Sunday, December 21, 2025

Morgan Stanley maps the retail winners and losers from agentic shoppers

Investing.com — Morgan Stanley told investors in a note on Wednesday that it believes “agentic commerce will be a paradigm shift for e-Commerce,” reshaping how consumers discover, compare, and buy products, with meaningful implications for retailers and digital advertising platforms.

Analysts, led by Brian Nowak, stated that agentic shopping, effectively a “personal digital interactive shopper,” is the “next substantial GenAI-enabled unlock,” potentially adding “~$50bn to ~$115bn to US e-commerce spend by ’30.”

Early agentic offerings are already emerging from platforms such as Alphabet and OpenAI, as well as retailers including Amazon and Walmart.

Morgan Stanley expects the e-commerce funnel to become “more conversational, personalized, interactive,” with agents handling tasks such as real-time price comparison, item pairing and automated repeat purchases.

Using its “5 I’s” framework (Inventory, Infrastructure, Innovation, Incrementality and Income Statement), Morgan Stanley assesses which retailers are best positioned.

The framework is said to highlight risks from third-party agents potentially displacing high-margin direct traffic.

On that basis, Morgan Stanley believes Amazon, Walmart and eBay “screen favorably,” while Five Below and Etsy “screen less favorably.”

The firm warns that profitability will hinge on incrementality. Its analysis shows retailers would need “~50% of agentic transactions to be incremental for EBIT breakeven (at a 5% fee),” which Morgan Stanley calls “a tall order.”

Through this lens, Amazon, Walmart, Target and eBay face higher margin risk from third-party agentic partnerships, while Chewy and Wayfair may have more opportunity, Morgan Stanley wrote.

In digital advertising, Morgan Stanley expects “leading performance-based reach platforms” to become more valuable, naming Meta, YouTube and AppLovin as potential winners as agentic shopping changes traffic patterns and monetization models.

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