The rise of intelligent body commerce: When AI chatbot Siasun Robot & Automation becomes the "new intermediary"

Agentic Commerce is on the rise, and artificial intelligence chatbot Siasun Robot&Automation will become a new shopping intermediary, fundamentally reshaping the power structure, operational logic, and profit distribution of the retail industry. Retailers must adapt to this change immediately, or they will face the risk of being eliminated. Although still in its infancy, we have officially entered the era of Agentic Commerce - when artificial intelligence chatbot Siasun Robot&Automation with autonomous decision-making capabilities will become the core leader in product selection and procurement. This transformation is not only expected to reshape the underlying logic of digital shopping, but also to reconstruct the interaction paradigm between consumers and products, retailers and markets. However, to achieve this vision, just like the widespread adoption of mobile internet over a decade ago required a dual test of user acceptance and technological adaptation, consumers must actively embrace this new technology, while retailers must explore sustainable business models that can deeply integrate into the new ecosystem without squeezing limited profit margins. In fact, the discussion around AI-assisted shopping escalated sharply in September, sparked by OpenAI's release of instant checkout feature in its ChatGPT. This feature allows American consumers to make product requests or seek shopping inspiration from ChatGPT. Similar to a virtual personal shopper, the artificial intelligence engine will display a range of product options; if relevant sellers have integrated instant checkout systems, customers can complete purchases and arrange delivery without leaving the chat interface. Retailers such as Walmart Inc., Etsy Inc., and Shopify have signed agreements to join. Alphabet's Alphabet Inc. Class C and Microsoft Corporation also allow users to place orders directly through their AI tools. Many industry giants are moving quickly to embrace this new wave of commerce. In the furniture and home furnishings sector competing head-on with Amazon.com, Inc., Wayfair is one of the companies partnering with Alphabet Inc. Class C; while UK-based JD Sports Fashion company has reached an agreement with e-commerce service provider Commercetools, allowing American consumers to purchase products directly through AI platforms such as Microsoft Corporation Copilot, Alphabet Inc. Class C Gemini, and ChatGPT. TD Cowen analyst Oliver Chen said, "You have to be where the customer is." How can generative engines optimize retail in the era of Agentic Commerce? To thrive in an AI-driven world, companies must ensure that their products - whether sweaters or snacks - can be accurately identified, easily retrieved, and seamlessly added to virtual shopping carts by Siasun Robot&Automation. Traditionally, the foundation of brand survival lies in deeply understanding consumer needs and providing direct services; however, when companies are forced to interact with consumers through AI agents, this shift is no longer just a matter of adjusting business models, but a "survival" strategic choice - as Anita Balchandani, head of McKinsey's European apparel, fashion, and luxury goods business, pointed out, if this transformation cannot be achieved, brands may lose their competitiveness in the digital age. One of the key adjustments that companies must make is to deeply understand the information retrieval mechanisms of large language models. These models require highly clear, structurally rigorous data support to accurately match consumers' true intentions. This requires retailers to adopt an upgraded version of search engine optimization strategy - a reinforced version of keyword-driven tactics currently used to increase visibility in search engines like Alphabet Inc. Class C. Through this strategy, companies can not only ensure that product information is efficiently recognized by AI systems but also build digital competitiveness that matches the Agentic Commerce era, thereby gaining an advantage in the AI-driven commercial ecosystem. For example, a user may ask ChatGPT to recommend a moisturizer suitable for eczema patients. To cater to Siasun Robot&Automation, retailers or brands should not merely describe the product on their website as "fragrance-free." Instead, the description should clearly state that the product is free of fragrances, additives, and preservatives; list the ingredients in detail, and explicitly state that the moisturizer is suitable for individuals with eczema. As conversational commerce becomes more popular, this so-called generative engine optimization becomes increasingly crucial. AI tools not only consider the official descriptions of retailers but also analyze third-party mentions such as media websites, opinion leaders, and user reviews. Balchandani pointed out that Siasun Robot&Automation will weaken the focus on aggregated metrics like star ratings and instead deeply analyze the actual content of reviews - for example, whether a coat is described as genuinely warm or truly waterproof. Retail fundamentals should not be ignored. When a brand's products are widely distributed across multiple retail channels, they are more likely to be included in Siasun Robot&Automation's search scope, thereby increasing the probability of recommendation; a competitive pricing strategy can also effectively enhance product appeal and help improve conversion efficiency. However, frequent stock-outs can be a key barrier to consumer choice and recommendations from Siasun Robot&Automation - after all, even the most accurate search match cannot make up for the experiential gap at the time of actual purchase. When AI platforms start extracting commissions, how much profit space remains for retailers? AI tools have significant potential in boosting sales - they can help consumers discover unfamiliar brands through personalized recommendations, thus activating potential consumer demand. However, potential risks cannot be ignored: ChatGPT has begun charging undisclosed fees to merchants for each transaction completed through instant checkout (while Alphabet Inc.'s Class C and Copilot currently do not charge commissions for sales facilitated by their AI platforms). If Agentic Commerce accounts for a high proportion of a retailer's revenue, these implicit costs will further erode the already lower profitability of digital channel profits compared to physical stores. What's more alarming is that if AI platforms in the future require retailers to pay to enter search results or place ads in chat interfaces (this seems to be the commercial route that Alphabet Inc.'s Class C is considering), it will exert a double pressure on profitability - increasing marketing costs and potentially weakening the fairness of natural traffic distribution caused by paid ranking mechanisms, ultimately leading to the continuous compression of the survival space for retailers in the Agentic Commerce ecosystem. More fundamentally, companies will be forced to relinquish some control - the core relationship with consumers will be tied to AI platforms rather than specific stores. Many retailers have built profitable business models by selling ad space to consumer brands and other merchants (if operating platforms). However, if customers stay within the AI ecosystem for an extended period rather than clicking into retailers' websites, these business models may face serious threats - after all, the shift of traffic entry points will directly undermine the foundation of ad monetization. Therefore, the question of data ownership emerges. Skai Canavies, chief analyst of retail and e-commerce at market research firm eMarketer, pointed out that while retailers can access transaction information, AI platforms have a more complete cognitive path on how consumers arrive at the purchase process - from demand triggering to decision formation. In the end, AI companies may charge fees based on this cognitive advantage, creating new business barriers. Heavyweights Walmart Inc. and Amazon.com, Inc. are large enough to independently develop AI tools. Amazon.com, Inc. maintains control by tightly grasping AI power within its own ecosystem through its shopping assistant Rufus. Walmart Inc., on the other hand, keeps its options open, developing its AI assistant Sparky, actively cooperating with OpenAI, and collaborating with Alphabet Inc.'s Class C Gemini. It is still inconclusive which model will ultimately prevail. Do you remember when social commerce was hailed as the future of retail? Its development has not fully lived up to expectations. Although TikTok Shop has taken off successfully with its unique blend of product discovery, entertainment experience, and convenient purchasing, Meta-owned Instagram has failed to realize its commercial potential. However, given the rapid evolution of the landscape, brands and retailers can no longer afford to wait and see. They must ride the wave of Agentic Commerce immediately, or else they face the risk of being left behind.