"E-commerce Agent"—AI applications with enormous commercial potential are beginning to "emerge."

The narrative logic of AI is undergoing a dramatic shift from pure “conversation” towards “action”—namely, emptying the user’s wallet. From Alibaba’s launch of the “Qianwen App” to OpenAI’s shopping search, tech giants are vying for the next era’s traffic gateway through “e-commerce Agents” (AI as agent).

According to ChaseWind Trading Desk, on November 23, Morgan Stanley analyst Brian Nowak and his team released a new report stating that we are on the eve of a business revolution. Agent-style e-commerce is expected to reach $385 billion in GMV by 2030, accounting for about 20% of total US e-commerce. Current data shows that general large-model platforms (like ChatGPT) have far surpassed retailers’ self-developed AIs in shopping penetration, and users are not just “chatting,” but also “buying”—about 30–40% of AI users have completed purchases based on platform recommendations.

For investors, this trend directly benefits tech giants with a massive user base and AI infrastructure, giving Google, Amazon, and Meta powerful new support for their long-term growth logic.

Giants Enter the Arena: The Battle for the “Super Gateway” from Alibaba to OpenAI

Frequent moves at the news level confirm the acceleration of AI To C commercialization.

Alibaba’s “AI Super Gateway” ambition: Recently, Alibaba fully revamped “Tongyi” and renamed it as the “Qianwen App,” aiming to create China’s ChatGPT. The app is equipped with the Qwen3-Max model, claimed to outperform GPT-5. Unlike previous B-end focus, this time Alibaba seeks to build the go-to gateway for C-end consumers through a powerful, free, and connected model, covering shopping, office, and other scenarios. Alibaba is attempting to integrate its traditional e-commerce strengths by connecting its huge Agent ecosystem (like Taobao, Gaode) to the model, achieving a leap from “conversation” to “action.”

OpenAI enters shopping search: On the other side of the ocean, OpenAI released a shopping search function optimized with the GPT-5-Thinking-mini model. The system can precisely recommend 10–15 products via Q&A format. Although there’s no direct monetization yet, its intention is clear: to occupy a key position at the front-end of the consumer decision chain (the search phase), paving the way for future business models.

Market Space: The $385 Billion Blue Ocean of Agent E-Commerce

According to Morgan Stanley, this is not only a functional upgrade, but the beginning of the “Agent-style e-commerce” era.

GMV Forecast: Morgan Stanley predicts that by 2030, Agent-style e-commerce GMV will reach about $190 billion in the baseline scenario, and as much as $385 billion in the optimistic scenario.Penetration Rate: This means that by 2030, about 10% (baseline) to 20% (optimistic) of US e-commerce transactions will be driven primarily by Agent.Current Stage: Although still in the early (nascent) stage, “commercial activity” is already appearing on platforms. About 40–50% of users are using AI platforms for commerce-related activities, and conversion rates (purchasing behaviors) are starting to show.

Platform Competition: General Large Models vs. Retailers’ Vertical AI

The current winners are general platforms, not dedicated retail tools.

Adoption Rate Advantage: Data shows ChatGPT has a monthly adoption rate of 45%, Gemini at 32%, and Meta AI at 22%. By contrast, retailer-specific AI shopping assistants (like Amazon Rufus and Walmart Sparky) only have an adoption rate of about 10%. General platforms have followed the path of mobile app proliferation, expanding far faster in scale than single retailer apps.Youth Trend: Young people are the main driving force. In the group aged 34 and under, over 60% use ChatGPT, showing its cross-generational dominance. This is a key signal for Google: it must continue rolling out new products to stay competitive.

Behavioral Conversion: High Conversion Rates from Price Comparison to Purchase

Users aren’t just “playing” with AI; they are voting with real money.

Price comparison: 53% of ChatGPT users and 46% of Gemini users used the platform to research or compare product prices in the past month.Purchase Conversion: A stunning statistic—36% of ChatGPT users reported making purchases based on platform recommendations in the past month. Scaled to the US population, this means about 16% of Americans have already completed AI-driven purchases via ChatGPT.Leading Categories: Contrary to public intuition, the first turf conquered by Agents isn’t high-tech products, but high-frequency necessities. Grocery (49%) and household daily goods/CPG (41%) are the primary categories for AI shopping so far. Morgan Stanley believes groceries will be the biggest unlocked sector for Agent e-commerce in the next 5 years.

Investment Targets: Morgan Stanley’s Picked Winners (GOOGL, AMZN, META)

Based on the explosive potential of Agent e-commerce, Morgan Stanley remains bullish on tech giants, issuing 2027 target prices.

Alphabet (GOOGL):Rating: Overweight.Target Price: Baseline of $330.Logic: Search ads keep gaining share; AI-driven innovation (Search and YouTube) will bring meaningful engagement growth, and new AI products will not cannibalize the core search business.Amazon (AMZN):Rating: Overweight.Target Price: Baseline of $315.Logic: High-margin businesses (ads, AWS) allow continued investment alongside profitable growth. Cloud adoption is at an inflection point, and advertising will be key for growth and profitability.Meta Platforms (META):Rating: Overweight.Target Price: Baseline of $820.Logic: Meta has structurally shifted into its “year of efficiency.” AI investment is boosting Reels engagement and monetization, improving ad measurement. Additionally, click messaging and further AI-driven upsides are seen as undervalued “call options.”

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The above content is from ChaseWind Trading Desk.

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