The rise of Agentic Commerce is underway, with artificial intelligence chatbots set to become new shopping intermediaries. This development is poised to fundamentally reshape the power structure, operational logic, and profit distribution within the retail industry. Retailers must immediately adapt to this transformation or risk being left behind.
Although still in its early stages, we have officially entered the era of Agentic Commerce—a time when AI chatbots with autonomous decision-making capabilities will become the primary agents for product selection and purchasing. This shift is expected to not only reshape the underlying logic of digital shopping but also redefine the interaction patterns between consumers and products, as well as between retailers and the market.
However, realizing this vision requires overcoming challenges similar to those faced during the adoption of mobile internet over a decade ago. Consumers need to actively embrace the new technology, while retailers must explore sustainable business models that deeply integrate into this new ecosystem without excessively squeezing already limited profit margins.
Discussions around AI-assisted shopping gained significant momentum in September, primarily driven by OpenAI's introduction of an instant checkout feature within ChatGPT. This feature allows US consumers to ask ChatGPT for product recommendations or shopping inspiration. Functioning like a virtual personal shopper, the AI engine presents a range of product options; if the relevant seller has integrated the instant checkout system, customers can complete their purchase and arrange delivery without leaving the chat interface.
Major retailers such as Walmart (WMT.US), Etsy Inc (ETSY.US), and Shopify (SHOP.US) have already signed on to participate. Alphabet's Google (GOOGL.US) and Microsoft (MSFT.US) also allow users to place orders directly within their respective AI tools. Many industry giants are moving quickly to embrace this new commercial wave.
Wayfair (W.US), which competes directly with Amazon.com (AMZN.US) in the furniture and home goods sector, is one of the companies partnering with Google. In the UK, JD Sports Fashion has reached an agreement with e-commerce services provider Commercetools, enabling US consumers to purchase goods directly through AI platforms like Microsoft Copilot, Google Gemini, and ChatGPT.
As TD Cowen analyst Oliver Chen stated, "You have to be where the customer is." For businesses to thrive in an AI-driven world, they must ensure their products—whether sweaters or snacks—can be accurately identified, easily retrieved, and seamlessly added to a virtual shopping cart by AI agents.
Traditionally, a brand's survival has been rooted in deeply understanding consumer needs and providing services directly. However, as companies are increasingly compelled to interact with consumers through AI agents, this shift represents more than just a business model adjustment; it is a strategic imperative for survival. According to Anita Balchandani, Leader of McKinsey & Company's Apparel, Fashion & Luxury Group in Europe, failure to successfully navigate this transformation could cause brands to lose their competitiveness in the digital age.
One crucial adjustment for businesses is gaining a deep understanding of how large language models retrieve information. These models require highly clear, well-structured data to accurately match consumer intent. This necessitates that retailers adopt an upgraded version of search engine optimization strategies—an enhanced form of the keyword-driven tactics currently used to improve a website's visibility on search engines like Google.
For example, a user might ask ChatGPT to recommend a cream suitable for someone with eczema. To effectively cater to the AI, a retailer or brand should not merely describe the product as "fragrance-free" on its website. Instead, the description must explicitly state that the product contains no fragrances, additives, or preservatives; it should provide a detailed ingredient list and clearly indicate the cream's suitability for eczema sufferers. As conversational commerce becomes more widespread, this so-called generative engine optimization becomes increasingly critical.
AI tools consider not only the retailer's official descriptions but also synthesize information from third-party sources like media websites, influencers, and user reviews. Balchandani notes that AI agents will likely pay less attention to aggregate metrics like star ratings and instead deeply analyze the substance of reviews—for instance, whether a coat is described as genuinely warm or truly waterproof.
Fundamental retail principles remain important. When a brand's products are widely available across multiple retail channels, they are more likely to be included in an AI agent's search results, increasing the probability of being recommended. Competitive pricing strategies can also enhance product appeal and improve conversion rates. Conversely, frequent stockouts can become a significant barrier, hindering both consumer choice and AI recommendations, as even the most accurate search match cannot compensate for the inability to purchase.
While AI tools show significant potential for boosting sales—by helping consumers discover new brands through personalized recommendations and thereby activating latent demand—there are also potential risks. ChatGPT has already begun charging merchants undisclosed fees for each transaction completed via its instant checkout feature (whereas Google and Copilot currently do not take commissions on sales facilitated through their AI platforms). If agentic commerce comes to represent a substantial portion of a retailer's revenue, these hidden costs could further erode the already lower profit margins of digital channels compared to physical stores.
A more significant concern is the potential for AI platforms to require retailers to pay for placement in search results or for advertisements within chat interfaces—a monetization path Google appears to be considering. This could create a double squeeze on profitability: increasing marketing costs while potentially undermining the fairness of organic traffic distribution through paid ranking mechanisms, ultimately compressing retailers' viability within the agentic ecosystem.
At a more fundamental level, companies may be forced to cede some control, as the core relationship with the consumer becomes tied to the AI platform rather than a specific store. Many retailers have built lucrative business models by selling advertising space to consumer brands and other merchants (if they operate a platform). However, if customers remain within the AI ecosystem instead of clicking through to the retailer's website, these business models could be severely threatened, as the shift in traffic entry points directly undermines the foundation of advertising revenue.
This leads to the question of data ownership. As Sky Canaves, Principal Analyst for Retail and E-commerce at market research firm eMarketer, points out, while retailers can access transaction information, AI platforms possess a more complete understanding of the consumer's path to purchase—the entire data journey from need trigger to decision formation. Ultimately, AI companies might leverage this cognitive advantage to charge fees, creating new commercial barriers.
Industry giants like Walmart and Amazon.com are large enough to develop their own AI tools. Amazon.com maintains control over AI within its own ecosystem through its shopping assistant, Rufus. Walmart, meanwhile, is keeping its options open by developing its own AI assistant, Sparky, while also pursuing cooperation with OpenAI and collaborating with Google Gemini.
It remains uncertain which model will ultimately prevail. Recall when social commerce was hailed as the future of retail? Its development has not fully lived up to the initial promise. While TikTok Shop has taken off by uniquely blending product discovery, entertainment, and convenient purchasing, Meta's Instagram has struggled to unlock its full commercial potential.
However, given the rapid pace of change, brands and retailers can no longer afford a wait-and-see approach. They must immediately ride the wave of Agentic Commerce or face the risk of being left behind.
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