The robots are shopping, and they're picky! Here's how to prepare for AI shopping agents.
Predicting the future of retail usually involves a crystal ball and a fair amount of optimism. Predicting the present, however, should be much easier. Yet many brands still seem surprised that robots have already started shopping.
Agentic commerce isn't a vague concept on a roadmap for 2030. It’s happening right now. Consumers are increasingly handing over the reins to AI shopping agents, retail media networks, and social platforms to do the heavy lifting of discovery and decision-making. For enterprise brands, it’s no longer about spotting a trend. It is about survival.
The invisible shelf
The mechanics of how people buy are changing fundamentally. Retail media spend is skyrocketing, TikTok Shop is scaling up, and AI assistants are becoming the primary gatekeepers of what consumers see. These algorithms have a voracious appetite for data, but they are incredibly fussy eaters. They prioritise product information that is structured, enriched, and fully compliant.
If your data feeds are messy or incomplete, you’re not just missing an opportunity. You’re effectively invisible. At Inviqa, we frequently encounter a distinct paradox in modern retail: brands investing millions in a Savile Row-quality visual identity whilst relying on back-end product data that resembles a charity shop bargain bin.
It is a costly juxtaposition: you cannot sell premium products to an AI agent using discount-bin data.
AI agents don’t see products the way we do; the data is the shopfront. So when Gen Z uses AI for product research 11x more often than Boomers, and one in four Millennials turn to AI platforms over other channels for shopping advice, the trend indicates that data quality will be the great differentiator for successful brands.
The cost of ignoring the maths
The industry numbers paint a stark picture. Gartner suggests that by 2026, 40% of commerce
transactions will involve AI-driven agents. Forrester anticipates retail media ad spend will hit $300 billion globally by 2030. Meanwhile, Accenture reports that social commerce is on track to account for $1.2 trillion in global sales.
Brands standing still are effectively moving backwards. We have seen the difference firsthand. When REISS optimised their product information and user experience, they unlocked double-digit growth. N Brown’s focus on improving product data across its brands and commerce channels significantly improved CX, conversion and sell-through rates.
Conversely, data errors suppress listings, overselling triggers cancellations, and compliance breaches risk fines under the DMCC (Digital Markets, Competition and Consumers Act 2024) and ASA (Advertising Standards Authority). It is an operational headache that quickly becomes a reputational nightmare.
Building the backbone with BigCommerce
The brands winning right now are the ones treating machine readability with the same reverence as human-centred design. They understand that you need to satisfy the algorithm to get in front of the human. This is why our partnership with BigCommerce is the saving grace for brands needing to scale rapidly without the wheels coming off their compliance strategy.
BigCommerce provides the composable backbone, offering multi-storefront agility and advanced catalogue management, while we layer on the necessary governance and design to ensure every product feed is clean, compliant, and ready for conversion.
Crucially, the feed management and optimisation layer is powered by Feedonomics. It acts as the central nervous system for your product data, automatically cleaning, categorising, and optimising your feeds for hundreds of global channels. Instead of manually fighting fires, like mismatched currency codes or missing attributes, Feedonomics proactively resolves errors before they ever reach the platform. It ensures that when your product appears on TikTok Shop, Google Shopping, or a retail media network, it is accurate, compliant, and ready to convert. The formula is straightforward but difficult to execute without the right tools: technical precision matched with excellent experience design.
Notably, both Feedonomics and BigCommerce are empowering merchants with current and future agentic commerce capabilities. This includes instant checkout on LLMs, catalogue syndication to AI answer engines, AI data enrichment, and support for Stripe’s Agentic Commerce Suite — a way for merchants to make products discoverable and purchasable by AI agents, without building multiple integrations.
Sort your shop floor today
Waiting until the middle of 2026 to address this is a strategy for second place. Speed is the defining factor of this market.
To get ahead, you need to audit your data and product feeds today. If the data isn't right, nothing else matters. Next, prioritise retail media readiness and embed compliance directly into your UX - Agentic commerce requires trust as much as it requires technology.
We’re ready to help you lead that transformation. After all, it’s best to be prepared before the AI agents take over completely. We’d hate for you to be the one explaining to a robot why your SKU data doesn't match your inventory.
Keen to avoid a tricky conversation with AI? Chat to us today.
