Artificial Intelligence (AI) in Retail Market (By Technology: Machine Learning and Deep Learning, Natural Language Processing, Others (Analytics and Process Automation); By Deployment Model: Cloud, On-Premises; By Application: Predictive Merchandising, Programmatic Advertising, In-Store, Visual Monitoring and Surveillance, Location-Based Marketing, Other) – Global Industry Analysis, Market Size, Opportunities and Forecast, 2020-2027

The global artificial intelligence (AI) in retail market is expected to grow at a CAGR of around 34.9% from 2020 to 2027 and projected to reach the market value of around US$ 6,762.3 Mn by 2027.

Artificial intelligence (AI) in retail systems enhances working together to optimize customer experiences, forecasting, inventory management, and others. AI technology like computer vision brings near-real-time intelligence and data. This can be analyzed in the cloud and can provide additional business insights and platforms.

COVID-19 impact on AI retail markets

COVID-19 pandemic has accelerated demand for AI-based retail analytics. As the world crippled with COVID-19, technological innovations harnessed to fight this pandemic. Artificial intelligence and machine learning played a pivotal role in better understanding the COVID-19 crisis. According to the World Economic Forum, during the pandemic disruption in the food supply chain, food processors, and the government was highly witnessed. To address such a situation agri-tech startup Mantle Labs, Amazon Web Services (AWS) customer offered the cutting edge AI-driven crop monitoring solution to retailers free of charge for a duration of three months. This enhanced additional resilience and certainty to supply chains in the UK. Additionally, there are lucrative opportunities in inventory and warehouse management in the supply chain that leverage AI.

AI is also applied in other parts of supply chain like procurement. Through leveraging AI coupled with exponential technologies like block chain and IoT companies in the manufacturing industries expected to gain robust pace in the forthcoming years through the adoption of new supply chain models. Decentralizing supply chain by using technologies like block chain organizations can dramatically improve the visibility of end-to-end supply chain and resist contingency in novel coronavirus pandemic. The COVID-19 outbreak enforced a strict lockdown globally. This lockdown enforced the temporary shutdown of many retailers across the globe. E-commerce became the more popular platform for shopping during the pandemic. The retail companies integrated AI technology into their shopping models to improve the customer experience during the COVID-19 outbreak.

Merchandizing with Artificial Intelligence (AI) in Retails

Global retail spending on IT has gained massive growth that is considered as a shift to modernize technology. Global retail spending on IT has topped US$ 196 Bn in 2019 and is predicted to grow over US$ 225 Bn by the end of 2022. The drive for such robust growth involves prominent factors such as paradigm shift of retailers investing in hardware and software across the operations resulting in new ways of doing business. Such rapid changes and pressures on the industry have created lucrative opportunities to enter new markets.

Cross-channel fulfillment with AI

Through the combination of data from multiple channels with a strong base of machine learning, merchants can better understand the complex relationship between customers and products. It provides the platform to optimize inventory situations. It helps to eliminate stock-outs and reduce lead times to get products to customers. For instance, a company dependant on AI is a leading German sportswear manufacturer and retailer. Through the integration of machine learning algorithms, it optimizes inventory levels and Omni-channels fulfillment across online, third-party retailers, and private in-store businesses.

Market Drivers

Improvement of inventory through AI

By integration of AI in inventory management, it eliminates the inefficiencies in the current processes by enabling a predictive approach and reducing errors by automating operations. Through incorporating AI robots it proves as a powerful asset in warehouses. The robots are equipped with other advanced technologies such as smart sensors and computer vision to identify the shortest path, detect obstacles, and label items with the highest accuracy. As AI helps to balance demand and supply, products can be delivered faster to a consumer base. AI can also be used in logistics such as autonomous vehicles for delivery and carrying out backend repetitive tasks such as data entry and Robotic Process Automation (RPA) tools. Thus, AI has the capability to provide an end-to-end automation solution, specifically for e-commerce players.

AI chatbots to assist with customer service

Artificial intelligence solutions in retail can effortlessly improve customer engagement by building interactive chat programs. Chatbots act as an effective way to communicate with customers. The chatbots are programmed to self-learn from past data to keep refining and personalizing their subsequent interactions with the customers. The accuracy with the AI-powered chatbots handles data and customers through human intelligence. Additionally, the AI configured chatbots without engaging the human workforce. The quick, personalized, and on-demand support and suggestion provide by AI-driven chatbots augments customer's experience thus fostering the AI driven retail industry growth.

Segmental Analysis

Artificial intelligence (AI) in retail markets is segmented based on technology, deployment model, and application. By technology, the AI retail market is segmented as machine learning, natural language processing, and among others. By deployment model, the AI in the retail market is bifurcated into cloud and on-premise. Furthermore, by application, the market is segmented as predictive merchandising, programmatic advertising, in-store visual monitoring and surveillance, location-based marketing, and others.
Based on the technology, natural language processing segment is anticipated to dominate the overall artificial intelligence (AI) in retail markets globally. Furthermore, by deployment model, cloud segment will dominate the market of artificial intelligence (AI) in retail markets worldwide. Based on application, predictive merchandising will bolster the segmental growth for the growth of artificial intelligence (AI) in retail markets globally.

Regional Overview

North America is anticipated to dominate the overall regional market by recording largest market share. This is supported due to presence of several developed economies involving US and Canada and focusing on enhancement of existing solutions in retail space. Additionally, North America hosts the primary AI solution providers and is early adopter of AI technology. Additionally, presence of large pool of US based companies like NVIDIA Corporation, Intel Corporation, Salesforce, Sentient Technologies, Microsoft Corporation, Google Inc., IBM Corporation, Amazon Web Services and others are extensively involving themselves in the product innovation and optimization. This acts as a stimulating factor for the growth of AI in retail markets. 

On the other hand, Asia Pacific is expected to be the fastest growing regional market for AI in retail market. Development of internet and connectivity infrastructure, rising adoption of AI-based solutions & services among retailers, and surging digitization are the factors that act positively on the regional market to grow fully for AI in the retail market in APAC region.

Competitive Landscape

Key players operating in the artificial intelligence (AI) in retail markets involve International Business Machines Corporation (IBM), Microsoft Corporation, Amazon Web Services, Oracle Corporation, SAP SE, Intel Corporation, NVIDIA Corporation, Google LLC, Sentient Technologies, and among others

Market Segmentation

Market By Technology

Machine Learning and Deep Learning
Natural Language Processing
Others (Analytics and Process Automation)

Market By Deployment Model

Cloud
On-Premises

Market By Application

Predictive Merchandising
Programmatic Advertising
In-Store Visual Monitoring and Surveillance
Location-Based Marketing
Other

Market By Geography

North America

• U.S.
• Canada

Europe

• U.K.
• Germany
• France
• Spain
• Rest of Europe

Asia-Pacific

• China
• Japan
• India
• Australia
• South Korea
• Rest of Asia-Pacific

Latin America

• Brazil
• Mexico
• Rest of Latin America

Middle East & Africa

• GCC
• South Africa
• Rest of Middle East & Africa