What is the present valuation and projected CAGR of the artificial intelligence (ai) in retail market?
The artificial intelligence (AI) in retail market size has grown exponentially in recent years. It will grow from $11.9 billion in 2024 to $15.51 billion in 2025 at a compound annual growth rate (CAGR) of 30.3%. The growth in the historic period can be attributed to growth of AI in retail, increased necessity for surveillance and monitoring, rapid implementation of AI solutions, advancements in computer vision, growing demand for efficient operations.
The artificial intelligence (AI) in retail market size is expected to see exponential growth in the next few years. It will grow to $44.43 billion in 2029 at a compound annual growth rate (CAGR) of 30.1%. The growth in the forecast period can be attributed to projected market growth, AI’s transformative power, demand-side trends, favorable global market outlook, increasing competition. Major trends in the forecast period include adoption of machine learning, growing demand for ai services, enhanced user experience and productivity, regional market expansion.
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What key drivers have fueled the artificial intelligence (ai) in retail market’s development over the years?
The digital transformation in the retail industry is expected to propel the growth of artificial intelligence (AI) in the retail market going forward. Digital transformation refers to the comprehensive and strategic integration of digital technologies, processes, and capabilities across various aspects of an organization. Retailers globally are adopting digital processes and enhancing customer experiences, resulting in an increased demand for AI solutions. This integration of AI in retail, driven by the imperative of digital transformation, fosters innovation in tasks such as automation, personalized marketing, and trend prediction, improving operational efficiency and providing insights into customer behavior. For instance, in January 2024, according to a survey of 400 respondents conducted by NVIDIA Corporation, a US-based manufacturing and technology company, 69% of retailers reported increased annual revenue with AI adoption, 72% experienced lower operating costs, and over 60% plan to boost AI investments in the next 18 months. Therefore, the digital transformation in the retail industry is driving the growth of artificial intelligence (AI) in the retail market.
What is the segmentation for the artificial intelligence (ai) in retail market?
The artificial intelligence (AI) in retail market covered in this report is segmented –
1) By Component: Solution, Service
2) By Technology: Machine Learning, Natural Language Processing, Chatbots, Image And Video Analytics, Swarm Intelligence
3) By Deployment: Cloud, On-Premise
4) By Channel: Omnichannel, Brick And Mortar, Pure-Play Online Retailers
5) By Application: Customer Relationship Management, Supply Chain And Logistics In-Store, Navigation Inventory Management, Product Optimization, Payment And Pricing Analytics
Subsegments:
1) By Solution: Predictive Analytics, Customer Relationship Management (CRM), Inventory Management, Visual Search, Personalization Engines, Fraud Detection
2) By Service: Consulting Services, Implementation Services, Support And Maintenance, Managed Services
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Who are the most influential companies in the artificial intelligence (ai) in retail market?
Major companies operating in the artificial intelligence (AI) in retail market are Google LLC, Microsoft Corporation, Amazon Web Services, Intel Corporation, International Business Machines Corporation, Oracle Corporation, SAP SE, Presto, NVIDIA Corporation, Salesforce Inc., Baidu Inc., ViSenze, Travelport, Databricks, DATAIKU, Symbotic, BloomReach Inc., Trax, Interactions LLC, Featurespace, RetailNext Inc., Trigo, Standard Cognition, CognitiveScale Inc., BrainBox AI, Inbenta Technologies, Next IT Corp., Infinite Analytics, Lexalytics Inc., Sentient Technologies
What are the top industry trends projected to impact the artificial intelligence (ai) in retail market?
Major companies operating in the artificial intelligence (AI) retail market are developing advanced technologies, such as cloud-based solutions, to drive innovation and enhance efficiency in the retail sector. Cloud-based solutions refer to computing services, including storage, processing, and software applications, that are delivered over the internet (cloud) instead of relying on local servers or traditional computing infrastructure. For instance, in October 2023, Flipkart Private Limited, an India-based e-commerce company, launched Flipkart Commerce Cloud, which aims to help retailers across the world grow their businesses and solve business needs through intelligent and AI-driven solutions. This platform offers retail technology solutions for international retailers, marketplaces, and e-commerce platforms. The suite of solutions includes a complete marketplace technology stack, retail media solution, pricing solution, inventory management, and forecasting solutions, all built using artificial intelligence and machine learning
What are the major regional insights for the artificial intelligence (ai) in retail market, and which region holds the top position?
North America was the largest region in the artificial intelligence (AI) in retail market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI) in retail market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Does The Artificial Intelligence (AI) In Retail Market Report 2025 Offer?
The artificial intelligence (ai) in retail market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
Artificial intelligence (AI) in retail refers to the application of advanced computing technologies that simulate human intelligence to enhance and automate various aspects of the retail industry. This includes leveraging AI algorithms and machine learning techniques to analyze vast amounts of data, predict consumer behavior, optimize inventory management, personalize customer experiences, and streamline operational processes.
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