Agentic commerce could reshape a roughly $30 trillion consumer-spend opportunity, favoring scaled platforms and select enablers

Overview

This industry report lays out Morgan Stanley's framework for assessing how consumer-facing AI agents may change internet commerce, advertising, travel and gig-economy markets. It argues that the opportunity is large but unevenly distributed: platforms with scale, proprietary data, inventory and transaction infrastructure may benefit, while businesses with commoditized offerings or weak direct customer relationships may be more vulnerable.

Core views

Morgan Stanley estimates that roughly $30 trillion of consumer spending could be digitized through agentic offerings across advertising, e-commerce, travel, food delivery, rideshare, logistics and wearables. The report frames this as a meaningful commercial opportunity comparable in scale to the estimated GenAI enterprise knowledge-work total addressable market. Its central premise is that agents can increasingly move from answering questions to conducting personalized browsing, discovery and transactions. The report argues that scaled distribution and large proprietary data sets are the key advantages for horizontal agent platforms. Meta, Alphabet and Apple are viewed as well positioned: Apple and Google benefit from software-to-hardware integration across iOS and Android ecosystems, while Meta's advantage is personalization based on its first-party data. Morgan Stanley also stresses that adoption is not purely a technology problem; it depends on go-to-market execution, behavior change and demonstrating consumer utility. Meta Muse is presented as an important early development. Morgan Stanley cites nine consecutive days among the top-five downloaded apps, personalized interactions using Facebook, Instagram and other data, mobile web-browsing capabilities, and a free allowance of 100 million weekly tokens that could support more than 100 daily queries. The institution considers the current traction encouraging but early. It sees the larger monetization opportunity not primarily in subscriptions, although it notes possible $20-per-month and $100-per-month subscription tiers, but in monetizable commercial behavior and transaction commissions. Morgan Stanley's illustrative Muse model assumes 100 million users, five queries per user per day, a 10% commercial-query rate, and $0.07 monetization per commercial query—20% of Google's stated $0.36 U.S. monetization per commercial query. Under those assumptions, Muse could produce about $1.3 billion of global revenue, more than $1 billion annually, and approximately $0.35 of 2028 EPS upside for Meta, or 1%. The exhibit assumes an 80% incremental margin on new Muse-based revenue. Its sensitivity analysis indicates paths to more than $8 billion of transactional revenue and more than 15% upside to 2028 EPS at higher user and commercial-query volumes, while holding the commercial-query rate and monetization per query at 10% and $0.07, respectively. The report identifies continued go-to-market strength, transaction partnerships that reduce friction and true incremental demand as key conditions. For downstream businesses, Morgan Stanley applies its "5 I's" framework—inventory, infrastructure, innovation, incrementality and income statement—to assess agentic defensibility and incremental-revenue potential. Amazon and eBay are seen as among the better-positioned e-commerce participants, while Peloton, Chewy and FIGS are among those at greatest risk. Shopify is viewed as a strong enabler because it can help a fragmented supplier base adapt and optimize for agentic commerce. In travel, Booking, Airbnb and Expedia possess differentiated real-time, fragmented and scaled inventory, but their long-term valuation outcomes depend on maintaining direct traffic and capturing users and transactions through their own agentic products. Gig-economy agents will still require the courier and delivery infrastructure of Uber, Lyft and DoorDash. The report distinguishes industries by how much visual browsing, exploration, product discovery and time between search and booking they require. Morgan Stanley considers rideshare more exposed than food delivery or travel because it is more commodity-like and price sensitive. Food delivery retains risks, particularly for repeat orders, but travel may be more defensible because planning, exploration and discovery are valuable parts of the consumer experience. Morgan Stanley sets out three strategic scenarios for online travel and shared-economy companies. Under "Hold Rank," companies restrict structured agent access and build domain-specific agents; this is neutral near term but potentially positive longer term if they retain top-of-funnel and customer control. Under "Status Quo," agents can browse and book through browsers and existing application hooks without a commercial agreement; the near-term effect may be slightly positive from incremental transactions, but the longer-term risk is that agents capture the funnel and later charge commissions. Under "Partner With Agents," formal distribution, fee or revenue-share agreements can generate positive near-term volume at established unit economics, but could create permanently rising traffic costs as agents gain top-of-funnel power. For Google, Morgan Stanley argues that next-generation agentic products must be deployed across its Search user base to reduce the risk of other platforms capturing commercial behavior. The report estimates that current search effective take rates—advertising spending as a percentage of GMV—are roughly five to ten times higher than early agentic commission offerings. This makes loss of search traffic a monetization risk even if agentic commerce expands. More than 80% of retailer online traffic remains unpaid or direct, according to the report; a 500-basis-point shift from unpaid to paid traffic could offset a 1,400-basis-point decline in effective take rates. However, a 3,800-basis-point shift would be required for Google to break even at a 5% take rate. Morgan Stanley therefore argues that retailers need to preserve profitable direct traffic and focus on incrementality and transaction economics as platform incentives to monetize agentic channels increase.

Analysis framework

Morgan Stanley first sizes the agentic consumer-spending opportunity, then evaluates horizontal platforms through distribution, data and ecosystem advantages. It models Meta Muse using user adoption, query frequency, commercial-query conversion, monetization per query and incremental margins, and uses sensitivity tables to show alternative revenue and EPS outcomes. For downstream companies, it applies a five-factor assessment of inventory, infrastructure, innovation, incrementality and income-statement effects, followed by partnership scenarios for travel and shared-economy platforms and traffic/take-rate sensitivities for search.

Methodology notes

• Industry AnalysisSupply-demand framework

  Agentic-commerce market sizing and platform positioning

  The report estimates the consumer-spend pool that could move into agentic channels and assesses which platforms have the distribution, data and transaction capabilities to capture that demand.

• Competition & strategyValue chain analysis

  The "5 I's" framework

  Morgan Stanley evaluates downstream businesses through inventory, infrastructure, innovation, incrementality and income-statement impact to judge their defensibility and ability to benefit from agentic platforms.

• Other

  Meta Muse adoption and monetization sensitivity analysis

  The report varies users and commercial queries per user while holding selected monetization assumptions constant to show possible revenue and EPS outcomes for Meta.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Meta Platforms (META)

  Potential beneficiary from Muse adoption, monetizable behavior and transaction commissions.

  Strengths

  First-party data, personalization, early Muse traction and large distribution.

  Weaknesses

  Commercial-query rates, commission rates and incrementality remain uncertain.

  Comparison

  Morgan Stanley compares its illustrative monetization per commercial query with Google's U.S. search monetization.

  Risks

  Adoption, partnership execution and monetization may not reach modeled levels.

• Alphabet (GOOGL)

  A leading platform that faces transition and monetization risk if agentic competitors capture commercial traffic.

  Strengths

  Search scale, data and Android ecosystem integration.

  Weaknesses

  Current effective Search take rates are materially above early agentic commission rates.

  Comparison

  Its search monetization is used as an analogue for agentic commissions.

  Risks

  Traffic loss and lower take rates could pressure search monetization unless paid-channel conversion offsets the decline.

• Amazon (AMZN) and eBay (EBAY)

  Identified as among the better-positioned e-commerce participants.

  Strengths

  Morgan Stanley's framework indicates relatively strong agentic positioning.

  Comparison

  Screen more favorably than Peloton, Chewy and FIGS in the report's e-commerce assessment.

• Shopify (SHOP)

  An enabler positioned to help a fragmented supplier base adapt to agentic commerce.

  Strengths

  Can support supplier adjustment and optimization for agentic channels.

  Comparison

  Distinctly positioned as infrastructure and enablement rather than a downstream retailer.

• Booking Holdings (BKNG), Airbnb (ABNB) and Expedia (EXPE)

  Travel platforms with differentiated inventory but exposure to changes in agent-driven discovery and distribution.

  Strengths

  Unique, fragmented, scaled and growing real-time inventory.

  Weaknesses

  Long-term multiples depend on maintaining direct traffic and proprietary agentic engagement.

  Comparison

  Travel is viewed as more defensible than rideshare because discovery and exploration matter more.

  Risks

  Agent-controlled top-of-funnel traffic could lead to commissions and greater price competition.

• Uber (UBER), Lyft (LYFT) and DoorDash (DASH)

  Critical infrastructure providers for agentic rideshare and delivery services.

  Strengths

  Scaled courier and delivery networks.

  Weaknesses

  Rideshare is characterized as more commodity-like and price sensitive.

  Comparison

  Rideshare is viewed as more exposed than food delivery or travel.

  Risks

  Horizontal agents could reshape customer access and transaction economics.

Key data

• Agentic consumer-spend addressable market~$30 trillionEstimated consumer spend that could be digitized through agentic offerings.
• Muse app adoption signal9 straight days in the top 5 downloaded appsEarly adoption evidence cited by Morgan Stanley.
• Muse free usage allowance100 million free weekly tokensMorgan Stanley says this could likely support more than 100 queries per day.
• Illustrative Muse user base100 million usersModel assumption for the base-case revenue and EPS illustration.
• Illustrative Muse annual revenue$1.3 billionBased on five daily queries per user, a 10% commercial-query rate and $0.07 monetization per commercial query.
• Illustrative Meta 2028 EPS upside$0.35 or 1%Morgan Stanley's base-case Muse contribution estimate.
• Muse transactional revenue sensitivity$8 billion+Potential outcome in Morgan Stanley's higher-scale sensitivity analysis.
• Search versus early agentic take rates~5-10x higherMorgan Stanley estimates current effective search take rates exceed early agentic commission offerings.
• Retailer unpaid/direct online traffic80%+A 500-basis-point shift toward paid traffic could offset a 1,400-basis-point decline in effective take rates.

Impact & implications

Morgan Stanley believes agentic commerce could shift consumer discovery and transaction economics toward platforms that combine distribution, data and execution. The report sees selected platforms and commerce enablers as potential beneficiaries, but warns that downstream businesses may face rising customer-acquisition costs, weaker direct relationships and pressure on transaction economics if horizontal agents control more of the funnel.

Risks

• Meta Muse adoption, commercial-query rates, monetization and transaction partnerships may not achieve Morgan Stanley's modeled assumptions.
• Downstream platforms could lose top-of-funnel control and face rising commission or traffic costs as horizontal agents scale.
• Google could face search-monetization pressure if agentic channels capture traffic at lower effective take rates.
• Commodity-like categories, particularly rideshare, may be more exposed to price-driven agentic disruption.

What to watch

• Muse adoption, utility, transactional behavior and its ability to reduce browser friction through partnerships.
• Whether Meta can demonstrate incremental, monetizable commercial activity rather than merely shifting existing behavior.
• How online travel and gig-economy companies respond through proprietary agents, access restrictions or formal partnerships.
• Whether Google launches next-generation agentic products across its Search user base.
• Changes in retailer direct/unpaid traffic, paid-channel mix and effective search take rates.