Global AI In Retail Market Trends, Forecast Report 2025-2037
AI In Retail Market size was over USD 9 billion in 2024 and is projected to reach USD 310.5 billion by the end of 2037, witnessing around 30.6% CAGR during the forecast period i.e., between 2025-2037. In 2025, the industry size of AI in retail is estimated at USD 11.7 billion.
The AI in retail market's growth is positively reinforced by the surging integration of AI into retail chains, supported by the proliferation of advanced AI tools in the market. The advent of inventory management systems bolstered by AI has significantly reduced inventory waste. A key use case can be analyzed via Target's expansion of the Inventory Ledger system, which facilitated billions of predictions forecasting demands. These advancements improve the order fulfilment efficiency and tie up with the trends of warehouse automation.
In the logistics sector, AI technologies have facilitated the last-mile delivery operations. In terms of supportive regulatory practices, the U.S. Department of Transportation’s Freight Digital Solutions report has highlighted the role of real-time tracking systems in the optimization of delivery routes to reduce congestion. These innovations highlight the successful use case of AI in retail, driving the market’s growth. Additionally, in terms of the economic factors of the AI in retail market, the table below highlights the CapEx investments by major players of the market:
|
Company |
2024 CapEx ($B) |
CapEx/Revenue (%) |
YoY Change (%) |
Primary Investment Focus |
|
Amazon |
$75 |
11.4% |
+55% |
AI infrastructure, AWS cloud services, generative AI |
|
Microsoft |
$55.7 |
13.7% |
+43% |
AI servers, Azure AI, OpenAI infrastructure |
|
Alphabet (Google) |
$52.5 |
14.6% |
+91% |
AI data centers, Google Cloud AI |
|
Meta |
$39 |
20.3% |
+38% |
AI infrastructure, language models, and advertising AI |
|
Alibaba |
$11.1 |
8.4% |
+82% |
AI and cloud infrastructure, foundational models |
The heightening capital investments in AI tech have accelerated the adoption of AI in retail. With a greater number of companies experiencing measurable improvements in meeting consumer demands, the market is set to remain competitive through the forecast period.
AI in Retail Sector: Growth Drivers and Challenges
Growth Drivers
-
Dynamic pricing and promotions supported by the increasing integration of AI: With a growing competition between physical and digital retail channels, a key differentiator is dynamic pricing. The advent and growing integration of AI have made dynamic pricing strategies smarter, bolstering the ROI of retailers. AI is able to mirror the customer behavior, market demands, and competitor pricing, allowing them to adjust prices and promotional offers in real time. The U.S. Department of Commerce has measured an 18% increase in promotion-driven revenue and a 12% rise in basket sizes facilitated by the application of AI-based pricing engines in 2024.
-
Rising usage of AI for security in e-commerce: The rising usage of behavioral metrics bolstered by AI has improved the security in e-commerce transactions. The heightened security ties up with the growing popularity of e-commerce in notable regional markets such as APAC. The improvements brought forth by AI to security support its greater application in retail, which expands the scope of market growth. By the end of 2037, the application potential of AI in retail is poised to expand significantly by leveraging the demand for security in e-commerce applications.
AI and ML Trends of the Global AI in Retail Market
Rapid advancements in AI and ML, such as in natural language processing (NLP), computer vision, and data analytics have been instrumental in improving the scope of AI for applications in the retail sector. The technologies are being integrated to improve the customer experience as well as bolster the efficiency of operations. For instance, AI systems are able to analyze large datasets to predict customer preferences, which are invaluable in creating targeted marketing strategies. The table below maps the successful use cases and their impact:
|
Use Case |
Technology Applied |
Impact/Result |
Source |
|
Personalized Recommendations |
NLP, Machine Learning |
21% increase in customer conversion rates |
U.S. Department of Commerce, 2023 |
|
Demand Forecasting |
Data Analytics, AI |
16% improvement in inventory turnover rate |
National Retail Federation (NRF), 2023 |
|
Visual Search and AI Shopping Assist |
Computer Vision, AI |
24% increase in customer satisfaction and engagement |
Innovation, Science and Economic Development Canada (ISED), 2023 |
|
Fraud Detection & Prevention |
Machine Learning, AI |
31% decrease in fraudulent transactions |
Cybersecurity & Infrastructure Security Agency (CISA), 2023 |
Cybersecurity Measures in the AI in Retail Market
The rising application of AI in retail has expanded the threat surface of cybersecurity challenges. Over the years, cyberattacks have become increasingly complex, which has driven the necessity for advanced security solutions. For instance, retailers are targeted by bot assaults driven by AI and data breaches, leading to considerable financial losses. The table below highlights the major cybersecurity measures in the AI in retail market:
|
Company |
Cyber Attack Type |
Impact |
Potential Remedies to Mitigate Impact |
|
Target |
AI-Driven Bot Attack |
Over 500,000 daily attacks during peak season; 58% increase in evasive bot traffic |
Implement advanced bot management solutions utilizing behavioral analytics; deploy CAPTCHA systems |
|
Walmart |
Phishing & Deepfake Attack |
Employees deceived into transferring funds; sensitive data compromised |
Conduct regular cybersecurity training focusing on social engineering tactics; implement multi-factor authentication (MFA) |
|
Home Depot |
Third-Party Vendor Breach |
Customer data accessed via compromised vendor; reputational damage |
Perform thorough due diligence on third-party vendors; enforce strict access controls |
Challenges
- Data silos and fragmented retail infrastructure: AI solutions have experienced great strides of improvement in the current decade but despite the advancements, a persistent challenge has emerged for retailers due to the fragmented nature of data ecosystems. The isolated data silos due to multiple sales channels causes a challenge in the seamless adoption of AI in retail. The AI-powered solutions require a clean data stream, and the lack of it can pose a constraint in integration.
AI in Retail Market: Key Insights
| Report Attribute | Details |
|---|---|
|
Base Year |
2024 |
|
Forecast Year |
2025-2037 |
|
CAGR |
30.6% |
|
Base Year Market Size (2024) |
USD 9 billion |
|
Forecast Year Market Size (2037) |
USD 310.5 billion |
|
Regional Scope |
|
AI in Retail Segmentation
Technology (Machine Learning, Natural Language Processing, Computer Vision)
The machine learning segment of the global AI in retail market is slated to hold a leading revenue share of 57.6% throughout the forecast period. The segment's lucrative expansion is attributed to the proliferation of advanced ML models to process vast datasets. The surging demand to improve customer experience is tied to the greater deployment of ML tools. Additionally, Walmart's utilization of ML has allowed the leading retail chain to tailor its inventory based on regional demand. The scope of heightened ROI is poised to lead to greater integration of ML in retail throughout the forecast timeline.
Application (Customer Personalization, Inventory Management, Pricing Optimization)
The customer personalization segment in the AI in retail market is slated to account for a leading revenue share of 40.6% during the anticipated timeline. A significant factor supporting the segment’s expansion is the greater application of AI-powered personalization tools to improve shopping experiences. Due to the boom of e-commerce, consumer perceptions and behaviors have changed over the years. In mobile-first economies, such as India, there has been a sustained push for personalized shopping experiences, prompting retailers to invest in advanced customer personalization AI tools. The scope of application is expected to expand by the end of 2037.
Our in-depth analysis of the global AI in retail market includes the following segments:
|
Technology |
|
|
Application |
|
Vishnu Nair
Head - Global Business DevelopmentCustomize this report to your requirements — connect with our consultant for personalized insights and options.
AI in Retail Industry - Regional Scope
Asia Pacific Market Forecast
The APAC AI in retail market is poised to account for a leading revenue share of 28.9% during the forecast timeline. The market’s growth has been facilitated by the advancements in AI technologies along with regulatory policies supporting large-scale digitalization. Opportunities in the APAC market are particularly notable in the economies of China, India, Japan, and South Korea. Key focus areas of the market include the advent of dynamic pricing strategies and the demand for smarter inventory management. Additionally, the e-commerce market has been booming in APAC due to the consumer preferences changing to non-contact shopping and the disposable incomes rising. The growth is intrinsically tied to the greater deployment of AI in retail solutions within APAC.
The Japan AI in retail market is projected for robust growth during the anticipated timeline. The market remains lucrative in Japan due to the proliferation of e-commerce against the backdrop of the Society 5.0 initiative that supports greater digitalization across the country. In terms of regulatory support, the AI Strategy 2025 encourages businesses to leverage AI tools to improve operations. By the end of 2037, it is forecasted that more than 70% of retailers in Japan will implement AI tools to personalize marketing. In terms of current deployment, the convenience store giant 7-11 has reported greater sales through the successful usage of AI for predictive stocking.
North America Market Forecast
The North America AI in retail market is expanding at a CAGR of 33.4% during the forecast period, registering the fastest expansion. The North America market’s accelerated expansion is supported by the surging adoption of natural language processing, machine learning, and AI-powered personalization technologies in the retail sector. Additionally, vendors find greater opportunities to deploy AI-powered software solutions for retail chains by leveraging the supportive regulatory system in the U.S. and Mexico.
The U.S. AI in retail market is poised to maintain a leading revenue share in North America. A major driver of the U.S. market is rising R&D on AI, through supportive initiatives such as the National AI Initiative Act of 2020. Additionally, the retail sector of the U.S. remains considerably strong with the presence of major retailers such as Walmart, Target, etc., are already embracing the use of AI to improve customer analytics and inventory management.
Companies Dominating the AI in Retail Market
- Company Overview
- Business Strategy
- Key Product Offerings
- Financial Performance
- Key Performance Indicators
- Risk Analysis
- Recent Development
- Regional Presence
- SWOT Analysis
The AI in retail market is poised to reach maturity by the end of 2037. The market is highly competitive due to the lucrative opportunities for deployment in retail chains across regional markets. Major players such as Microsoft, Google, and Amazon Web Services are leading the development of improved AI-powered software. The table below highlights the major players of the AI in retail market:
|
Company Name |
Country of Origin |
Revenue Share (2024) |
|
Amazon Web Services (AWS) |
USA |
25.7% |
|
Microsoft Corporation |
USA |
18.8% |
|
Google Cloud |
USA |
12.1% |
|
IBM Corporation |
USA |
8.7% |
|
Salesforce |
USA |
5.9% |
|
SAP SE |
Germany |
xx% |
|
Oracle Corporation |
USA |
xx% |
|
Alibaba Cloud |
China |
xx% |
|
Fujitsu |
Japan |
xx% |
|
Siemens AG |
Germany |
xx% |
|
Tata Consultancy Services (TCS) |
India |
xx% |
|
Accenture |
Ireland |
xx% |
|
Cognizant Technology Solutions |
USA |
xx% |
|
Samsung SDS |
South Korea |
xx% |
|
Axiata Digital Labs |
Malaysia |
xx% |
Below are the areas covered for each company in the AI in retail market:
Recent Developments
- In December 2024, AWS introduced a suite of generative AI tools for the retail industry. These tools are slated to bolster pricing strategies and improve inventory management for retail chains.
- In November 2024, Alibaba Cloud launched Quanzhantui, i.e., AI-powered marketing solutions aimed at SMEs. The tool leverages AI to bolster marketing efficiency.
Author Credits: Preeti Wani
- Report ID: 3516
- Published Date: Jun 09, 2025
- Report Format: PDF, PPT
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