Shoptalk Europe: How can brands keep up with the pace of agentic commerce?

The direction was clear: more AI-powered discovery, agentic shopping experiences, personalized commerce, and pressure to connect content, data, media, stores, and technology into one working system.

That’s the exciting stuff…and the easiest themes to wax on about. What’s trickier to grapple with is whether most organizations can actually deliver against an agentic vision at the pace it requires.

At the interface level, a smarter product finder, shopping agent, AI-powered search experience, or more adaptive checkout journey may seem relatively simple. But behind each of those experiences is a long, intertwining chain of work that weaves together everything from product data to platform logic to CMS structure, and much more.

What our onsite DEPT® team heard from all directions is that as AI raises the ceiling for what shopping experiences can become, it’s exposing just how much brands need an operating model that can deliver those experiences faster, smarter, and at scale.

At Shoptalk, there was no debate that AI is influencing digital discovery and fundamentally shifting the customer journey. Product recommendations, AI search, shopping agents, retail media, and conversational commerce are all driving a future where customers increasingly rely on systems to help them find, evaluate, and compare products.

We’re seeing this shift in real time, and brands are feeling the pressure to ensure they can be accurately understood and represented across a growing number of AI-mediated environments. Generative Engine Optimization, or GEO, is a discoverability challenge. But in practice, it requires a significant amount of technical and operational input.

Merchandising teams need to structure product data. Content teams need to maintain product copy, imagery, and supporting assets. Technology teams need to keep integrations connected. Commerce teams need to keep catalogs accurate. Product and engineering teams need to test, refine, and deploy new experiences. 

In short: as the number of discovery surfaces grows, so does the work and data required to support them.
More importantly, this project doesn’t have a finish line—AI-powered discovery is evolving too quickly for that. To maintain visibility and performance, organizations need to continuously adapt their content, data, and customer experiences as new interfaces, behaviors, and expectations emerge. 

That shifts the scope from a contained marketing strategy to a business-wide operating model.

One of the more revealing themes at Shoptalk was that retailers don’t lack ideas. They lack the capacity to execute on all of them. Every opportunity discussed, GEO to business-to-agent strategy, creates additional operational complexity.

Retailers are feeling pressure to more continuously update and optimize their digital environments: product pages, search experiences, checkout flows, loyalty journeys, retail media placements, store tools, and the data behind all of it.

Traditional delivery can handle this work, but not always at the speed now required. And adding AI tools on top of the same old process doesn’t automatically fix the bottleneck. Moving faster only matters if teams can still launch, test, govern, and maintain those experiences once they reach real customers.

While Shoptalk brought these challenges to the forefront of conversation, we’ve been seeing them play out for some time now. And they’re a large part of what led DEPT® to launch Agent Studio earlier this week. The response at the show suggested the timing was right. One Shopify representative called Agent Studio the most exciting thing they had seen at Shoptalk.

Rather than focusing solely on individual productivity, Agent Studio is designed to help teams keep pace with the growing volume of changes modern commerce requires—from platform migrations and feature releases to content updates, testing, optimization, and ongoing maintenance.

Jeroen Schuijt, VP Sales at Optimizely, saw Agent Studio both at Shoptalk and in action during a recent migration to Optimizely. In his words: “The combination of quality and speed it brought was remarkable. It’s one of the most fundamental and strategic approaches to agentic delivery I’ve seen so far.”

Just as importantly, it’s designed around governance. Shoptalk attendees agreed that AI works best when paired with human judgment rather than treated as a replacement for it. The same principle applies here. In an agentic commerce environment, the human role becomes more valuable because the pace of change increases the cost of poor decisions.

Agents can accelerate execution and handle structured work, but architects, engineers, and product teams remain responsible for the decisions that affect quality, security, customer experience, and business outcomes.

But speed only solves part of the problem. Before a retailer can move faster, it needs a clearer view of what it is actually working with. This was the topic that drew the most interest in our Shoptalk conversations. A lot of retailers run heavily customized environments built up over years: logic no one fully maps anymore, undocumented integrations, dependencies that only surface when something breaks. Leadership wants to modernize, but can’t answer the questions that unlock the decision. Is this even possible on the platform we want? How big is the project really? What will it cost, and where are the risks?

That’s what our newly introduced Agentic Assessment is built for: a dedicated approach to solutioning that sits on top of agentic delivery. Before any build begins, we connect agents to a company’s own systems, the codebase, the ticket history, existing documentation, and map what’s actually there against the target solution. Instead of weeks of manual discovery and educated guesses, the work starts from evidence. A business walks away with a clear view of complexity, a target architecture, and a business case with a phased plan and cost comparison.

Shoptalk Europe confirmed where retail is heading and exposed many of the organizational and data gaps brands still face. AI-powered discovery, shopping agents, adaptive experiences, and more connected customer journeys are quickly moving from industry talking points to business priorities.

The most challenging aspect is that these experiences don’t exist in isolation, but depend on the interconnected systems, workflows, data, and teams that bring them to life. As the pace of change accelerates, the ability to continuously deliver, refine, and govern those experiences becomes a competitive advantage in its own right.

In an agentic commerce environment, the gap will widen between organizations that can talk about new experiences and those that can actually ship, test, govern, and improve them in production.