AI agents compete for the $30 trillion consumer market! Damo: Meta (META.US), Apple (AAPL.US), Amazon (AMZN.US), etc. are expected to benefit Google (GOOGL.US) faces the test of its business model

The Zhitong Finance App learned that Morgan Stanley released the latest research report saying that with the launch of the Muse smart device by Meta Platforms (META.US) and AI agents such as Instinct quickly garnering market attention, “smart AI” is evolving from a simple information question-and-answer tool to a “mobile assistant” that can search, compare, make decisions, and even complete transactions for users. Morgan Stanley estimates that in the future, the global consumer spending scale that can be digitized through smart products will reach about 30 trillion US dollars, covering various fields such as e-commerce, travel, advertising, takeout, and online car-hailing. The potential market size is roughly comparable to the market opportunities of generative AI in the field of enterprise knowledge work.

Morgan Stanley believes that this wave of smart devices may not only create new traffic entrances and transaction channels, but also redistribute profit pools formed over a long period of time in the Internet industry. Platforms with huge user distribution channels, unique data, and software and hardware ecosystems are in a relatively favorable position. Among them, Meta, Apple (AAPL.US), and Google (GOOGL.US) have obvious basic advantages; among downstream enterprises, companies such as Amazon (AMZN.US), eBay (EBAY.US), and Shopify (SHOP.US) are relatively prominent in the intelligent era. At the same time, the potential impact on industries with a high degree of standardization, such as online car-hailing, where consumers value price more is worth paying more attention to.

Notably, Morgan Stanley is still optimistic about the overall prospects of the North American internet industry, and lists Meta, Apple, Amazon, eBay, and Shopify as a group of companies that it believes are better positioned in the wave of smart devices.

Meta Muse becomes a new variable that will contribute about 1% per 100 million users to EPS in 2028

This research report focuses in particular on Meta's latest Muse. Morgan Stanley believes that Muse is an important development in the smart device market: it has been in the top 5 app download lists for 9 consecutive days since launch, can also use Facebook, Instagram and other Meta data resources to provide personalized interaction, and has incorporated mobile web browsing and operation capabilities into usage scenarios, and can perform some transaction tasks directly through a browser. At the same time, Muse has a high free usage quota — providing 100 million free tokens every week. Morgan Stanley estimates that this amount may be enough to support users to make more than 100 queries per day.

Compared to simply relying on subscription fees, Morgan Stanley believes that Muse's real noteworthy commercial opportunities may come from user behavior and transactions themselves. Currently, Muse can charge through a subscription model, but the bank anticipates that Meta may eventually charge commissions for transactions facilitated by Muse.

Morgan Stanley also quantified this business model. Assuming that Muse has 100 million users by 2028, and each user initiates 5 queries per day, of which 10% are commercializable queries, and Meta achieves revenue of about $0.07 billion per commercial query, then Muse can contribute about 1.3 billion US dollars in revenue to Meta and an incremental revenue of about $0.35 per share in a year, which is equivalent to an increase of about 1% to EPS in 2028.

And this model has quite a large-scale effect. Morgan Stanley's sensitivity analysis shows that if the size of Muse users and the number of commercial queries generated by each user increases further, its transaction-related revenue may reach more than $8 billion; under a more positive scenario, Muse may even bring more than 15% incremental space to Meta's 2028 EPS. However, this result is highly dependent on assumptions such as user size, frequency of commercial inquiries, and monetization efficiency, and is not the bank's benchmark forecast.

The key to intelligent competition is not only the ability to distribute models and exclusive data as core bargaining chips

Morgan Stanley believes that the two important factors that determine the final competitive landscape of horizontal AI agents are large-scale distribution capabilities and large-scale unique data sets.

This is why Meta, Google, and Apple are considered by the bank to have a good foundation. Apple and Google respectively master the iOS and Android ecosystems, and their deep integration of software and hardware makes it easier for the two companies to deploy smart applications and functions across the entire device ecosystem; Meta's differentiating advantage comes from a large amount of first-party data accumulated by platforms such as Facebook and Instagram, which helps the intelligence system understand user preferences and provide more personalized services.

However, technical ability alone is not enough to guarantee victory in the end. Morgan Stanley pointed out that promoting the popularization of smart devices also essentially involves changes in consumer behavior habits, so product promotion, user education, and the ability to clearly demonstrate actual use value are also important. Muse has been out for less than 10 days, but initial user performance has already given off some positive signals.

The e-commerce landscape or reshuffling Amazon, eBay, and Shopify positions are relatively beneficial

After smart agents gradually intervene in shopping decisions and transactions, e-commerce platforms may become one of the most directly affected areas.

Morgan Stanley believes that among the e-commerce companies it covers, Amazon and eBay are relatively well positioned in the smart era, while companies such as Peloton (PTON.US), Chewy (CHWY.US), and FIGS (FIGS.US) face relatively higher potential risks.

Shopify plays a different role. Morgan Stanley believes that Shopify is not just a shopping platform directly facing consumers; its more important value lies in providing infrastructure for a large number of scattered merchants. As a result, when merchants need to adjust product information, transaction processes, and technical architectures to suit an intelligent-led shopping environment, Shopify may become an important “infrastructure provider” to help these merchants complete their transformation.

In other words, as consumers increasingly let AI “find products, compare prices, and place orders” for themselves, the focus of e-commerce industry competition may gradually expand from “who has the best websites and apps” to “who can be most easily discovered, understood, and completed by AI agents”.

Travel platforms are not the most vulnerable and unique real-time inventory poses an important barrier

Recently, market concerns about smart devices disrupting online travel platforms (OTAs) have clearly heated up. The report points out that as related concerns rekindled, the stock prices of some online travel companies in the “smart competition battleground” fell by a cumulative total of about 6%-12% in the previous two weeks.

However, Morgan Stanley believes that the market may have underestimated an important asset in the hands of Booking Holdings (BKNG.US), Airbnb (ABNB.US), and Expedia (EXPE.US), which is unique, scattered, large-scale, and ever-changing real-time inventory.

Travel products such as hotel rooms, homestays, and flights are not as easy to be completely replaced by AI as standardized products. Travel spending usually requires extensive image browsing, destination exploration, itinerary planning, and product discovery, so consumers aren't necessarily willing to completely skip OTA platforms. Morgan Stanley believes that “exploration, planning, and product discovery” itself may constitute a competitive barrier in the travel industry.

However, OTAs still need to pay attention to two key indicators: one is whether direct traffic is diverted by AI agents; the other is whether these platforms can launch their own smart products to keep users and transactions within their own platforms. These two points are likely to affect its long-term valuation level.

Online car-hailing faces a more direct impact AI may further push competition to “price comparison”

Compared to travel and takeout, Morgan Stanley believes that the online car-hailing industry faces a higher risk of intelligent disruption.

The reason is that online car-hailing services are more standardized. For a consumer who just wants to travel from the office to the airport, the choice between Uber (UBER.US) and Lyft (LYFT.US) may depend mainly on price and wait times. The agent can search multiple platforms at the same time and then automatically select the lowest or fastest service.

In contrast, ordering takeout and travel products usually involves more image browsing, exploration, and personal preferences, so it is more valuable for consumers to actively participate in decision-making. As a result, Morgan Stanley believes that the more standardized, the smaller the customer unit price, and the more transactions that rely on price to make decisions, the more susceptible they are to be influenced by horizontal AI agents.

That doesn't mean Uber, Lyft, or DoorDash (DASH.US) will lose value, though. Morgan Stanley points out that large-scale drivers, delivery agents, and local delivery networks themselves are physical infrastructure that is difficult for smart bodies to replicate on their own. Even if future consumers request cars and order meals through Meta or other AI smart devices, horizontal smart devices may still need to connect to the Uber, Lyft, and DoorDash networks to actually complete the service.

As a result, the real question may shift from “whether consumers continue to open the Uber app” to “how much economic value can Uber retain from a single order when AI becomes an entryway”.

Google is facing a deeper test, and the smart commission model may reduce the monetization rate of traditional searches

Morgan Stanley believes that one potential influencer of particular interest in the smart age is Google's current business model.

As large platforms such as Meta continue to launch smart products, if these products successfully attract a large number of users and take commercially valuable queries and transactions from Google's search engine, Google may have to actively adjust the current highly mature search advertising monetization system.

The biggest difference is the “draw rate.”

Morgan Stanley estimates that the current “effective margin rate” for each transaction in traditional search ads — that is, the ratio of advertising spend to total commodity transaction value (GMV) — is about 5 to 10 times the commission model for some smart transactions earlier this year. This means that if consumers increasingly complete purchases directly through AI agents instead of clicking on traditional search ads to enter merchant websites, Google may face the risk of a decline in the level of monetization in a single transaction.

Therefore, the bank believes that Google must continue to speed up the implementation of next-generation smart products and use its huge search user base and data advantages to maintain an upstream position in the smart device transaction funnel.

But Google isn't without buffer space. Currently, over 80% of retailers' online traffic is still free or direct. With the popularity of AI agents, if some of the original free direct traffic is converted into agent traffic that requires commission payment, even if the profit rate for a single transaction falls, the additional paid transaction volume may partially offset the impact.

Morgan Stanley estimates that if about 5 percentage points of free/direct traffic is transferred to paid channels, it can offset a 14 percentage point drop in the effective margin rate; however, if the final rate of the smart entity is only 5%, Google needs about 38 percentage points of traffic to switch from free channels to paid channels to fully achieve balance of payments.

This also means that potential conflicts of interest in the smart era will become more and more obvious. Large platforms such as Google want to turn more direct traffic that was originally free into fee-based smart transactions, while retailers need to protect direct traffic with higher profit margins.