In 2026, your customer might not be a human browsing your website. It could be an AI chatbot or agent (think Perplexity, Gemini, Claude, or a specialized shopping bot) acting on a simple brief: "Find me the most sustainable red dress under £100 with four-star reviews and same-day delivery to London zone one." The retail industry has spent decades refining experiences built around human emotion, behavior, and loyalty. But what happens when the entity completing the purchase is not human at all?
This is not a distant hypothetical. The invisible shopper is already here, and retailers who do not prepare for it risk becoming invisible themselves. Critically, this is not purely a digital challenge. How you build the new hybrid customer experience, bridging the physical and the agentic, is where retailers will win or lose in the years ahead.
An agent acts on behalf of a human, executing a defined task from start to finish. Agentic commerce describes the phenomenon where an AI agent completes part or all of the discovery-to-purchase journey on a customer's behalf, without the customer ever interacting directly with your website, app, or store.
Consider Kieran. He needs a smart-casual outfit for a work event in two days, on a budget. His AI agent already knows his style, sizing, preferred brands, and existing wardrobe, and it executes the search for him. It shortlists options, cross-references reviews for fit accuracy and care instructions, and completes the transaction through his connected smart wallet. Kieran reviews the shortlist, tries the options via a virtual fitting, and hits confirm. The package arrives, wrapped in a third-party delivery company's branding. At no point did Kieran visit your store, digital or physical. He may not even know your brand name.
This scenario sounds futuristic, but the mechanics are already in motion. You can purchase directly from influencer content on Instagram and TikTok today, completing transactions in-app without ever knowingly engaging a retailer's owned channel. ChatGPT launched in-app payments in the US in 2025 for single-item purchases, with multi-cart and markets including the UK expected in 2026. Given the pace of AI development, with operator-style agents emerging at the start of this year, the full agentic buying journey is closer than most retailers are prepared for.
The strategic question becomes: if Kieran never entered your store, browsed your site, or interacted with your brand, how do you understand his preferences, build loyalty, and ensure your product range remains relevant to customers like him?
In a phygital world (where physical and digital experiences converge), data remains the foundation of competitive advantage. Yet time and again we hear the same objection from retailers: "Our data is too messy for AI." The reality is that waiting for an expensive two-year data architecture program and implementing a data lake before acting is not caution, it is a competitive liability. So what can you do more tactically to make it good enough?
The answer is not to ignore data quality; it is to prioritize the data that matters most to get started and use AI to help cleanse and improve that data. Applying the Pareto principle, focus on the vital 20% of data that will underpin your understanding of the new customer buying experience. Decide which SKUs you want to prioritize for initial agentic commerce pilots, based on trend analysis of the customers most likely to take this leap.
Then map your customer journey end-to-end, including the new digital moments that matter, and ask: what data points are actually influencing your customer (or agent's) decision to buy? These are your priority data assets. Metadata, including product materials, detailed sizing, sustainability credentials, real-time stock levels, delivery speed and customer reviews, are the signals an AI agent uses to discover and evaluate shopping decisions on behalf of a consumer.
How can you then automate the data collection and tagging of those priority SKUs using AI and machine learning, to improve Generative Engine Optimization (GEO) rankings and get the ball rolling?
Alongside this operational data, you also need behavioral insight: 40% of your Gen Z target market are buying via AI chat interfaces - how does your marketing strategy reflect that? 60% of your sportswear customers still come in-store to purchase trainers - what does that mean for your physical experience investment? This is the lens through which data becomes decision-making power. Run your cleansing program in parallel, use AI tools to accelerate the cross-mapping of disparate data sets, and focus on building momentum and continuous learning, rather than incur multiple-year delays whilst your competitors get ahead.
In 2025 research by Conveo, over 97% of participants in the ‘AI-Powered Shopper Study’ reported that AI has some degree of influence on their shopping behaviors, with 38% saying it influences them ‘a lot’ or ‘completely’. AI recommendations (51%) are twice as popular as advice from friends and family (26%) and five times more than in-store staff or online reviews. Over two-thirds of UK participants said that AI is their most trusted source for recommendations.
Shoppers across demographics are trusting AI for the discovery and evaluation stage of their shopping journeys at an unprecedented rate. Yet it remains to be seen whether this exponential growth will be seen for the purchase step, with cybersecurity and payment risk a major trust issue for many customers, preferring to complete the purchase themselves via the retailer's website.
Returning to Kieran’s suit purchase, this creates a wealth of opportunity for retailers beyond the end-to-end agentic commerce journey. From increasing brand awareness, offering upsell opportunities in the cart and providing visibility of cart abandonment, which can then be influenced to increase conversion.
It’s crucial not to assume this will always be the case - just two years ago, the concept of initiating a shopping journey via ChatGPT felt like a stretch, five years ago GenAI and ChatGPT weren’t in our lexicon, and twenty years ago, online shopping was a futuristic concept. For reference, Amazon was founded in 1994, which transformed the e-commerce landscape. For those with legacy payment systems which won’t support agentic commerce, this provides a short window of opportunity for experimentation and transformation.
The invisible shopper is not a future persona to plan for; it is a current reality to respond to. The challenge is not solely technological, with traditional organizational designs meaning siloed teams cannot move at the pace required to match your competitors, and leadership making decisions at a distance from the customer reality.
Responding effectively to agentic commerce requires a fundamental shift in how retail businesses are structured and how they make decisions. The customer experience (physical, digital, and now agentic) is no longer a function that lives in a slide deck. It is a live decision-making tool that should be guiding your C-suite and informing your board. Retailers who treat it as such will build the agility to trial, experiment, and learn fast enough to stay ahead of the disruption curve.
At Clarasys, our Double Diamond methodology is designed to break business inertia, align siloed teams around AI strategy and re-imagine the customer experience. By using agentic commerce as a shared decision-making opportunity, Clarasys can broker the complex, often difficult internal conversations that genuine organizational change requires. We help retailers identify pragmatic, data-led paths forward that build incremental, real-world gains without the cost and risk of multi-year transformation programs.
The question every retail leader needs to answer right now is not "how do we prepare for the invisible shopper?" It is "are we already too late to catch up with them?" For most, there is still time, but the window for deliberate, purposeful action is narrowing. With every disruption comes opportunity. The retailers who move now, with intention and the right foundations, will be the ones writing the playbook that others follow.
Ready to adapt your strategy? Learn more about our AI consulting services, or get in touch today.