"E-commerce Agent" - The AI application with enormous commercialization potential is "emerging"

The narrative logic of AI is undergoing a dramatic shift from simple "conversation" to "action"—that is, emptying users' wallets. From Alibaba's launch of the "Qianwen APP" to OpenAI's shopping search, tech giants are competing for the next era's traffic entry point through "e-commerce Agents" (agent-style AI).

According to the Chasing Wind Trading Desk, on November 23, Morgan Stanley analyst Brian Nowak and his team released a research report stating that we are on the eve of a commercial transformation. Agent-style e-commerce is expected to reach a GMV scale of $385 billion by 2030, accounting for about 20% of the total U.S. e-commerce market. Current data shows that general large model platforms (such as ChatGPT) far exceed the shopping penetration rate of retailers' self-developed AI, 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 large user base and AI infrastructure, providing new strong support for the long-term growth logic of Google, Amazon, and Meta.

Giants Enter the Arena: The "Super Entry Point" Battle from Alibaba to OpenAI

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

Alibaba's ambition for an "AI Super Entry Point": Recently, Alibaba has fully revamped "Tongyi" and renamed it "Qianwen APP," aiming to create China's ChatGPT. The application is equipped with the Qwen3-Max model, which claims to outperform GPT-5. Unlike previous versions that leaned towards B-end, this time Alibaba aims to cover shopping, office, and other scenarios through a powerful model that is free and connected, making it the preferred entry point for C-end consumers. Alibaba is attempting to integrate its traditional e-commerce strengths to connect its vast Agent ecosystem (such as Taobao and Amap) to the model, achieving a leap from "conversation" to "action."

OpenAI's entry into shopping search: Across the ocean, OpenAI has launched a shopping search function optimized based on the GPT-5-Thinking-mini model. Through a Q&A format, the system can accurately recommend 10-15 products. Although it is not currently monetized directly, its intention is clear: to occupy a key position at the front end of the consumer decision chain (search phase), paving the way for future business models.

Market Space: A $385 Billion Blue Ocean for Agent E-commerce

Morgan Stanley believes that this is not just an update of product functions, but the beginning of the "Agent-style e-commerce" era.

• GMV Forecast: Morgan Stanley predicts that by 2030, the GMV of Agent-style e-commerce will reach approximately $190 billion under baseline conditions and as high as $385 billion under optimistic conditions.
• Penetration Rate: This means that by 2030, about 10% (baseline) to 20% (optimistic) of U.S. e-commerce transaction volume will be driven primarily by Agents.
• Current Stage: Although we are still in the early (nascent) stage, "commercial behavior" has already emerged on the platform. About 40-50% of users are using AI platforms for business-related activities, and conversion rates (purchase behavior) are beginning to appear

Platform Battle: General Large Models vs Retail Vertical AI

The current winner is the general platform, not the dedicated tools of retailers.

• Adoption Rate Dominance: Data shows that ChatGPT's monthly adoption rate is as high as 45%, Gemini at 32%, and Meta AI at 22%. In contrast, the adoption rate of retailer-specific AI shopping assistants (such as Amazon Rufus and Walmart Sparky) is only around 10%. The general platform has adopted a similar path to the proliferation of mobile apps in the past, with a scale expansion speed far exceeding that of single retailer applications.
• Youth Trend: The younger demographic is the main force in adoption. Among those aged 34 and below, over 60% use ChatGPT, demonstrating its cross-generational dominance. This is a key signal for Google: it must continuously launch new products to maintain competitiveness.

Behavioral Conversion: High Conversion Rate from Price Comparison to Purchase

Users are not just "playing" with AI; they are voting with real money.

• Price Comparison Behavior: 53% of ChatGPT users and 46% of Gemini users have used the platform to research or compare product prices in the past month.
• Purchase Conversion: This is an astonishing statistic—36% of ChatGPT users reported making purchases based on platform recommendations in the past month. This translates to approximately 16% of the U.S. population having completed AI-driven shopping through ChatGPT.
• Leading Categories: Contrary to public intuition, the first categories to be captured by Agents are not high-tech products but rather high-frequency necessities. Groceries (49%) and household goods/CPG (41%) are currently the main categories for AI shopping. Morgan Stanley believes that groceries will be the largest unlocking area for Agent e-commerce in the next five years.

Investment Targets: Winners in Morgan Stanley's Eyes (GOOGL, AMZN, META)

Based on the explosive potential of Agent e-commerce, Morgan Stanley maintains a positive outlook on tech giants and has provided target prices based on 2027 expectations.

• Alphabet (GOOGL):
  • Rating: Overweight.
  • Target Price: Base case $330.
  • Logic: Search advertising continues to gain share, AI-driven innovations (such as Search and YouTube) will bring meaningful engagement increases, and new AI products will not cannibalize core search business.
• Amazon (AMZN):
  • Rating: Overweight.
  • Target Price: Base case $315.
  • Logic: High-margin businesses (advertising, AWS) allow it to maintain profit growth while investing. Cloud adoption is at a turning point, and the advertising business will be key to growth and profitability.
• Meta Platforms (META):
  • Rating: Overweight.
  • Target Price: Base case $820.
  • Logic: Meta has structurally shifted to an "efficiency year." AI investments have driven engagement and monetization capabilities for Reels, and improved ad measurement. Additionally, the click-through message and further upside potential driven by AI are seen as undervalued "call options."