Over the past two decades, eCommerce has followed a reliable logic: customers search, brands respond. Whether through Google, on-site search, marketplaces or social platforms, discovery has traditionally started with a click or a query.
In the UK, online retail grew by over 3 % in 2024 to more than £125 billion, according to Mintel’s UK Online Retailing Market Report 2025, and is forecast to grow by around 1.7 % in 2025. Mintel eCommerce Report 2025. Even within this steady growth, however, the way consumers find products is undergoing one of the most significant shifts since the arrival of mobile commerce.
A large share of search behaviour has already moved into what is known as zero-click search where users receive answers directly on the search results page without clicking on any website. Google’s featured snippets, AI overviews, product panels and knowledge boxes are now resolving millions of queries instantly, reshaping how consumers discover information long before they reach a retailer’s site.
But the bigger transformation is happening just beyond this: AI-driven discovery and intelligent agents.
Today’s early-stage intelligent agents already assist shoppers by surfacing recommendations, comparing options and simplifying decision-making. Industry leaders describe this as the first wave of “agentic commerce” a shift where AI does more of the searching, sorting and filtering that humans once performed manually. These agents aren’t replacing the buying journey yet, but they are clearly beginning to shape it.
Taken together, zero-click search and early agentic behaviour signal a new era of AI-led, low-friction discovery. Customers are doing less; systems are doing more. And as this develops, the brands that succeed won’t be those generating the most noise, but those whose product data, content and experiences are structured clearly enough for AI to interpret and confidently surface to customers.
At Williams Commerce, we believe this marks the beginning of a profound shift in how retailers attract, convert and retain customers and the retailers who prepare now will be the ones best positioned to thrive in an AI-shaped commerce landscape.
#1. Zero-Click Discovery Is Already Changing How Customers Shop
Zero-click discovery began as a search-engine phenomenon, but it is rapidly expanding into core parts of the customer journey. Google now resolves millions of queries directly inside the results page. Shoppers increasingly see product carousels, size guides, comparisons and AI-generated summaries before ever reaching a retailer’s website.
At the same time, recommendations across platforms like Instagram, TikTok, Meta Shops and Pinterest are becoming less reactive and more predictive, surfacing products based on behaviour, context and inferred intent rather than explicit search terms.
This means discovery is becoming decentralised. Customers still buy, but the moment of influence has moved earlier, faster and outside the retailer’s control.
“Retailers often think their customer journey starts on their homepage. It doesn’t. Increasingly, it starts in spaces the retailer never sees, AI search results, social feeds, voice prompts or recommendation engines,” says Tanya Peasgood, Head of Consultancy at Williams Commerce.
“Our role is helping brands structure their data and experiences so AI can understand them clearly enough to bring them into those moments of discovery.”
In a zero-click environment, your product pages matter, but your product data matters more.
#2. The Rise of Intelligent Agents, From Assistants to Active Participants
While zero-click behaviour is already mainstream, intelligent agents represent the next wave of change. These early-stage AI systems can analyse needs, compare products, consider price, check stock availability and propose optimal choices to users, with minimal human input.
Examples emerging today include:
- Retail copilots that ask questions and guide customers to products
- AI support agents that help customers troubleshoot, reorder or change subscriptions
- Voice assistants that manage reordering or replenish household items
- Early “agentic commerce” models where AI compares multiple retailers before suggesting a choice
These agents don’t replace human decision-making, but they shape it, by narrowing the field and reducing the friction that leads to drop-offs.
“We’re starting to see AI agents behave less like search tools and more like shopping companions,” says Tanya.
“They don’t need the customer to browse ten pages. They can take a need, filter hundreds of products and surface the top two. That changes what visibility means for retailers.”
In a traditional search world, retailers optimise for humans.
In an agent-driven world, they must also optimise for how AI interprets and ranks their products.
#3. What Retailers Need to Do Now, Before AI Becomes the Primary Gateway
The shift toward zero-click and AI-mediated shopping won’t happen overnight. But the foundations are forming fast enough that retailers need to act now, not later.
Williams Commerce is already working with brands across Adobe Commerce, Magento, BigCommerce and Shopify to prepare for this shift. The focus is on four critical pillars:
- Making product data AI-ready
Clean, structured, technically rich product data is becoming core to discoverability. AI agents rely on attributes, accuracy and clarity, not just keywords.
- Implementing AI-powered search and merchandising
Retailers using AI to analyse intent and behaviour today build the datasets that will matter tomorrow.
- Strengthening integrations for real-time accuracy
AI systems don’t tolerate inconsistent stock, pricing or lead times. Real-time integration between ERP, PIM and eCommerce systems becomes essential.
- Testing conversational and assistive journeys early
Voice flows, chat-based shopping, and guided product selection will become the new entry points for discovery.
“The biggest misconception is that this is a future problem,” Tanya adds.
“But the retailers who prepare early will be the ones AI agents trust, because their data is clean, their systems are connected and their product information is consistent. You can’t bolt that on later.”
Retailers who delay risk becoming invisible in an AI-led discovery ecosystem.
Tanya says… “When we introduce AI into customer service, the goal isn’t to replace the team, it’s to support them. We help businesses decide where AI can genuinely make things easier and where a human touch is essential. By setting tone, escalation rules and reviewing performance over time, we make sure customer service still feels personal, just far more sustainable for the people behind it.”
#4. What AI-Readable Commerce Looks Like in Practical Terms
For retailers to win in this era, they must make commerce readable, not just for humans, but for AI systems and agents. Here’s what it means in practice:
Clean, structured product data
AI agents don’t “see” your website the way a customer does. They rely on rich, machine-interpretable attributes such as size, material, lead-time, stock location, and contract pricing. According to a recent McKinsey & Company survey, 23 % of organisations report scaling agent-based AI systems today, and a further 39 % are experimenting. McKinsey. The State of AI That means the infrastructure you build now must be ready for machine consumption.
Real-time system integration
In a world where AI can initiate or influence purchases without human clicks, delays and inaccuracies become liabilities. Its essential that data flows seamlessly from ERP to storefront and back. Data strategists warn that for agentic AI to perform reliably, eCommerce companies need to shift from static to dynamic, unified, orchestrated data landscapes. Business Insider. Harness Agentic AI
Conversational and assistive touchpoints
Whether voice, chat, image-search or a virtual assistant in a car, the entry point to eCommerce is becoming less a web page and more a contextual interaction. Agents can prompt a re-order or suggest the right product without a shopper wandering through categories.
Lets just quickly discuss contextual interaction.
In AI-driven commerce, interactions become contextual, happening in the moment based on the customer’s behaviour, environment or conversation, rather than from deliberate search queries or page-by-page browsing.”
Lets quickly look at a few examples of this in practise.
Voice prompts at home. A customer says: “Alexa, I’m almost out of washing tablets.” AI replies with options, compares prices, checks subscriptions and suggests a bundle; all without the customer opening a website.
This is contextual because it’s reacting to a moment of need.
Another example might be reordering prompts based on behaviour
An AI agent notices a B2B buyer usually orders specific consumables every 28 days.
Before they run out, the agent says: “You’re due to reorder. Would you like the same quantity as last time?” The agent acted because of observed timing and behaviour, not because the user searched.
What about this example: Image-based shopping. A user takes a photo of a coat they like. The AI identifies the style, price range and alternatives, then presents products that match. The customer didn’t search, the image was the context.
To sum up…Contextual interactions helps explain how AI agents fit into the emerging zero-click world:
- Customers won’t always search
- They won’t always browse
- They won’t always click through to a website
Instead, AI will insert helpful moments into the customer’s world at the right time, in the right place, with minimal effort required from the human.
That’s what makes it different from traditional online shopping. It sounds remarkable in theory, but for retailers it naturally raises a big question: how do you even begin to build for this? The truth is that seamless AI-led interactions only happen when the foundations; data, structure, integration and experience, are in the right shape long before the AI steps in.
Then measure what matters
In traditional eCommerce you evaluate clicks, sessions and page views. In an AI-readable world you measure intent accuracy, time-to-purchase, and system trust. McKinsey estimates that agentic AI could influence up to $3 trillion to $5 trillion in global retail commerce by 2030. McKinsey & Company. A New Era for consumers and merchants
#5. How Williams Commerce is Engineering the Shift towards AI-Enabled Retail
The shift to zero-click and agent-mediated commerce is not cosmetic. It is structural. It changes how data flows, how decisions are made and how customers discover products. At Williams Commerce, we aren’t talking about this in theory. We are already working inside retailers’ storefronts, systems and operational realities to help them prepare for the next era of digital commerce.
Active service, not passive advice
Many agencies talk about AI. We’re implementing it.
Williams Commerce helps retailers operationalise the four pillars that make AI work in practice: product-data readiness, AI-powered search and merchandising, real-time system integration, and early conversational journeys.
These aren’t nice-to-haves. They are the new foundations of discoverability and conversion in an AI
-first environment.
Platform-Agnostic, But Strategically Opinionated
Retailers today don’t just need a platform. They need a platform that can carry the next era of AI-enabled commerce; clean data, real-time integrations, structured content and predictable architecture. That’s why Williams Commerce works confidently across Adobe Commerce, Shopify, BigCommerce and composable environments, but always with a clear point of view on what each platform does best and how to get the most from it.
We don’t simply “build” on these platforms, we work with them to ensure they are engineered for AI-readiness.
This means helping retailers organise and optimise the parts of the ecosystem that AI systems rely on:
- Data structure and product attributes
- Taxonomy, categorisation and relationships between products
- Clean, consistent content that AI can interpret and surface
- Integrations that ensure stock, pricing and rules remain accurate in real time
- Search and merchandising tools that use behavioural signals, not static rules
Each platform provides strong foundations — but their real power is unlocked when a partner understands how to shape them for AI-driven discovery, personalisation and automation.
“A lot of retailers assume the platform will handle AI for them,” says Tanya. “But the results depend entirely on how the data, structure and integrations are set up. That’s where we guide clients, turning good platforms into AI-capable ecosystems.”
Williams Commerce helps retailers make confident decisions about where to invest effort, which native features to use, when to extend with third-party tools and when to keep things simple. Our role is to ensure that whatever platform a client chooses, it’s not just functional, it’s structured, connected and intelligent enough to support the next generation of commerce.
Tanya ends with…“The biggest misconception is that this is a future opportunity. But the retailers who prepare early will be the ones AI agents trust, because their data is clean, their systems are connected and their product information is consistent. You can’t bolt that on later.”
Today you may be testing an AI-search plugin or piloting AI driven product recommendations. Tomorrow you may be operating inside agents’ decision-frameworks. Williams Commerce will help brands design for the short term and build for the long term simultaneously.
Don’t wait and watch. Start now and turn the AI advantage into your competitive edge.
Ready to talk about what a zero-click world means for your eCommerce business?
Email Tanya and her team to set up a meeting. [email protected]
