The agents are coming. This was the key contention of our most recent piece of thematic work, which argued that the practical application of artificial intelligence to shopping could revolutionise commerce. For those, like your author, who find shopping a chore, the potential embedded within agentic commerce is significant. However, revolutions rarely occur overnight. Many people may understandably be reluctant to hand over shopping decisions (and their financial details) to a piece of still-unproven software.
To see just how far advanced this revolution might be, I spent some time interacting with three different platforms that offer agentic propositions. The results varied markedly. In order to allow for a like-for-like comparison across platforms, I resorted (not without recognising the irony) to my trusty Copilot software tool for a prompt that would test a combination of product discovery, the understanding of constraints, the scope for the agent to ask clarifying questions and explain trade-offs, as well as its ability to demonstrate a degree of autonomous (or ‘agentic’) behaviour.
The following prompt was put to Amazon’s Rufus agent, Google’s Gemini and the Zalando Assistant: “I’m attending a business casual technology conference in London next month. I need a pair of smart trainers that will work with chinos and a blazer. Budget £200. UK size 9. Recommend three options, explain why each fits the occasion, compare them, and tell me which one offers the best balance of style, comfort and value.”
Rufus responded most quickly. It suggested three options (from different retailers) ranging in price from £30-£125. It provided a justification for each. In a nice upsell, it also offered to show me “matching chinos for conference” and “blazer options for under £200.” Had I wanted to purchase any of the pairs of trainers, Rufus was not able to perform this autonomously, but I could have done so with only a few additional clicks. Gemini spent slightly longer considering my request. It also returned three suggestions, albeit at a higher price point (£110-£190), but still within the specified budget. It offered me tips on sock and trouser hem styles, but nothing more. When I mentioned that I wanted to buy one of its three recommendations, Gemini told me either to go direct to the retailer’s website or to browse a price comparison site. There was no scope for direct purchase. Zalando’s experience was the most disappointing. Customers cannot use its Assistant without first creating an account, meaning an additional layer of friction. It struggled with the clauses in my question. When I asked for trainers given a £200 budget, the Assistant told me it had no trainers priced at £200.
Conclusion: agentic commerce is still very nascent. It is, of course, important to recognise that the propositions trialled serve very different purposes. Amazon (with Rufus now being folded into Alexa) is arguably closest to true agentic commerce, while Gemini operates more as a gateway. Zalando can be thought of just as a vertical specialist, retailing only items on its website. For agentic commerce to succeed, it’s important to build underlying infrastructure – not just the front-end platforms, but also the supporting payment protocols and logistics for product distribution. Shopping may never be the same again. For now, however, the agents remain more enthusiastic personal shoppers than fully fledged buying assistants.
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