Why agentic commerce is the new front door to retail

How AI conversations are replacing traditional search results for retail

It’s the day before a friend’s birthday. You need a gift under 50 dollars that arrives tomorrow. Instead of opening a dozen tabs, you ask an AI assistant. In a single conversation, it understands your context, evaluates constraints, and recommends a choice you can act on with confidence and feel good about giving.

That moment illustrates a shift underway in retail. ¹Bain & Company estimates that 30% to 45% of US consumers already use generative AI to research and compare products. Shopping is increasingly happening within AI-guided conversations, where agents move beyond listing options to interpret intent, evaluate tradeoffs, and guide decisions in real time.

For CMOs, this is not simply another channel to optimize. It represents a fundamental change in how influence is earned and how brands compete for loyalty, margin, and growth.

What is agentic commerce and how is it changing the shopper experience

For years, the front door to retail was a homepage, a search box, or a category page. Growth came from capturing keywords, driving traffic, and optimizing funnels, often measured through last click attribution.

Agentic commerce changes that. The new front door is the conversation.

Instead of navigating pages and filters, shoppers now express intent in natural language: “I need a sustainable gift under fifty dollars for a coworker who loves cooking. It has to arrive by Friday and feel premium, not generic.” The conversation itself becomes discovery, surfacing unexpected options and sparking new ideas. Through continued dialogue, those possibilities sharpen into confident decisions.

What matters is not just what is recommended, but how that recommendation is shaped using context in the moment of decision.

How AI shopping agents generate insights that drive business growth

The following video shows agentic commerce in action. It demonstrates how a single request can generate value both for the shopper and the brand.

A shopper asks for a coat for a trip to Aspen in February. The agent immediately goes to work, considering weather data, the shopper’s style preferences, available inventory, pricing, reviews, and more.

At the same time, that request also produces actionable insights for the brand. The marketer sees intent signals combined with internal retail data and broader market trends. Patterns emerge, showing rising demand for winterwear. An AI agent recommends a targeted promotion, the marketer approves it, and the offer is delivered back to the shopper.

The shopper receives curated recommendations with a timely promotion, makes a confident choice, and heads to the slopes in the right jacket.

This is agentic commerce in action. The conversation delivers value in the moment while simultaneously generating learning that informs future business decisions. This creates a feedback loop that strengthens with every interaction.

What sets this apart from previous shifts in the industry is when influence occurs. It is no longer applied only before a decision through advertising or merchandising. Influence is now shaped during the decision itself, as real-time signals flow between shopper and brand.

What makes the agentic commerce shift different

Retail has gone through major transitions before from physical stores to websites, from desktop to mobile, and from owned commerce to marketplaces. Each wave opened new channels of demand.

Agentic commerce goes further. It changes how decisions themselves are made. It introduces a decision layer between shoppers and brands. Behind every interaction sits a learning layer, where signals flow back to merchants, informing decisions that shape recommendations, promotions, assortments, and experiences.

The scale of this shift is substantial. ²McKinsey projects that by 2030, the US business-to-consumer retail market alone could see up to $1 trillion in orchestrated revenue from agentic commerce, with global projections reaching $3 trillion to $5 trillion. This is not an incremental growth. It represents a reconfiguration of how products are discovered, evaluated, and purchased.

For CMOs, strategy now centers on guiding decisions at the moment of choice and capturing the intelligence those interactions produce. Brands that earn influence in the moment and compound what they learn over time are better positioned to build lasting advantages in pricing, loyalty, and lifetime value.

How to build competitive advantage in agentic commerce

As agentic commerce scales, two imperatives are emerging, and leading brands are pursuing both.

Ensure discoverability wherever shoppers ask

AI assistants such as Microsoft Copilot are becoming common starting points for product discovery. When a shopper asks, “What’s the best running shoe for marathon training?” or “Find a sustainable laptop bag under $200,” AI agents interpret intent and surface recommendations.

To compete in these moments, brands must ensure their products, attributes, and value propositions are accurately represented in AI platforms. Success depends on being discoverable when consumers ask questions, not just when they type keywords into a search bar.

Build owned agentic experiences that capture learning

Discovery on third party platforms creates awareness. Owned conversational experiences create advantage. When brands deploy AI agents on their own properties, they capture the context behind each decision. That intelligence feeds merchandising, pricing, inventory, content strategy, and personalization. Just as importantly, brands can use these insights to enrich product catalogs with the language, attributes, and use cases that improve discoverability on third-party AI platforms, strengthening AEO and GEO performance over time.

Trust plays a critical role here. According to Bain & Company, while consumers increasingly use AI for research, they currently trust brands’ on-site agents three times more than third-party agents. That trust advantage makes owned conversational experiences more effective at driving conversion.

Why the winning move is doing both

The question for CMOs is not whether to participate in agentic commerce. The shift is already underway. The real question is whether your brand will appear only in third-party recommendation engines, or whether it will also own the intelligence that turns interactions into durable advantages in pricing, loyalty, product development, and lifetime value.

Four actions retail leaders can take now to prepare for agentic commerce

Agentic commerce is taking shape, and the path to readiness is clear.

1. Optimize for AI discoverability. Most product data was built for search filters, not AI conversations. Brands need structured attributes, descriptions that reflect real use cases and brand voice, and accurate information for pricing, availability, fulfillment, and policies. This practice, often called AI engine optimization (AEO) or generative engine optimization (GEO), helps ensure AI can accurately represent your products when shoppers ask questions across search engines and conversational platforms.
2. Launch owned conversational experiences to learn fast. Deploying AI shopping assistants on owned surfaces creates a feedback loop. Each interaction and conversion generates insight into customer intent, preferences, and friction points. Marketers can use these insights to continuously improve product catalog data, strengthening AEO and GEO performance across all platforms.
3. Design for openness and portability. Agentic commerce spans websites, apps, stores, partner channels, and third-party platforms. Product intelligence and brand logic need to travel across surfaces so brands can participate in new ecosystems without losing differentiation or starting over each time an interface evolves.
4. Govern measurement so learning compounds into growth. As AI agents mediate more of the shopper journey, brands risk losing visibility into how decisions are made. Clear expectations around signal sharing, experimentation, and insight ownership helps ensure every interaction strengthens the business.

Trust and privacy run across all four moves. Transparent recommendations, responsible data use, and alignment with brand values shape long term loyalty.

A new growth era for retail CMOs

Agentic commerce does not replace marketers or merchants. It elevates their role, bringing intelligence, context, and action closer to the moment of choice. For CMOs, this is a leadership moment. It is an opportunity to shape how customers discover and choose products, turn data into conversational intelligence, and build trust as a durable source of differentiation.

Those who define how shoppers discover, trust, and choose in an AI mediated world will define the next era of growth in retail and consumer goods.

Prepare your brand for agentic commerce

Optimize your product data and brand content so AI agents can accurately represent and recommend your products across platforms. Access our guide on AEO and GEO to advance your business for AI-driven shopping.

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¹Bain & Company estimates that 30% to 45% of US consumers already use generative AI to research and compare products.

²McKinsey projects that by 2030, the US business-to-consumer retail market alone could see up to $1 trillion in orchestrated revenue from agentic commerce, with global projections reaching $3 trillion to $5 trillion