AI In Retail - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
The AI In Retail Market size is estimated at USD 9.85 billion in 2024, and is expected to reach USD 40.49 billion by 2029, growing at a CAGR of 32.68% during the forecast period (2024-2029).
Artificial intelligence, a collection of algorithms harnessing vast and reliable data, is increasingly adopted in retail to personalize the shopping experience. By leveraging customer preferences, retailers can offer tailored product recommendations, elevating the customer experience and driving sales.
Key Highlights
Retail has witnessed a profound digital transformation, propelled by the integration of advanced data analytics and forecasting systems. This, bolstered by the convergence of artificial intelligence and the Internet of Things, has empowered retailers with sophisticated insights to optimize operations and identify lucrative business opportunities. Retailers are turning to AI-powered solutions to tackle challenges like evolving consumer behavior, labor constraints, supply chain disruptions, and escalating costs.
Recognizing the potential of AI to reduce costs and enhance operational efficiency, retailers are increasingly integrating it into their processes. This shift is reshaping customer service, with AI-powered chatbots revolutionizing interactions. During online purchases, chatbots can suggest products based on customers' preferences, including price range, features, and user reviews. By incorporating recommendation algorithms, retailers can boost sales while customers find products tailored to their preferences.
Moreover, retailers are forging deeper customer relationships, infusing digital elements into sales, support, merchandising, and finance operations. Beyond AI, technologies like IoT, automation, blockchain, and virtual reality are digitally disrupting the retail landscape. AI-equipped retailers leverage sharp forecasting tools for smarter decision-making while enhanced visual recognition and augmented reality redefine online shopping, enabling customers to experience products virtually.
The global retail sector is witnessing a surge in AI applications, with both tech giants and SMBs ramping up their efforts. Consequently, the demand for AI engineers has soared, but more experienced professionals are still needed in this field.
The COVID-19 pandemic has accelerated these trends, leaving retailers grappling to adapt. As consumer behavior tilts toward online, traditional retailers are grappling to bolster their technological capabilities. The pandemic has ushered in a customer-centric paradigm, and companies embracing digital transformation principles are fortifying their operations and reaping significant profits.
AI in Retail Market Trends
Software Segment to Witness Major Growth
Leading retailers are adopting AI software to offer personalized shopping experiences. By analyzing customer data and behavior, these retailers leverage AI algorithms to power advanced recommendation engines. These engines suggest products tailored to individual preferences, driving sales and boosting customer engagement.
As omnichannel retailing gains prominence, retailers are increasingly investing in AI software. This software helps integrate data from multiple channels, ensuring a seamless shopping experience across online, mobile, and brick-and-mortar stores. With AI-driven solutions, retailers can unify customer data, personalize marketing messages, and optimize inventory management across all channels.
AI software equips retailers with the ability to craft targeted marketing campaigns and personalized advertisements. By analyzing vast amounts of customer data, AI algorithms identify trends, preferences, and buying patterns. This enables retailers to tailor marketing messages and promotions, resulting in higher engagement and sales. Consequently, an increasing number of retailers are embracing AI-based software.
Asia-Pacific is witnessing a surge in demand for AI software, driven by rising e-commerce adoption and factors such as increasing internet penetration and smartphone usage. According to GSMA, Mobile Economy 2023, Asia-Pacific is expected to see its smartphone adoption rate increase to 94% by 2030, and digital payment options are fueling this growth. Retailers in the region are leveraging AI software to enhance the online shopping experience. This includes offering personalized product recommendations, optimizing pricing strategies, and streamlining order fulfillment processes.
North America to Hold Significant Market Share
The demand for artificial intelligence (AI) in the retail sector in North America is experiencing significant growth driven by various factors such as personalized shopping experiences, inventory management and optimization, supply chain optimization, and others.
Many retailers in this region have deployed AI-based solutions to optimize their supply chain operations and inventory. AI helps retailers manage and maintain customers and understand consumers' buying patterns. Also, AI technologies are being adopted by offline and online retail businesses to engage customers and improve sales turnover.
Many retailers in the United States and Canada are also adopting AI technologies, such as predictive analytics and machine learning, helping retailers optimize their supply chains. AI can identify inefficiencies, reduce lead times, and improve overall supply chain performance by analyzing data from suppliers, logistics providers, and other sources. Due to this, retailers are focusing on the adoption of such technologies.
Furthermore, many retail companies in the US leverage AI to analyze customer data and behavior to offer personalized shopping experiences. AI-powered recommendation engines may suggest products based on past purchases, browsing history, and demographic information, enhancing customer satisfaction and loyalty.
AI in Retail Industry Overview
Artificial intelligence in the retail market is fragmented. The growing adoption of IoT, e-commerce marketing, and big data analytics provides lucrative opportunities for artificial intelligence in the retail market. The competitive rivalry among existing competitors is high. Moreover, large companies such as SAP SE, Microsoft Corporation, IBM Corporation, Salesforce Inc., and Google LLC are expected to make acquisitions and collaborate with startups focused on innovation.
In March 2024, IBM announced the expansion of its technical expert laboratory capacity in India to ensure that businesses remain strong in a highly competitive environment. It focuses on helping clients take full advantage of artificial intelligence, hybrid cloud, and cyber security technologies.
In January 2024, Oracle announced the general availability of the Oracle Cloud Infrastructure (OCI) Generative AI service and innovations that make it easier for enterprises to take advantage of the latest advancements in generative AI. OCI Generative AI service is a fully managed service that seamlessly integrates large language models (LLMs) from Cohere and Meta Llama 2 to address various business use cases.
Additional Benefits:
The market estimate (ME) sheet in Excel format
3 months of analyst support
Artificial intelligence, a collection of algorithms harnessing vast and reliable data, is increasingly adopted in retail to personalize the shopping experience. By leveraging customer preferences, retailers can offer tailored product recommendations, elevating the customer experience and driving sales.
Key Highlights
Retail has witnessed a profound digital transformation, propelled by the integration of advanced data analytics and forecasting systems. This, bolstered by the convergence of artificial intelligence and the Internet of Things, has empowered retailers with sophisticated insights to optimize operations and identify lucrative business opportunities. Retailers are turning to AI-powered solutions to tackle challenges like evolving consumer behavior, labor constraints, supply chain disruptions, and escalating costs.
Recognizing the potential of AI to reduce costs and enhance operational efficiency, retailers are increasingly integrating it into their processes. This shift is reshaping customer service, with AI-powered chatbots revolutionizing interactions. During online purchases, chatbots can suggest products based on customers' preferences, including price range, features, and user reviews. By incorporating recommendation algorithms, retailers can boost sales while customers find products tailored to their preferences.
Moreover, retailers are forging deeper customer relationships, infusing digital elements into sales, support, merchandising, and finance operations. Beyond AI, technologies like IoT, automation, blockchain, and virtual reality are digitally disrupting the retail landscape. AI-equipped retailers leverage sharp forecasting tools for smarter decision-making while enhanced visual recognition and augmented reality redefine online shopping, enabling customers to experience products virtually.
The global retail sector is witnessing a surge in AI applications, with both tech giants and SMBs ramping up their efforts. Consequently, the demand for AI engineers has soared, but more experienced professionals are still needed in this field.
The COVID-19 pandemic has accelerated these trends, leaving retailers grappling to adapt. As consumer behavior tilts toward online, traditional retailers are grappling to bolster their technological capabilities. The pandemic has ushered in a customer-centric paradigm, and companies embracing digital transformation principles are fortifying their operations and reaping significant profits.
AI in Retail Market Trends
Software Segment to Witness Major Growth
Leading retailers are adopting AI software to offer personalized shopping experiences. By analyzing customer data and behavior, these retailers leverage AI algorithms to power advanced recommendation engines. These engines suggest products tailored to individual preferences, driving sales and boosting customer engagement.
As omnichannel retailing gains prominence, retailers are increasingly investing in AI software. This software helps integrate data from multiple channels, ensuring a seamless shopping experience across online, mobile, and brick-and-mortar stores. With AI-driven solutions, retailers can unify customer data, personalize marketing messages, and optimize inventory management across all channels.
AI software equips retailers with the ability to craft targeted marketing campaigns and personalized advertisements. By analyzing vast amounts of customer data, AI algorithms identify trends, preferences, and buying patterns. This enables retailers to tailor marketing messages and promotions, resulting in higher engagement and sales. Consequently, an increasing number of retailers are embracing AI-based software.
Asia-Pacific is witnessing a surge in demand for AI software, driven by rising e-commerce adoption and factors such as increasing internet penetration and smartphone usage. According to GSMA, Mobile Economy 2023, Asia-Pacific is expected to see its smartphone adoption rate increase to 94% by 2030, and digital payment options are fueling this growth. Retailers in the region are leveraging AI software to enhance the online shopping experience. This includes offering personalized product recommendations, optimizing pricing strategies, and streamlining order fulfillment processes.
North America to Hold Significant Market Share
The demand for artificial intelligence (AI) in the retail sector in North America is experiencing significant growth driven by various factors such as personalized shopping experiences, inventory management and optimization, supply chain optimization, and others.
Many retailers in this region have deployed AI-based solutions to optimize their supply chain operations and inventory. AI helps retailers manage and maintain customers and understand consumers' buying patterns. Also, AI technologies are being adopted by offline and online retail businesses to engage customers and improve sales turnover.
Many retailers in the United States and Canada are also adopting AI technologies, such as predictive analytics and machine learning, helping retailers optimize their supply chains. AI can identify inefficiencies, reduce lead times, and improve overall supply chain performance by analyzing data from suppliers, logistics providers, and other sources. Due to this, retailers are focusing on the adoption of such technologies.
Furthermore, many retail companies in the US leverage AI to analyze customer data and behavior to offer personalized shopping experiences. AI-powered recommendation engines may suggest products based on past purchases, browsing history, and demographic information, enhancing customer satisfaction and loyalty.
AI in Retail Industry Overview
Artificial intelligence in the retail market is fragmented. The growing adoption of IoT, e-commerce marketing, and big data analytics provides lucrative opportunities for artificial intelligence in the retail market. The competitive rivalry among existing competitors is high. Moreover, large companies such as SAP SE, Microsoft Corporation, IBM Corporation, Salesforce Inc., and Google LLC are expected to make acquisitions and collaborate with startups focused on innovation.
In March 2024, IBM announced the expansion of its technical expert laboratory capacity in India to ensure that businesses remain strong in a highly competitive environment. It focuses on helping clients take full advantage of artificial intelligence, hybrid cloud, and cyber security technologies.
In January 2024, Oracle announced the general availability of the Oracle Cloud Infrastructure (OCI) Generative AI service and innovations that make it easier for enterprises to take advantage of the latest advancements in generative AI. OCI Generative AI service is a fully managed service that seamlessly integrates large language models (LLMs) from Cohere and Meta Llama 2 to address various business use cases.
Additional Benefits:
The market estimate (ME) sheet in Excel format
3 months of analyst support
1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Stakeholder Analysis
4.3 Industry Attractiveness - Porter's Five Forces Analysis
4.3.1 Bargaining Power of Consumers
4.3.2 Bargaining Power of Suppliers
4.3.3 Threat of New Entrants
4.3.4 Threat of Substitute Products
4.3.5 Intensity of Competitive Rivalry
5 MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Rapid Adoption of Advances in Technology Across Retail Chain
5.1.2 Emerging Trend of Startups in the Retail Space
5.2 Market Restraints
5.2.1 Lack of Professionals as well as In-house Knowledge for Cultural Readiness
5.3 Impact of COVID-19 on the Market
6 KEY TECHNOLOGY INVESTMENTS
6.1 Cloud Technology
6.2 Artificial Intelligence
6.3 Cyber Security
6.4 Digital Services
7 MARKET SEGMENTATION
7.1 By Channel
7.1.1 Omnichannel
7.1.2 Brick and Mortar
7.1.3 Pure-play Online Retailers
7.2 By Component
7.2.1 Software
7.2.2 Service (Managed and Professional)
7.3 By Deployment
7.3.1 Cloud
7.3.2 On-premise
7.4 By Application
7.4.1 Supply Chain and Logistics
7.4.2 Product Optimization
7.4.3 In-Store Navigation
7.4.4 Payment and Pricing Analytics
7.4.5 Inventory Management
7.4.6 Customer Relationship Management (CRM)
7.5 By Technology
7.5.1 Machine Learning
7.5.2 Natural Language Processing
7.5.3 Chatbots
7.5.4 Image and Video Analytics
7.5.5 Swarm Intelligence
7.6 By Geography***
7.6.1 North America
7.6.2 Europe
7.6.3 Asia
7.6.4 Australia and New Zealand
7.6.5 Latin America
7.6.6 Middle East and Africa
8 COMPETITIVE LANDSCAPE
8.1 Company Profiles
8.1.1 SAP SE
8.1.2 IBM Corporation
8.1.3 Microsoft Corporation
8.1.4 Google LLC
8.1.5 Salesforce Inc.
8.1.6 Oracle Corporation
8.1.7 ViSenze Pte Ltd
8.1.8 Amazon Web Services Inc.
8.1.9 BloomReach Inc.
8.1.10 Symphony AI
8.1.11 Daisy Intelligence Corporation
8.1.12 Conversica Inc.
9 INVESTMENT ANALYSIS
10 MARKET OPPORTUNITIES AND FUTURE TRENDS
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Stakeholder Analysis
4.3 Industry Attractiveness - Porter's Five Forces Analysis
4.3.1 Bargaining Power of Consumers
4.3.2 Bargaining Power of Suppliers
4.3.3 Threat of New Entrants
4.3.4 Threat of Substitute Products
4.3.5 Intensity of Competitive Rivalry
5 MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Rapid Adoption of Advances in Technology Across Retail Chain
5.1.2 Emerging Trend of Startups in the Retail Space
5.2 Market Restraints
5.2.1 Lack of Professionals as well as In-house Knowledge for Cultural Readiness
5.3 Impact of COVID-19 on the Market
6 KEY TECHNOLOGY INVESTMENTS
6.1 Cloud Technology
6.2 Artificial Intelligence
6.3 Cyber Security
6.4 Digital Services
7 MARKET SEGMENTATION
7.1 By Channel
7.1.1 Omnichannel
7.1.2 Brick and Mortar
7.1.3 Pure-play Online Retailers
7.2 By Component
7.2.1 Software
7.2.2 Service (Managed and Professional)
7.3 By Deployment
7.3.1 Cloud
7.3.2 On-premise
7.4 By Application
7.4.1 Supply Chain and Logistics
7.4.2 Product Optimization
7.4.3 In-Store Navigation
7.4.4 Payment and Pricing Analytics
7.4.5 Inventory Management
7.4.6 Customer Relationship Management (CRM)
7.5 By Technology
7.5.1 Machine Learning
7.5.2 Natural Language Processing
7.5.3 Chatbots
7.5.4 Image and Video Analytics
7.5.5 Swarm Intelligence
7.6 By Geography***
7.6.1 North America
7.6.2 Europe
7.6.3 Asia
7.6.4 Australia and New Zealand
7.6.5 Latin America
7.6.6 Middle East and Africa
8 COMPETITIVE LANDSCAPE
8.1 Company Profiles
8.1.1 SAP SE
8.1.2 IBM Corporation
8.1.3 Microsoft Corporation
8.1.4 Google LLC
8.1.5 Salesforce Inc.
8.1.6 Oracle Corporation
8.1.7 ViSenze Pte Ltd
8.1.8 Amazon Web Services Inc.
8.1.9 BloomReach Inc.
8.1.10 Symphony AI
8.1.11 Daisy Intelligence Corporation
8.1.12 Conversica Inc.
9 INVESTMENT ANALYSIS
10 MARKET OPPORTUNITIES AND FUTURE TRENDS
