Executive Summary
AI is beginning to play a meaningful role in how consumers shop. Yet its influence has been difficult to capture through conventional purchase data. When consumers use AI to choose products but complete their purchases on e-commerce sites or in physical stores, AI's contribution often goes unrecognized. By looking beyond purchases executed through AI to include those in which AI meaningfully shapes purchase decisions, BCG estimates that Japan's agentic commerce market has already reached JPY 12.5 trillion in 2026, representing 18% of consumer spending across the 14 categories covered in this study. The market is projected to grow to JPY 15.6 trillion by 2030, with AI also taking on a greater role in executing purchases.
For companies, however, the strategic question goes beyond simply whether their products will be chosen by AI. What AI optimizes for depends on what consumers are trying to accomplish in a particular shopping occasion—their Shopper Mission. There is no single formula for winning in agentic commerce.
The Value of AI Delivers Depends on the Shopper Mission
This report examines Japan's agentic commerce landscape through two dimensions: Shopper Mission and AI involvement level. The analysis reveals a diverse set of players leveraging their distinct strengths to serve different shopping missions.
These differences in the value AI delivers are fundamentally reshaping competitive dynamics. In routine replenishment, consumers value convenience and reliability. Once an AI recommends a product, that recommendation can become the default choice, giving early movers a potential advantage.
When planning a home party, by contrast, consumers need AI to compare options and optimize a combination of products against their budget and other requirements. This makes products more susceptible to selection based on price and functionality. In shopping occasions centered on finding something that feels right or discovering an exciting new product, the dynamics are different. By understanding consumers' tastes, personal styles, and intended uses, AI can introduce unexpected and appealing choices. Here, a brand's distinctive identity and a product's originality can become decisive.
AI can thus create new connections between brands and consumers, helping brands communicate value beyond price and inspire greater willingness to pay. AI can be both an accelerator of price competition and an amplifier of brand value.
AI Adoption Is Advancing Faster in Categories with More Demanding Purchase Decisions
Agentic commerce penetration has already reached 31% in the Baby & Kids category and is projected to rise to 38% by 2030. Cosmetics, Books, Magazines & Manga, Furniture, Home Furnishings & Household Goods, Alcoholic Beverages, and Fashion & Apparel also show relatively high levels of penetration.
AI tends to gain traction earlier where purchase decisions are more demanding—whether because consumers need specialized knowledge, face an overwhelming range of choices, or would traditionally need to inspect products in person. These are the situations where AI's value becomes most tangible.
Younger Consumers Offer an Early View of the Future of Shopping
Consumers aged 18–29 account for just 17% of survey respondents yet generate 41% of agentic commerce spending. While older generations tend to turn to AI in shopping situations where they face unmet needs or particular challenges, younger consumers are beginning to use AI as a starting point across all eight Shopper Missions, including everyday categories such as food and beverages.
They may also move more quickly toward delegating product selection and purchase execution to AI, without necessarily progressing through the gradual stages of trust-building seen among older consumers.
What Should Companies Do?
For consumer goods companies, the priority is to understand how AI creates value—and how competitive advantage is built—across different Shopper Missions. This calls for allocating investments across three strategic imperatives: win the default position; distinguish products that compete on functionality and price; and secure presence in consumer touchpoints where a brand's story and attributes can resonate with consumers. Companies should also reassess their product portfolios through a Shopper Mission lens and explore new opportunities for cross-border sales through agentic commerce. For retailers and fashion companies, the opportunity lies in owning the AI-powered consumer touchpoints and turning consumer understanding and product recommendation capabilities into incremental store visits and basket size growth. AI is not necessarily a threat to physical stores. In cosmetics purchases involving AI under the Need Now mission, approximately 70% are completed in physical stores. By connecting AI and stores seamlessly, AI can become not only a powerful channel for driving traffic, but also a means of enhancing the in-store experience itself, through product discovery, comparison, and related-product suggestions. Furthermore, companies with strong traffic entry points and merchandising capabilities can look beyond the limits of their own inventory and consider expanding into a marketplace model.
For device and media companies, everyday consumer touchpoints provide a distinctive opportunity to develop direct insights into consumers' behaviors and interests. By using AI to deepen these insights and connecting them with brands and retailers, these companies can expand their role—shaping demand before consumers have formed explicit purchase intentions and guiding them through to purchase.
1. How Is AI Changing the Way Consumers Shop?――From Shopping Assistance to Purchase Decisions
Generative AI is rapidly expanding its role in the shopping journey. By understanding consumers' needs—even when they are vaguely expressed—and the context behind them, AI is beginning to take on decisions that consumers have traditionally made themselves: what to buy, which product to choose, and when and where to make a purchase. As a result, a new decision layer is emerging between consumers and companies.
In this report, we define agentic commerce as purchases in which AI meaningfully shapes purchase behavior, including purchase decision, through to those in which AI also executes the purchase.
1.1 Defining Agentic Commerce and Its Market Scope
To understand the true scale of agentic commerce, we need to look beyond whether a transaction is completed through AI. The more fundamental question is whether AI meaningfully shapes the consumer's purchase decision.
Consider a consumer who asks AI to recommend running shoes suited to their needs. Based on the recommendations, the consumer selects a pair but completes the purchase on the brand's website or at a physical store. Although AI does not execute the transaction, it has played a decisive role in determining what the consumer buys.
To capture this distinction, BCG classifies AI involvement in shopping into five levels, from L0 to L4, based on the depth of AI's role in the purchase journey. We define as agentic commerce as purchases at L2 and above, where AI begins to meaningfully shape product purchase decisions. At L2, AI recommendations materially influence which products or combinations of products consumers choose. At L3 and above, AI's role extends to purchase execution (Exhibit 1).
This definition captures both purchases completed through AI and those in which consumers make their final transactions through conventional e-commerce channels or physical stores after AI has shaped their decisions.
How large is Japan's agentic commerce market under this definition? To answer this question, BCG conducted a proprietary survey of 3,606 consumers in Japan. The following chapter examines the market's current scale and its projected growth through 2030.
2. How Large Will Japan's Agentic Commerce Market Become?――Japan's Agentic Commerce Market Is Projected to Reach JPY 15.6 Trillion by 2030
Applying this definition to Japan's market reveals that agentic commerce is already a substantial economic reality, rather than a distant vision of how people might shop in the future.
2.1 Agentic Commerce Is Already a JPY 12.5 Trillion Market in Japan
BCG estimates that Japan's agentic commerce market—defined as purchases at AI involvement level L2 and above—has already reached JPY 12.5 trillion in 2026, accounting for 18% of consumer spending across the 14 product and service categories covered in this study.
This figure represents more than consumers simply asking AI for shopping advice. It reflects purchases in which AI-generated recommendations materially influence product selection decisions, and in some cases extending through to AI-enabled purchase execution.
2.2 The Market Is Set to Grow to JPY 15.6 Trillion by 2030 as AI Adoption Broadens and Its Role Extends to Purchase Execution
BCG projects that Japan's agentic commerce market will expand from JPY 12.5 trillion in 2026 to JPY 15.6 trillion by 2030, with its share of the consumer market covered in this study increasing from 18% to 21% (Exhibit 2).
Today, many consumers still move from AI recommendations to separate e-commerce sites or physical stores, where they check prices and availability before completing their purchases. As AI becomes more closely integrated with retailers' and brands' systems—including payment, inventory, and delivery—product discovery, recommendations, and purchase execution can increasingly become part of a seamless shopping experience. Reflecting this shift, the share of the total market represented by L3+ purchases, in which AI's role extends to purchase execution, is projected to rise from 4% in 2026 to 6% in 2030. This signals AI's expanding role across the shopping journey, from shaping product decisions to enabling transaction execution.
2.3 The Additional Demand Agentic Commerce Could Unlock
Beyond its growing share of existing consumer spending, agentic commerce has the potential to unlock additional demand. Some purchases never happen despite an underlying desire to buy. Consumers may struggle to find the right product, become overwhelmed by comparisons, or abandon a purchase before completing it. AI can help recover this unmet demand by making it easier to discover, evaluate, and buy products. AI can also generate new demand by understanding consumers' preferences and everyday contexts, introducing them to products or experiences they had not previously considered. In doing so, AI can help turn latent needs into new desires—and ultimately into purchases.
The survey points to another intriguing possibility. As AI frees up consumers' time and helps them discover new interests, experiences, and products, spending on hobby and leisure categories could increase significantly.
BCG estimates that these forms of demand creation could represent up to approximately JPY 3.8 trillion in additional demand potential, separate from the projected JPY 15.6 trillion agentic commerce market in 2030.
3. What Value Does AI Bring to Consumers?――AI’s Shifting Value Proposition by Shopper Mission
The previous chapter defined agentic commerce according to the depth of AI involvement and examined the market today and its potential growth. But AI involvement level alone cannot fully explain the value AI brings to shopping. Equally important is the objective consumers are trying to accomplish: their Shopper Mission. Even when buying goods in the same category, consumers may want very different things from AI. Consider shopping for food and cooking. When the goal is to restock familiar essentials before they run out, value lies in a reliable purchase with minimal effort. But when the goal is to explore new culinary experiences, AI can create value by suggesting a new recipe and assembling all the ingredients in one go, rather than leaving the consumer to find each item separately.
BCG therefore organizes shopping behavior in Japan into eight Shopper Missions. The report uses Shopper Mission—why consumers are buying—together with AI involvement level as its core analytical framework. This lens reveals where AI is gaining traction, what consumers value in each situation, and how shopping behavior and competitive dynamics are changing.
3.1 Eight Shopper Missions: A Framework for the analysis
BCG identifies eight distinct missions that characterize everyday purchases. Routine Re-stock involves stocking up on familiar products at regular intervals. Quick Refill is about replenishing a small quantity that has run short. Need Now arises when something is unexpectedly required immediately. Deal Seek focuses on comparing prices and benefits to secure better purchasing terms. Occasion Planning involves working backward from a specific occasion or objective such as a home party, starting school, moving into a new home, or taking a trip—to assemble everything needed within a budget and other constraints. Specific Purchase means, with a specific purchase item in mind, finding the optimal product among a set of relevant alternatives. Treasure Hunt is the enjoyment of discovering unexpected products without a specific purchase objective. Socially Inspired describes a new interest sparked by friends, public figures, social media, or broader trends (Exhibit 3).
Across traditional industry boundaries, a diverse group of players is beginning to serve these different Shopper Missions, each drawing on their own strengths. The matrix of mission and AI involvement shows that both the depth of AI adoption and the value it creates vary substantially with the shopping objective. As the Shopper Mission changes, so does the value AI delivers. There is no single formula for winning.
Exhibit 4 maps prominent agentic commerce players across the eight Shopper Missions and AI involvement levels L1–L4. General-purpose AI services, e-commerce platforms, and category-focused offerings are already active across information support, product selection, and purchase execution. Their differences cannot be explained by business model alone: each brings distinctive positioning and capabilities to particular consumer missions.
3.2 Three Distinct Ways AI Creates Value Across Shopper Missions
We examine adoption using the L2+ penetration rate: the share of spending within a Shopper Mission in which AI meaningfully shapes purchase decisions or executes purchases. When the eight missions are grouped by similarities in the value AI delivers, three patterns emerge: Convenience & Efficiency, Price & Value Optimization, and Explore & Leisure (Exhibit 5).
Convenience & Efficiency
In Routine Re-stock, Quick Refill, and Need Now, AI's main value lies in reducing the work involved in shopping and ensuring that needed products are obtained reliably. By tracking inventory and consumption, choosing the right product at the right time, and linking selection with purchasing and delivery, AI can simplify the entire process. L2+ penetration in 2026 stands at 15% for Routine Re-stock, 15% for Quick Refill, and 20% for Need Now. By 2030, these rates are expected to reach 16%, 17%, and 22%, respectively, a relatively modest increase. Existing services such as subscriptions and repeat ordering already solve some of the convenience problems, leaving fewer visibly unmet needs in the survey.
For AI to deliver greater value, it is important not only to organize product information so that AI can correctly understand product attributes and use cases, both online and offline, but also to track which products are located where and to connect AI with supporting infrastructure such as inventory detection, consumption forecasting, automated ordering, and on-demand delivery.
Price & Value Optimization
In Deal Seek and Occasion Planning, AI helps consumers find better options across multiple constraints, including product price, purpose, and total budget. For Deal Seek, it can compare discounts, rewards, total costs, and substitutes to identify the most advantageous purchasing terms. For Occasion Planning, AI can work backward from questions such as who is attending, what the occasion calls for, and how much can be spent, then assemble the right combination of products.L2+ penetration in 2026 is 17% for Deal Seek and 23% for Occasion Planning, projected to rise to 19% and 26% by 2030. The value proposition is particularly compelling in Occasion Planning: consumers need to coordinate several products under shared constraints rather than selecting a single item (Exhibit 6).
Home-party planning was among the examples frequently raised by consumers. Imagine telling AI the budget, guest list, desired cuisine, dietary preferences, and allergies. It works backward to suggest wine, soft drinks, snacks, and desserts as one coordinated selection and can enable a “one-click” purchase. Like a thoughtful concierge, it can remove much of the time and effort involved in getting everything ready.
In missions built around comparison and optimization, this added transparency can also intensify competition, as products become easier to compare and select on price and functionality.
Explore & Leisure
In Specific Purchase, Treasure Hunt, and Socially Inspired, AI can help consumers find something that suits their needs, discover unfamiliar products, and turn the excitement of wanting something into a concrete purchase. Although these missions begin with different motivations, they share a common opportunity: AI can understand consumers' tastes and lifestyles and introduce options they are excited about but might never have considered themselves.
Even as AI makes comparison and optimization more efficient, product choices do not all come down to specifications and price. In explore-oriented missions, AI can account for personal style, intended use, a brand story and attributes, and a product's originality. It can bring brands and consumers together in new ways. For companies, the priority is to secure these types of spaces where brand identity and consumer tastes resonate, nurturing value beyond price and encouraging greater willingness to pay.
In markets where agentic commerce is advancing, shopping is starting to evolve from searching for what one already wants to discovering possibilities one did not know one had. When consumers share a photo of themselves with AI, styles, and products they would never have thought of appearing one after another, tailored to their tastes and the occasions, they can compare options across brands, virtually try on products, and repeatedly encounter new possibilities that feel personally relevant before seamlessly completing a purchase. AI is becoming a place where new preferences—and demand itself—can take shape (Exhibit 7).
4. Where Does AI Deliver the Most Value Across Product Categories?――How AI Is Changing Product Selection and Purchase Behavior
Product categories differ considerably in how widely AI is used and where in the purchase journey it adds value. The survey reveals striking variations in L2+ penetration (Exhibit 8). Baby & Kids leads at 31% in 2026 and is projected to reach 38% by 2030. Cosmetics is also high at 29%. Books, Magazines & Manga and Furniture, Home Furnishings & Household Goods are each projected to rise from 23% to 27%; Alcoholic Beverages from 21% to 24%; and Fashion & Apparel from 20% to 23%. Prepared Foods and Household Essentials, by contrast, remain at around 10%.
A clear pattern emerges: AI tends to penetrate earlier where purchasing involves a greater burden of judgment—whether consumers need specialist knowledge, face an overwhelming choice of products, or would traditionally physically examine the products. AI can supplement expertise, help consumers narrow down an extensive range of options, and make it easier to assess products digitally that once required physical examination.
AI’s value proposition by product category can be broadly grouped into three types.
1. Supplementing Expert Knowledge
In categories such as Baby & Kids and Cosmetics, consumers may not even know which criteria to use when choosing. AI can organize relevant information, establish a set of decision criteria, and narrow down options for each person's circumstances, helping consumers make informed choices without specialized expertise.
For first-time parents, choosing products that may not be well suited to their child or may raise safety concerns can be a source of significant anxiety. The challenge is compounded by the need to continuously adapt purchases to a child's development, requiring parents to repeatedly determine what is needed at a given stage, what size is appropriate, and how product safety should be evaluated. If AI could draw on a child's age and developmental stage, the intended use, experienced parents' perspectives, and reliable information to suggest 'This could be right for your child now,' choosing products might feel like seeking advice from someone they trust (Exhibit 9).
2. Finding the Right Product in an Overwhelming Range of Choices
In categories such as Alcoholic Beverages, Seasonings, Books, and Cosmetics, extensive long-tail assortments make it difficult to identify the best-fitting product. AI can go beyond price and features to consider each consumer's lifestyle, preferences, intended use, and circumstances, then narrow thousands of possibilities to a personally relevant shortlist.
In cosmetics, shopping may begin with a moment of inspiration: watching a video or scrolling through social media and thinking, 'I love that look.' AI can identify the products used in the video or post, then recommend suitable items and alternatives based on the consumer's skin type, preferences, and budget. A fleeting moment of admiration can become a tangible product choice (Exhibit 10).
3. Digitally Replicating or Augmenting the Benefits of Physical Product Inspection
In Fashion & Apparel and Furniture, Home Furnishings & Household Goods, consumers have traditionally needed to see and touch products to judge color, texture, fit, size, and how an item works in a particular space. AI, combined with other technologies, is increasingly helping them assess these qualities digitally. In fashion, photographs of consumers and items they already own can help them visualize whether a piece suits them—or would make the right gift for someone else.
Imagine a consumer who has just moved and takes a photograph of their living room. They tell AI, 'I want the calm, natural look of a hotel I loved while traveling, with warm wood and off-white tones.' AI considers the room's dimensions, window positions, existing furniture, and budget, then proposes a complete setting—sofa, lighting, rug, table, and accessories. Instead of selecting products one by one, the consumer begins with a finished vision that makes them think, 'I want to live in this room.' AI helps turn their personal aesthetic into an entire space, reaching beyond merely compensating for physical inspection.
5. Where Are the Earliest Signs of Agentic Commerce's Future?――Younger Consumers Are Already Showing How Shopping Could Evolve
Consumers aged 18–29 are already exhibiting behaviors that offer an early view of agentic commerce's future. Although they represent only 17% of survey respondents, they account for 41% of L2+ spending. Their per-capita L2+ spending is 2.4 times the overall average. Generative AI usage reaches 86% among this group, and 62% use it at least three days per week. Some 65% also report more complex AI usage, such as engaging in extended dialogue and assigning multiple consecutive tasks and decisions to AI, compared with 39% overall. Younger consumers lead both in the breadth of situations in which they use AI and in the sophistication of that use.
5.1 Making AI the Starting Point for Everyday Shopping
Among younger consumers, AI penetration is high across all eight shopper missions and is not limited to specific situations where AI is uniquely needed (Exhibit 11). They are beginning to use AI as a starting point for everything from discovering exciting new products to routine replenishment and price-and-value optimization.
Among middle-aged and older consumers, AI tends to be used when existing shopping experiences leave needs unmet or purchasing decisions feel difficult. Younger shoppers, by contrast, integrate AI naturally into the purchase journey whether or not the task is burdensome. Even in everyday categories such as food and beverages, the rate of purchases involving AI is more than twice the overall average (Exhibit 12). Their behavior offers an early view of how AI could evolve from a problem-solving tool into an everyday shopping interface.
5.2 Moving More Quickly Toward Delegating Decisions to AI
Having grown accustomed to using AI in everyday life, younger consumers are more receptive to its recommendations. Whereas middle-aged and older shoppers may move gradually from L1 information gathering to L2 and L3 as experience and trust build, younger shoppers may compress these stages and move directly toward delegating product choice and purchase execution. They offer an early glimpse of agentic commerce's future in both the breadth of AI use and the depth of decisions entrusted to it.
"I use AI regularly, not just for shopping but for things like cooking, planning trips, and looking up information. I increasingly ask AI first about things I used to search for online. When shopping, I often compare options with AI and even ask, 'Is this really the right choice?' before deciding. If AI could understand my tastes, my size, and the brands I usually like, I would be happy to let it handle everything from recommendations to purchasing. Ideally, I would leave routine replenishment entirely to AI." — Female office worker in her 20s (interview respondent)
6. What Should Companies Do?
Building on the above, we outline the key questions to consider and the areas requiring early action for different sectors: Consumer Goods, Retail & Fashion, and Devices & Media players (Exhibit 13).
6.1 Consumer Goods Companies
Three priorities stand out for consumer goods companies. First, rethink competitive strategy and investment based on how winning differs by Shopper Mission. Second, review product portfolios through a mission-led lens to identify opportunities for product development. Third, capture cross-border opportunities opened up by agentic commerce.
Rethink Where to Compete and Invest by Shopper Mission
Competitive advantages look different across Shopper Missions. Consumer goods companies need to understand how AI delivers value and allocate investment across three strategic imperatives: win the default position; distinguish products that compete on functionality and price; and secure spaces where a brand's world can resonate with consumers.
Win the default position. In Convenience & Efficiency missions, a product that becomes an established AI recommendation may continue to be chosen for replenishment and repeat purchases. With fewer opportunities for consumers to compare alternatives every time they shop, brands may become less exposed to recurring price competition. But companies that move slowly risk finding competitors entrenched as the default, leaving little room to break in. Establishing a place among AI's preferred options early is critical.
Distinguish products that compete on functionality and price. In Price & Value Optimization missions, AI makes it easier to compare and rank products side by side on price, promotions, pack size, and purchasing conditions. Companies need portfolios that clearly distinguish which products will compete on function and price and which will protect other forms of value. Second brands, separate product lines, and private-label offerings may all play a role.
Secure spaces where a brand's world can resonate with consumers. In Explore & Leisure missions, AI becomes a place where consumers encounter new products and brands. Securing spaces in which a brand's story and attributes and a product's originality can connect with consumer tastes and lifestyles can help shape preferences, attract new customers, and create demand. In the AI era, it is particularly important to identify the Shopper Missions and touchpoints where brand value truly matters—and invest accordingly.
These different routes to advantage require deliberate choices about the missions in which the company seeks to lead and where it concentrates resources.
Reassess the Product Portfolio Through a Shopper Mission Lens
Companies should examine which missions their existing products serve well and where their offerings fall short. Unmet needs within a particular mission may reveal opportunities to develop new products, or re-position existing products. This mission-led view adds a valuable dimension to portfolio strategy in agentic commerce.
Capture Cross-Border Opportunities Through Agentic Commerce
Agentic commerce platforms could help consumer goods companies reach and sell to overseas consumers without depending as heavily on local stores or their own e-commerce sites, opening up opportunities to capture international demand at a lower cost of entry.
6.2 Retail and Fashion Companies
For retailers and fashion companies, the priority is to own the customer traffic. Building and strengthening their own agentic AI capabilities in-house can become an important foundation for competitiveness. Three opportunities stand out: translate customer understanding into incremental visits and purchases, connect AI seamlessly with physical stores and enhance in-store experience, and consider to expand into a marketplace model that goes beyond their own inventory.
Turn Customer Understanding into Traffic and Sales Growth
By owning the AI entry point through their apps and other direct interfaces, and improving the underlying data collection and AI engines, retailers can translate customer knowledge into more relevant recommendations—particularly for Treasure Hunt and Socially Inspired missions.
Consider a retailer serving consumers who enjoy cooking. AI could suggest an unfamiliar recipe or an appealing new dining occasion and recommend the fresh ingredients and seasonings needed to bring it to life. Such suggestions can create discoveries that fit each shopper's lifestyle, encouraging more frequent visits and higher basket spending per customer. Developing owned AI capabilities can turn customer relationships into growth and improve store productivity. In fashion, AI can draw on consumers' styles and occasions to inspire new looks, personalize recommendations, and visualize how an outfit would appear—turning vague interest into a specific product choice and purchase.
Connect AI Seamlessly with Stores—As Both a Traffic Channel and an In-Store Experience
In the survey, approximately 70% of AI-involved cosmetics purchases under the Need Now mission were ultimately completed in physical stores. Many consumers who use AI to explore and compare products still visit a store to make their purchases. Retailers therefore need to ensure that accurate inventory and store information is accessible to their AI-powered touchpoints and that consumers arriving with AI-informed purchase intent can find and buy what they need smoothly. This integration of online and offline channels can make AI a powerful source of store traffic.
There is also considerable potential to integrate AI into the store experience itself. A customer browsing shelves might use the retailer's AI app to ask where a product is located or upload a photograph of something that catches their eye. AI could immediately compare options within the store and suggest products or complementary items matched to their preferences. This can make shopping both easier and more enjoyable, while encouraging additional purchases and increasing basket size.
Explore Marketplace Model Beyond Owned Inventory
Retailers with strong customer touchpoints and compelling product recommendation capabilities can also consider expanding the assortment they recommend beyond the inventory they own. A marketplace model could offer consumers greater one-stop convenience while giving retailers a broader assortment and new revenue opportunities, including sales commissions.
The opportunity for retail and fashion companies extends across the entire purchase journey—and potentially into how they structure assortments and generate revenue—not just how they understand customers and make recommendations.
6.3 Device and Media Companies
Device and media companies have a distinctive opportunity to shape demand before consumers have formed explicit purchase intent, then guide them toward purchase. Their everyday consumer touchpoints provide direct insight into behavior, interests, and the contexts in which needs emerge.
By using AI to deepen those insights, uncover latent needs, and introduce consumers to new products, these companies can play a greater role in demand creation. Connecting their insights and AI-driven experiences with brands and retailers would allow them to extend that role from the earliest stages of preference formation through to purchase.
Conclusion
The pace and ultimate form of agentic commerce remain uncertain. Yet the shift from AI as a source of information to AI as a force shaping purchase decisions—and increasingly executing purchases—is already under way in Japan.
Companies need to recognize these changes early and identify the Shopper Missions and customer touchpoints that matter most to them. As AI transforms how consumers decide and buy, companies should invest in sharpening the reasons customers choose them and the value they deliver. Those choices will help determine the next sources of growth and competitive advantage.
Methodology and Notes
- Market shares refer to the 14 product and service categories covered by this study.
- BCG conducted an online survey in August 2026 of 3,606 consumers aged 18–74 in Japan, covering purchase behavior, AI use, Shopper Missions, and AI involvement levels across 14 product and service categories.
- Market sizing for the 14 categories uses the Shopper Mission, purchasing channel, and AI involvement level distributions observed in the consumer survey. Category market sizes are based on Euromonitor International's forecast 2026 retail selling price (RSP) sales, adjusted to the domestic consumer market by deducting estimated inbound visitor spending using data from Japan's tourism authorities. Channel composition and AI involvement proportions are based on the survey.
- Categories covered: Prepared Foods & Meal Solutions; Personal Care; Fashion & Apparel; Pet Care; Baby & Kids; Beverages; Cosmetics; Processed Foods, Snacks & Seasonings; Furniture, Home Furnishings & Household Goods; Household Essentials; Consumer Electronics & Digital Devices; Alcoholic Beverages; Books, Magazines & Manga; and Fresh Foods.
- The 2030 projection reflects survey responses on expected changes over the next three to five years in purchasing frequency, channel composition, and AI involvement level by Shopper Mission, applied to the 2026 baseline to estimate the L2+ market.
- L3+ as a share of the total scoped market is the retail sales value of L3 and L4 purchases divided by total category retail sales. The 2026 figure reflects the survey; the 2030 figure is an estimate based on the forward-looking assumptions described above.
- L2+ penetration is the share of retail sales within a given Shopper Mission attributable to L2–L4 purchases in which AI meaningfully shapes purchase decisions or executes purchases. The 2030 estimate reflects expected changes over the next three to five years in purchase frequency, purchasing channel, and AI involvement level, applied to the 2026 market baseline. L2+ penetration measures the extent of AI involvement, not the underlying strength of demand for AI.
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About Glance
Glance is an innovative shopping agent redefining the shopping experience. Across smartphones, televisions, apps, and other devices, it combines predictive technologies, visual processing, and real-time connectivity through its proprietary AI platform to open new possibilities for commerce. Glance is operated by Glance InMobi Pte. Ltd., an affiliate of global technology leader InMobi, and is backed by Mithril Capital, Google, and Jio Platforms.
Contributors
Orie Nagamine — Partner, BCG Tokyo
Jingyi Yang — Senior Associate, BCG Tokyo
