More AI agents will soon be able to browse and purchase from Shopify listings, marking an expansion of the company’s agentic commerce ambitions. Shopify announced Tuesday it will let shoppers configure their AI agents to purchase products on their behalf, giving more agents access to over a billion listings in Shopify’s catalog. (The catalog consists of both items on and off Shopify storefronts.) In September, Shopify announced it was partnering with Meta to allow its Muse agent to browse and purchase items on a human’s behalf; now, shoppers can use any agent without a partnership integration. To set up the feature, customers connect an AI agent to their Shopify account and specify purchase preferences, such as price range, product type, and shipping destination. Once configured, the agent can autonomously search for and buy items, sending purchase confirmations directly to the shopper. This move is seen as a step towards fully automated e-commerce, where AI agents handle everything from product discovery to checkout, potentially reducing human intervention in online shopping. However, critics argue that while the integration is sleek, it may overlook the nuances of personalized shopping experiences, such as brand loyalty or seasonal trends, which AI agents might not yet fully grasp. Additionally, the reliance on a single platform—Shopify—means that agents are still limited to its curated listings, possibly missing out on broader market diversity. The article also hints at the scalability of AI agents, suggesting they could handle peak shopping seasons effortlessly, yet it doesn’t delve into how these agents manage inventory or deal with stockouts—key considerations for any e-commerce platform. Lastly, the partnership with Meta for the Muse agent is highlighted, but the article could have explored whether other AI models, like OpenAI’s GPT or Google’s Gemini, are also being integrated, providing a more comprehensive view of the AI landscape in Shopify. Overall, while Shopify’s expansion into AI-driven shopping is promising, the article could benefit from a deeper dive into the technology’s current limitations and future potential.