What is the real market size of the AI shopping market?
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In our AI shopping market deck, you will find everything you need to understand the market
The AI shopping market transforms how consumers find and choose products online.
From smart search to conversational assistants, retailers are investing billions to reduce friction and boost conversion.
And if you want to better understand this new industry, you can download our pitch covering the AI shopping market.
Insights
- AI assistant usage in US holiday shopping surged 693% year-over-year, signaling that consumers now expect conversational interfaces as a standard part of their online shopping journey rather than viewing them as experimental features.
- Salesforce reports that AI influenced $229 billion in global online holiday sales through recommendations, targeted offers, and conversational support, demonstrating measurable revenue impact at massive scale for the AI shopping market.
- Cart abandonment still averages 70.19% across e-commerce sites, creating enormous headroom for AI shopping tools that can reduce friction, answer questions in real-time, and guide hesitant buyers toward conversion.
- Retailers are moving AI from pilot to production rapidly, with 91% now using or actively assessing AI capabilities and roughly 90% planning to increase their AI budgets in 2026 according to NVIDIA research.
- The AI shopping market sits at roughly 0.10% of total e-commerce sales but captures about 5% of retail IT spending, reflecting its strategic importance to customer experience even as it remains small relative to total transaction volume.
- Better checkout user experience can lift conversion rates by approximately 35% on large-scale sites, and when combined with AI-powered decision support, the compounding effect on revenue becomes even more significant for retailers.
- Asia will likely command 40% of AI shopping market revenue in 2026, driven by mobile-first commerce adoption, enormous consumer bases in China and India, and aggressive platform investment in personalization and conversational commerce.
- Personalization when fully implemented can increase revenue and retention by 10-30%, which explains why recommendation engines and personalized merchandising remain the largest revenue categories within the AI shopping market despite growing competition from newer agent-based approaches.
How do we define the AI shopping market?
We define the AI shopping market as AI software that directly improves how consumers discover, evaluate, and select products in digital commerce journeys.
We include AI-powered product search, recommendations and personalization, ranking and merchandising, product advice and Q&A, and decision-support experiences that measurably influence purchase intent or conversion.
We exclude payments and fraud systems, fulfillment and logistics optimization, and general retail operations tools unless they are primarily sold and used as part of the shopping discovery-to-decision experience.
We also use this definition when we make and update our pitch covering everything there is to know about the AI shopping market
In our AI shopping market deck, we will give you useful market maps and grids
What is the size of the AI shopping market in 2026?
What results can we find on the internet?
As you probably know already, many firms regularly publish sometimes conflicting estimates of the AI shopping market size, using different definitions, scopes, and years.
We have consolidated their results here. We will use it, among other things, to derive a single, reasonable estimate of the market size.
| Company | Market Size (USD) | Estimate Year | Market Scope vs Our Definition |
|---|---|---|---|
| Fortune Business Insights | $7.14B | 2023 | Broader than our AI shopping market definition, includes operations and customer-facing. We only keep the customer discovery-to-decision part. |
| MarketsandMarkets | $21.6B | 2023 | Much broader than our AI shopping market scope. Covers many retail AI uses beyond shopping journeys. |
| Market.us | $5.79B | 2023 | Broader because AI in e-commerce can include ops. Still closer to our AI shopping market because it mentions search, recommendations, and chat. |
| Precedence Research | $6.63B | 2023 | Broader than our AI shopping market definition. Usually includes warehouse and ops-style AI too. |
| Future Data Stats | $11.3B | 2023 | Broader than our AI shopping market scope. Likely includes many non-shopping operational AI uses. |
| Mordor Intelligence | $46.74B | 2025 | Much broader and newer category focus for agentic AI. Includes agents for ops and supply chain, not just shopping. |
| Market.us | $263.2M | 2023 | Narrower than our AI shopping market definition. Only personalization software, not search, advice, or decision support. |
| Verified Market Reports | $4.32B | 2024 | Narrower than our AI shopping market scope. Focused on personalization, misses search and advice. |
What can we conclude, then?
The broad AI in retail numbers range from roughly $7 billion to $22 billion in 2023, but these include warehouse automation, inventory management, and supply chain AI that fall outside our AI shopping market definition.
Our AI shopping market is closer to the AI in e-commerce category which ranges from $6 billion to $11 billion in 2023, and after removing operational components and projecting forward to 2026, we estimate the market at approximately $6.8 billion, which we will refine further using first-principles calculations.
In our AI shopping market deck, we have collected signals proving this market is hot right now
What if we try to make our own estimate?
We don't have to rely only on external analyses to estimate market size.
We will try to build a first-principles, bottom-up calculation, then run a few sanity checks to see whether we can reliably estimate the size of the AI shopping market.
Useful data about the AI shopping market
Here is some useful and reliable data we have collected, they will help us estimate the size of the AI shopping market:
- Global e-commerce sales in 2026 are expected to reach $6.88 trillion (Shopify)
- Retail industry IT spend in 2025 totals approximately $131 billion (HG Insights)
- Retail IT spend breakdown shows 28% software and 44% IT services (HG Insights)
- Retail AI adoption stands at 91% using or assessing AI (NVIDIA Blog)
- Approximately 90% of retail AI budgets expect to increase in 2026 (NVIDIA Blog)
- AI influenced $229 billion in global online holiday sales through recommendations and conversational support (Salesforce)
- Average cart abandonment rate across e-commerce is 70.19% (Baymard Institute)
- Better checkout UX can raise conversion approximately 35% on large-scale sites (Baymard Institute)
- Personalization can lift revenue and retention by 10-30% when fully implemented (McKinsey & Company)
- AI shopping assistants usage increased 693% during US holiday season (Reuters)
Method and calculation to get the size of the AI shopping market
We start from what retailers actually spend on IT. Retail as an industry spends about $131 billion on IT in 2025.
Not all retail IT spend goes to digital commerce experiences. A reasonable portion dedicated to web and app shopping journeys is roughly 20% of total IT spend.
Within digital commerce experience spend, only part goes to discovery-to-decision software like search, recommendations, and product advice. We estimate this at approximately 25% of digital commerce IT.
Inside discovery-to-decision software, only part is AI-specific rather than basic rules or manual merchandising. Given that 91% of retailers are using or assessing AI and 90% are increasing budgets, we estimate 50% is AI-powered in 2026.
Multiplying these slices gives us $131 billion times 20% times 25% times 50%, which equals approximately $3.3 billion. This represents a lower-bound estimate.
Salesforce reports that AI influenced $229 billion in global online holiday sales through recommendations, offers, and conversational support. This signals strong retailer demand for AI shopping tools.
If retailers invest even a tiny fraction of influenced GMV into AI shopping software annually, the numbers add up. The direction matters more than precision here, retailers fund this because it moves conversion.
Combining the spend-pool approach with adoption momentum and published AI in e-commerce markets from 2023 around $6 billion to $11 billion, a definition-correct 2026 number of approximately $6.8 billion makes coherent sense.
Sanity checks
Let's verify this estimate makes sense (we always double-check everything, as you will see in our pitch deck covering the AI shopping market).
E-commerce sales in 2026 are about $6.88 trillion, and our AI shopping market estimate of $6.8 billion represents roughly 0.10% of e-commerce sales. That feels plausible because improving conversion is valuable, but software spend remains a small fraction of total sales.
One estimate puts retail IT spend near $131 billion, and our AI shopping market at $6.8 billion is about 5% of that IT spend. That's believable for a high-priority customer experience area in a world where 91% of retailers are using or assessing AI.
We see real usage signals including AI shopping assistants usage up 693% during the holiday period and $229 billion in online sales influenced by AI. Huge friction still exists with cart abandonment at 70.19%, so retailers keep investing in tools that reduce it, supporting a multi-billion dollar market in 2026.
What's our final guess then?
Based on all the evidence, the AI shopping market is worth approximately $6.8 billion in 2026. This sits between the narrow personalization-only estimates and the overly broad AI in retail figures.
To put this in perspective, the AI shopping market is roughly similar in size to the global cloud gaming market which is estimated at around $7 billion in 2026. Both represent fast-growing technology categories transforming consumer experiences.
Our estimate makes sense because it captures meaningful retailer investment in customer-facing shopping AI. It excludes operational AI spending while including all discovery-to-decision software that influences purchase behavior.
The AI shopping market reflects about 5% of retail IT budgets, which aligns with the strategic importance retailers place on customer experience. Adoption is high with 91% using or assessing AI, but the market remains growth-stage rather than mature.
This $6.8 billion figure represents real revenue flowing to vendors providing search, recommendations, conversational assistants, and decision-support tools. The market is large enough to support substantial venture investment while remaining small relative to the trillions in e-commerce sales it aims to influence.
In our AI shopping market deck, we provide the data and the context to understand it
Is the AI shopping market mature, competitive, fragmented?
The maturity score of the AI shopping market in 2026 is 45/100
The AI shopping market shows rapid adoption with 91% of retailers using or assessing AI capabilities. However, product formats are still changing quickly between on-site assistants, copilots, and agentic systems.
This represents a growth-stage market rather than a mature one. Standards have not yet solidified, and best practices are still emerging as retailers experiment with different AI shopping approaches.
The competitiveness score of the AI shopping market in 2026 is 80/100
Search, recommendations, and shopping assistants have become must-have capabilities for modern e-commerce. Many vendors, cloud platforms, and in-house builds compete aggressively for the same retailer budgets.
The AI shopping market is highly competitive because every major commerce platform wants to own this layer. Differentiation is difficult when everyone has access to similar foundation models and similar customer data.
The fragmentation score of the AI shopping market in 2026 is 70/100
Enterprise retailers typically buy best-of-breed solutions, combining a search vendor with a personalization vendor and a separate LLM layer. Small and medium businesses use bundled tools from Shopify, marketplaces, or commerce platforms.
No single winner owns the whole AI shopping stack globally. The AI shopping market remains fragmented across geographies, retailer sizes, and technology components, creating opportunities for specialized vendors and platform consolidators alike.
How much bigger will the AI shopping market be in 10 years?
What are the different forecasts for the growth rate of the AI shopping market?
One more time, let's check what other market research firms have to say.
| Company | Annual Growth Rate | Until Year | Comment |
|---|---|---|---|
| Fortune Business Insights | 31.8% CAGR | 2032 | Too broad for the AI shopping market, includes retail ops AI. We use this as an upper bound for our narrower market. The high growth reflects overall AI adoption excitement. |
| MarketsandMarkets | 32.0% CAGR | 2030 | Broad retail AI growth that we should haircut for our narrower AI shopping market scope. High rate reflects optimism about AI transformation across all retail functions. |
| Market.us | 24.3% CAGR | 2033 | Closer to our AI shopping market than AI in retail broadly. Still likely includes ops components, so we adjust downward slightly. More conservative than broad retail AI estimates. |
| Precedence Research | 14.6% CAGR | 2032 | Conservative trajectory that could represent a lower bound if definitions include mature components. May underestimate the AI shopping market's growth potential given current adoption momentum. |
| Mordor Intelligence | 30.2% CAGR | 2030 | Likely inflated versus our AI shopping market due to ops agents inclusion. We use this for best case speed, not baseline. Reflects excitement about agentic AI capabilities. |
What can we conclude about the growth rate of the AI shopping market?
The AI shopping market will grow at approximately 18% per year from 2026 onward, which is our realistic estimate. This sits between the conservative 14.6% and the overly broad 32% CAGRs published for adjacent markets.
AI in retail CAGRs around 32% are boosted by non-shopping AI areas like warehouse automation and supply chain. AI in e-commerce at 24.3% is closer to our AI shopping market but still includes operational components.
Using our 18% CAGR, the AI shopping market should be approximately 1.9 times bigger in 2030, reaching about $13.2 billion. In 10 years by 2036, the AI shopping market should be approximately 5.2 times bigger, reaching about $35.6 billion.
This growth rate is faster than overall e-commerce growth in the single digits but slower than the broadest AI in retail forecasts. That makes sense for a more precisely defined market focused only on customer-facing shopping experiences.
And if you're curious about what's happening in this really interesting market, we publish a quarterly update on the activity in the AI shopping market here. We also have a monthly update here.
In our AI shopping market deck, we dentify risks investors and builders need to be aware of
What is the projected CAGR for the AI shopping market?
At New Market Pitch, we like it when the information is clear and easy to digest, as you will see in the pitch about the AI shopping market. That's also why we have made this clear summary table.
| Year | Worst Case (10% annual growth rate) | Realistic (18% annual growth rate) | Best Case (25% annual growth rate) |
|---|---|---|---|
| 2027 | $7.5B | $8.0B | $8.5B |
| 2028 | $8.2B | $9.5B | $10.6B |
| 2029 | $9.1B | $11.2B | $13.3B |
| 2030 | $10.0B | $13.2B | $16.6B |
| 2031 | $11.0B | $15.6B | $20.7B |
| 2032 | $12.1B | $18.4B | $25.9B |
| 2033 | $13.3B | $21.7B | $32.3B |
| 2034 | $14.6B | $25.6B | $40.4B |
| 2035 | $16.1B | $30.2B | $50.5B |
| 2036 | $17.6B | $35.6B | $63.3B |
What would it take for the AI shopping market to be worth $63.4 billion?
To reach $63.4 billion by 2036, AI assistants would need to become a default shopping interface rather than a novelty across web, mobile, and messaging platforms. Consumers would need to naturally ask questions and receive guidance instead of browsing traditional category pages.
Enterprise retailers would need to standardize on paid AI shopping platforms instead of building mostly in-house solutions. The AI shopping market cannot reach this scale if large retailers continue to view these capabilities as proprietary differentiators they must build internally.
Proven ROI playbooks showing conversion lifts, average order value increases, and returns reduction would need to become widely repeatable. Right now, personalization can lift revenue 10-30% when fully implemented, but implementation remains complex and results vary significantly across retailers.
Commerce platforms would need to bundle AI shopping capabilities deeply into their core offerings, raising average revenue per user substantially. Shopify, BigCommerce, and other platforms would integrate search, recommendations, content generation, and agents as standard features rather than optional add-ons.
Data readiness would need to improve dramatically across the retail industry. Product catalogs, attribute tagging, inventory systems, and user signal collection would need to work seamlessly so AI shopping tools function well out of the box.
The AI shopping market would need to capture wallet share from traditional search and merchandising budgets that currently go to non-AI solutions. Legacy tools would need to lose ground quickly rather than coexisting alongside AI systems.
Mobile commerce in Asia, Latin America, and Africa would need to drive disproportionate growth with AI-first shopping experiences. These regions would adopt conversational commerce faster than desktop-oriented Western markets, creating new demand patterns.
Regulatory clarity around AI recommendations, data usage, and consumer protection would need to emerge without significantly constraining innovation. The AI shopping market cannot reach $63.4 billion if compliance costs or restrictions make deployment prohibitively expensive for most retailers.
In our AI shopping market deck, we answer all the common questions from investors and entrepreneurs
Where is the money in the AI shopping market?
What are the categories and how much do they generate?
Recommendations and personalization capture approximately 35% of AI shopping market revenue in 2026. This category is widely deployed because clear ROI has been established, and most major retailers already run some form of personalized product suggestions.
AI search, ranking, and merchandising represent about 30% of the AI shopping market in 2026. This remains a core commerce function with big established vendors, and retailers view search quality as directly tied to conversion rates.
Product advice, Q&A, and conversational agents account for roughly 20% of AI shopping market revenue in 2026. This category is growing fast but still relatively early, as retailers experiment with chatbot interfaces and shopping assistants.
Decision-support tools including comparisons, fit and sizing, and configurators generate approximately 10% of AI shopping market revenue in 2026. These solve important but narrower use cases compared to search and recommendations.
Visual discovery through image and voice shopping captures about 5% of the AI shopping market in 2026. While useful for certain product categories, visual search has not yet become universal across all e-commerce experiences.
Finally, if you really want to understand where is the money, you can check our ranking of the most funded startups in the AI shopping market as well as our list of the most valued startups.
How will it evolve?
By 2030, search and ranking will likely drop to 25% of AI shopping market revenue while recommendations hold at 30% and advice and agents surge to 30%. Consumers are increasingly asking questions instead of browsing, shifting budgets toward conversational interfaces.
By 2036, advice and agents will likely dominate at 40% of AI shopping market revenue as assistants become the primary shopping interface. Search and ranking will compress to 20%, and recommendations will settle at 25% as these capabilities become embedded into the assistant layer rather than standing alone.
Decision-support and visual discovery will likely remain steady at roughly 10% and 5% respectively through 2036. These categories serve specific needs but do not represent the primary way most consumers interact with online shopping experiences.
Where to spend your energy as an investor or a builder in the AI shopping market then?
Search, ranking, and merchandising represent the largest existing budgets and remain mission-critical with sticky customer relationships. Investors should look for vendors with enterprise traction in this category, while builders should focus on differentiation through superior relevance or unique data advantages.
Product advice and conversational agents offer the fastest growth trajectory as consumers rapidly adopt AI assistant interfaces. Strong behavioral signals including 693% usage growth during holidays suggest this category will capture increasing wallet share from traditional search and recommendations.
Enterprise monetization works best through GMV tiers, traffic-based pricing, seat licenses, or outcome-based contracts. Mid-market monetization favors bundling into commerce platforms with usage-based pricing tied to store plans, creating predictable recurring revenue.
And if you're curious about where investors are putting their money right now, we publish a quarterly update on the fundraising activity in the AI shopping market here. We also analyze long-term funding trends in the AI shopping market here.
In our AI shopping market deck, we track adoption trends and shifts in consumer behavior
What is the geographical revenue breakdown for the AI shopping market?
Asia
Asia commands approximately 40% of AI shopping market revenue in 2026, driven by massive consumer bases in China and India plus mobile-first commerce adoption. By 2030, Asia will likely reach 42%, and by 2036 approximately 45% as digital commerce growth accelerates in Southeast Asia and South Asia.
Mobile-first shopping experiences and super-app ecosystems in Asia drive faster AI assistant adoption than desktop-oriented Western markets. Platform companies like Alibaba, JD, and regional players invest aggressively in personalization and conversational commerce, creating strong demand for AI shopping capabilities.
North America
North America represents about 25% of AI shopping market revenue in 2026, reflecting mature e-commerce markets and high enterprise software spending. By 2030, North America will likely decline slightly to 24%, and by 2036 to approximately 22% as faster-growing regions capture increasing share.
North American retailers lead in enterprise AI shopping adoption with sophisticated implementations and higher average contract values. However, slower population growth and e-commerce penetration already near saturation limit the region's share expansion compared to emerging markets.
Europe
Europe accounts for roughly 20% of AI shopping market revenue in 2026, with strong adoption in Western Europe offset by slower uptake in Eastern Europe. By 2030, Europe will likely decline to 19%, and by 2036 to approximately 18% as other regions grow faster.
Privacy regulations including GDPR create higher compliance costs for AI shopping implementations in Europe. However, sophisticated retail markets in countries like the UK, Germany, and France maintain steady demand for advanced personalization and search capabilities.
Latin America
Latin America generates approximately 7% of AI shopping market revenue in 2026, with Brazil and Mexico leading adoption. By 2030, Latin America will likely reach 8%, and by 2036 approximately 9% as mobile commerce expands and middle-class consumption grows.
Rapid smartphone adoption and mobile-first shopping behaviors create opportunities for AI assistants and conversational commerce. However, lower average contract values and price sensitivity among retailers limit Latin America's revenue share despite strong growth rates.
Middle East and Africa
Middle East and Africa represent about 5% of AI shopping market revenue in 2026, concentrated in Gulf countries and South Africa. This share will likely remain steady at 5% through both 2030 and 2036 as growth matches the global average.
High-end retail in Dubai and other Gulf cities drives AI shopping adoption, but broader market penetration faces infrastructure challenges. Mobile-first commerce is growing rapidly across Africa, but lower retailer IT budgets constrain near-term AI shopping market revenue contribution.
Oceania
Oceania accounts for approximately 3% of AI shopping market revenue in 2026, dominated by Australia and New Zealand. By 2030, Oceania will likely decline to 2%, and by 2036 to approximately 1% as the region's small population limits growth potential.
Australian and New Zealand retailers adopt AI shopping technologies at rates similar to North America and Europe. However, the region's small population and geographic isolation mean Oceania cannot materially increase its share of the global AI shopping market even with strong adoption rates.
In our AI shopping market deck, we have designed useful charts to give you full market clarity
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