demand. Those who wait may find they’re deprioritized from agentic commerce flows.

Across retail and consumer markets, industry leaders are struggling with how to enter this next phase and design for a world where AI agents are at the wheel. You can explore PwC’s perspective on agentic commerce and the capabilities required to design for an AI-driven buying landscape.