Artificial Intelligence (AI) in Retail

Global Artificial Intelligence (AI) in Retail Market to Reach US$80.6 Billion by 2030

The global market for Artificial Intelligence (AI) in Retail estimated at US$18.8 Billion in the year 2024, is expected to reach US$80.6 Billion by 2030, growing at a CAGR of 27.4% over the analysis period 2024-2030. Machine Learning, one of the segments analyzed in the report, is expected to record a 27.7% CAGR and reach US$35.2 Billion by the end of the analysis period. Growth in the Natural Language Processing segment is estimated at 28.5% CAGR over the analysis period.

The U.S. Market is Estimated at US$5.6 Billion While China is Forecast to Grow at 26.4% CAGR

The Artificial Intelligence (AI) in Retail market in the U.S. is estimated at US$5.6 Billion in the year 2024. China, the world`s second largest economy, is forecast to reach a projected market size of US$12.1 Billion by the year 2030 trailing a CAGR of 26.4% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 24.2% and 23.2% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 18.8% CAGR.

Global Artificial Intelligence (AI) in Retail Market - Key Trends and Drivers Summarized

How Is AI Personalizing the Shopping Experience in Retail?

Artificial Intelligence (AI) is transforming the retail landscape by offering personalized shopping experiences that cater to individual customer preferences, significantly enhancing engagement and satisfaction. Traditionally, retailers segmented customers based on basic demographic data, but AI now enables a much deeper level of personalization by analyzing extensive data on browsing habits, purchase history, and real-time behavior. For example, machine learning algorithms can identify patterns in a customer’s shopping journey and recommend products that align with their tastes, making the experience feel tailored and relevant. E-commerce giants like Amazon and fashion retailers like ASOS utilize AI-driven recommendation engines to offer curated product suggestions, while brick-and-mortar stores are increasingly adopting in-store personalization technologies. Through AI-powered apps and loyalty programs, physical stores can recognize customers as they enter, offering personalized promotions and real-time product suggestions. This level of personalization increases conversion rates, builds customer loyalty, and encourages repeat visits, marking a significant shift in how retailers engage with shoppers and stay competitive in a crowded market.

Can AI Enhance Inventory Management and Demand Forecasting in Retail?

AI is revolutionizing inventory management and demand forecasting in retail, optimizing stock levels and improving operational efficiency across the supply chain. In the past, inventory decisions were often based on historical sales data and estimations, which could lead to overstocking, stockouts, and inefficiencies. Today, AI-driven forecasting models use real-time data and predictive analytics to anticipate demand with remarkable accuracy, factoring in variables like seasonal trends, economic indicators, and even social media sentiment. This proactive approach allows retailers to adjust stock levels based on anticipated demand shifts, ensuring that popular items are always available while minimizing excess inventory. Retailers like Walmart and Zara employ AI algorithms to monitor sales patterns and automatically adjust inventory distribution across regions, stores, and online platforms. Additionally, AI helps streamline supply chains by predicting disruptions, optimizing order quantities, and coordinating logistics in real time. By integrating AI into inventory management and demand forecasting, retailers can significantly reduce waste, improve profitability, and enhance the customer experience by ensuring that products are available exactly when and where they’re needed.

How Is AI Enhancing Customer Service and Engagement in Retail?

AI is reshaping customer service in retail by automating interactions and providing around-the-clock support, improving customer satisfaction and fostering deeper engagement. AI-powered chatbots and virtual assistants are widely used across online retail platforms to assist customers with product recommendations, answer common questions, and manage returns and exchanges, all in real time. These chatbots use natural language processing (NLP) to understand customer inquiries and provide personalized responses, simulating a human-like interaction. Retailers like Sephora and H&M use chatbots to offer product recommendations, answer queries about stock availability, and assist with purchase decisions, creating a seamless shopping experience that meets customer expectations. In addition, AI in customer service allows retailers to track engagement across multiple touchpoints, from websites and mobile apps to social media, offering insights into customer preferences and improving future interactions. Through sentiment analysis, AI can gauge customer satisfaction and proactively address concerns, enhancing brand loyalty. By integrating AI into customer service, retailers can offer efficient, personalized support that builds customer relationships and boosts overall brand engagement.

What Factors Are Driving the Growth of AI in the Retail Sector?

The growth of AI in the retail sector is driven by several factors, including technological advancements, shifting consumer expectations, and the need for efficient, data-driven decision-making. With the rise of e-commerce and digital shopping platforms, the volume of customer data generated is growing exponentially, creating a strong demand for AI solutions capable of analyzing and leveraging this data to inform marketing strategies, inventory decisions, and customer engagement. Consumers increasingly expect personalized, seamless shopping experiences across channels, which has prompted retailers to adopt AI-driven tools that enhance customization and improve the overall shopping journey. Additionally, supply chain optimization has become a priority, especially after the pandemic, leading to the integration of AI to predict demand, streamline logistics, and manage inventory more effectively. Advances in machine learning, computer vision, and NLP are expanding AI applications in areas like recommendation engines, automated checkout, and virtual shopping assistants, which are reshaping customer expectations around convenience and service. Partnerships between retail and tech companies are further accelerating AI innovation in retail, providing tailored solutions that meet the sector`s unique demands. Collectively, these drivers underscore the transformative impact of AI in retail, positioning it as a critical asset for enhancing efficiency, customer satisfaction, and competitive advantage in an increasingly digital market.

SCOPE OF STUDY:

The report analyzes the Artificial Intelligence (AI) in Retail market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
Technology (Machine Learning, Natural Language Processing, Computer Vision, Other Technologies); Type (Offline, Online); Deployment (Cloud, On-Premise)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 91 Featured) -

• Amazon Web Services
• Bloomreach, Inc.
• Google LLC
• IBM Corporation
• intel Corporation
• Microsoft Corporation
• NVidia Corporation
• Oracle Corporation
• Salesforce.Com, Inc.
• SAP SE
• Sentient technologies
• ViSenze

TARIFF IMPACT FACTOR

Our new release incorporates impact of tariffs CBob geographical markets as we predict a shift in competitiveness of companies based on HQ country, manufacturing base, exports and imports (finished goods and OEM). This intricate and multifaceted market reality will impact competitors by artificially increasing the COGS, reducing profitability, reconfiguring supply chains, amongst other micro and macro market dynamics.

We are diligently following expert opinions of leading Chief Economists (14,949), Think Tanks (62), Trade & Industry bodies (171) worldwide, as they assess impact and address new market realities for their ecosystems. Experts and economists from every major country are tracked for their opinions on tariffs and how they will impact their countries.

We expect this chaos to play out over the next 2-3 months and a new world order is established with more clarity. We are tracking these developments on a real time basis.

As we release this report, U.S. Trade Representatives are pushing their counterparts in 183 countries for an early closure to bilateral tariff negotiations. Most of the major trading partners also have initiated trade agreements with other key trading nations, outside of those in the works with the United States. We are tracking such secondary fallouts as supply chains shift.

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APRIL 2025: NEGOTIATION PHASE

Our April release addresses the impact of tariffs on the overall global market and presents market adjustments by geography. Our trajectories are based on historic data and evolving market impacting factors.

JULY 2025 FINAL TARIFF RESET

Complimentary Update: Our clients will also receive a complimentary update in July after a final reset is announced between nations. The final updated version incorporates clearly defined Tariff Impact Analyses.

Reciprocal and Bilateral Trade & Tariff Impact Analyses:

USA
CHINA
MEXICO
CANADA
EU
JAPAN
INDIA
176 OTHER COUNTRIES.

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