By Jessica Leitch
Over the next decade, retail will leave behind today’s channel-based model and its distinctions between physical and digital experiences.
We’re already experiencing how AI has reshaped ecommerce through features like conversational chatbots and virtual try-on. The bigger AI transformation story is behind the scenes, where retail is being redesigned in less visible but more impactful ways.
Over the next decade, retail will leave behind today’s channel-based model and its distinctions between physical and digital experiences. In its place, we’ll see a tightly integrated ecosystem that blends digital and AI experiences into physical spaces. Retailers that embrace this transformation as a redesign will lead on customer experience and AI value creation.
Innovators in the space are already experimenting in a few key areas: physical and ambient AI, generative engine optimization (GEO), and agentic commerce.
Dissolving the digital-physical retail divide
Physical AI brings intelligence directly into warehouses and shop floors through agentic robotics. These AI-powered digital workers leverage computer vision and other digital sensor technologies go beyond automation and respond to changes in the environment. Some retailers are testing smart robots that can show customers around a showroom or store to help them find exactly what they are looking for. In the warehouse, physical AI devices can scan racks for quick, accurate inventory updates and retrieve a product to fulfill orders faster than human workers can.
One major retailer has improved efficiency by 25% in the facilities where it’s trialing physical AI devices. Physical AI also frees employees to focus on higher-value customer interactions that require more human engagement, such as helping to plan a kitchen using the company’s products instead of helping customers locate cabinet pulls.
While physical AI is reshaping the store and warehouse environments, ambient AI has the potential to reshape the customer’s environment, wherever that might be. The effects of ambient AI were already on display during the 2025 winter holiday season. Adobe’s yearly analysis of holiday shopping trends found a 693% year-over-year increase in the amount of ecommerce traffic coming from AI search results and checkout tools embedded in some chatbots. Soon, some AI chatbots will show ads, allowing retailers to raise their visibility in AI product discovery and search.
These are just the start of what’s possible with ambient AI. Agents embedded in websites and campaigns will be able to adapt customer journey content and navigation in real time. Eventual advances in AI logistics could lead to anticipatory customer experiences like predictively shipping what customers will need next, or autonomous “storefronts on wheels” to bring customers exactly what they need when they need it. Instead of customers seeking out a channel to shop, retailers will bring the experience to them in new ways.
Staying visible in the GEO era
With 58% of consumers now using AI instead of traditional web search for product recommendations, best practices for brand and product discoverability are changing fast. Where SEO used to dominate, GEO is now a necessity as well, because AI delivers summaries rather than lists of links. This shift requires a new strategy based on building authority through trusted third-party content rather than optimizing for keywords. That’s because appearing in AI search summaries depends on retailer’s presence in content that AI agents and LLMs learn from, such as product review sites, major news outlets, and expert communities.
Successful GEO relies on:
- PR strategies to earn mentions in trusted sources
- Content that aligns with the way AI users ask questions and AI bots seek answers
- New approaches to rank tracking designed specifically for GEO
Without a strong GEO program, brands risk becoming invisible to consumers who use AI to search and make a purchase without ever clicking a link.
Leading global retailers and brand groups are already auditing their AI visibility to understand how they appear across major models. Such GEO audits can show retailers where they can boost visibility by restructuring site content, identifying ideal targets for earned media, and rebalancing their channel presence to favor channels that AI models use to create their summaries.
Reshaping how customers buy
Along with the shift to GEO and more use of physical and ambient AI, agentic commerce is also transforming retail. With agentic commerce, the customer journey fundamentally changes. Instead of searching, clicking, comparing, and checking out, customers can ask their AI agent to handle those tasks for them. Using what they know about the customer and the context of the product search, agents will become the primary decision makers in many buying journeys. One major retailer announced in 2025 that it was launching an in-app “super agent” to help customers compile product lists for meals and events and order those items.
Now, retailers need to plan buying journeys driven by agents as well as those driven by customers. Designing both options can help brands keep their products visible to retail shopping agents. It can also increase repeat purchases as shoppers set orders on agentic autopilot.
Designing the retail transformation
The most innovative retailers are already reshaping customer experiences and expectations with these AI technologies. Retail and design leaders who want to keep up need to redesign their CX, visibility strategies, and buying journeys to leverage AI. These redesigned processes will also need unified data foundations. As part of this redesign, strategic retailers will also:
- Identify physical and ambient AI use cases to pilot
- Audit their brand’s and products’ GEO visibility
- Restructure product content, data, and CX flows to accommodate human and agentic shoppers
Approaching all these activities from the perspective of trust-building is important. As retail transforms, it’s not only customer trust that brands need to earn. They’ll also need to learn how to create the signals that LLMs and AI agents look for to decide what to recommend, what to buy, and what to ignore.
Jessica Leitch leads frog North America at Capgemini Invent.
Photo by Joshua Rawson-Harris on Unsplash
