by VML Commerce

In a world that never slows down, is your brand ready to be recommended by AI agents?

VML observes in The Future Shopper 2025 that customer journeys are compressing. According to the study, 58% of shoppers want to move from inspiration to purchase as fast as possible, a dynamic VML calls "compressed commerce."

Generative AI has already changed the way consumers search, compare and decide. The numbers speak for themselves: traffic to US retail sites from GenAI browsers grew by 4,700% in 2025, and McKinsey estimates that agentic commerce could generate up to $1 trillion by 2030.

The next shift goes even deeper. Soon, consumers won't just visit your site to buy. They'll ask an AI what to choose, why to choose it, where to buy it, and sometimes even ask it to buy on their behalf.

Commerce isn't disappearing. It's changing its interface. And in this new interface, one question becomes strategic:

If an AI agent were to recommend your products tomorrow, would it have all the right reasons to do so?

MCP Ready ENG
Agents will allow us to express our shopping wishes and they will do the job. This is not science-fiction, this is tomorrow.

Commerce is entering its agentic era

Atlas and Arc
Atlas and Arc are two of the new Agentic Browsers: the Chrome and Firefox of tomorrow.

For a long time, AI mostly helped with inspiration. It could suggest a gift idea, recommend an outfit, compare two products or help articulate a need. But when it came to actually buying, the journey almost always looped back to a traditional interface: search engine, marketplace, product page, cart, checkout.

That gap is now closing.

Commerce agents no longer just respond. They can understand an intent, query a catalogue, check product data, compare options, build a cart and guide the path to purchase.

This is no longer just a new user experience. It is a new e-commerce infrastructure. A quick demo below...

What does MCP mean for your brand?

nouvelle entrée agents IA
What does MCP mean for your brand?

You have spent years optimising journeys across Google, Amazon, retailers, marketplaces, social media and retail media.

Get ready for a new entry point: AI agents.

Because if tomorrow a consumer asks: "Which product best fits my needs?" "Which brand would you recommend?" "Which one is available right now?" "Can you build me the best cart?"

Then the agent will need to be able to understand your products, access the right information, identify your proof points, communicate your benefits and, potentially, trigger an action.

The battle will no longer be just about traffic. It will be about comprehension, recommendation and activation by AI.

Failing to prepare to MCP means risking...

ne pas se préparer c'est risquer
Failing to prepare to MCP means risking
  1. Becoming invisible
    If your product data is not sufficiently structured, your products may simply not surface in agentic recommendations.
     
  2. Being misrepresented
    If your benefits, proof points and differentiators are not clearly defined, AI may reduce your product to nothing more than a price, a rating or a stock status.
     
  3. Losing revenue
    The purchase journey can start, and sometimes end, outside your website. The customer relationship does not disappear, but it shifts.

A 5-day workshop audit over 2 weeks to give you full clarity

workshop 1

Workshop 1

Business & Customer Journey

Objective:
Understanding the client's business context

Duration: 2 to 4 hours

Content:

  • Deep dive into the 'product catalogue exposure' use case tailored to the client's context
workshop 2

Workshop 2

Architecture & APIs

Objective:
Mapping of the e-com ecosystem

Duration: 2 to 4 hours

Content:

  • Technical mapping
  • Data quality & structure
  • Existing / missing APIs
workshop 3

Workshop 3

Data / Security / Ops

Objective:
Data mapping

Duration: 2 to 4 hours

Content:

  • Data access
  • Auth / OAuth / tokens
  • Exposure to external agents
  • Logs / observability / control

Going further

VML Commerce helps you prepare your e-commerce ecosystem for this new reality.

  • We audit your ability to be understood by AI agents.
  • We identify friction points in your product data, content, customer journeys and systems.
  • We prioritise the highest-value use cases.
  • We build a roadmap to move from experimentation to activation.
  • We prototype concrete agentic experiences.

Agentic Commerce: what we can activate

  • An AI Commerce Readiness Audit to assess whether your products, content, data and customer journeys are ready to be leveraged by AI agents.
  • Product data optimisation to make your product pages more accurate, better structured, more contextualised and more easily interpretable.
  • Agentic use cases to guide discovery, personalised recommendation, product comparison, cart building, cross-sell, assisted reorder, pre-purchase assistant or conversational experience connected to your catalogue.
  • Rapid prototypes to concretely test the value of a commerce assistant, a recommendation agent, a WhatsApp journey, a conversational cart or a prototype connected to your systems.

Please provide your contact information to continue.

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