The Global Artificial Intelligence (AI) In Retail Market Size Accounted For USD 8.41 Billion In 2022 And It Is Projected To Attain Around USD 45.74 Billion By 2030, Poised To Grow At A CAGR Of 18.45% During The Forecast Period 2023 To 2030.

Artificial Intelligence in Retail Market Overview

The growth is being driven by things like the growing number of people who use the internet, smart devices, the need for surveillance and monitoring at a physical store, and government policies that encourage digitization. AI in retail is based on how businesses have been run over the past few decades. AI and big data analytics are important parts of digital business. They can change everything from the customer experience to how a business works.

Big data analytics and AI are being used more and more in the retail industry because technology is getting better, there are more apps and smart devices, more people are using cloud services, and the Internet of Things (IoT) is becoming more popular. For example, in February 2020, Baker Hughes, an oil field services company, teamed up with C3.ai and announced the release of an AI-based app called BH3 Production optimization. This app lets operators see real-time production statistics, optimise operations, and better predict future production to increase gas and oil production rates.

In the retail industry, AI is helping companies make decisions faster in product management, marketing, e-commerce, and other business areas by shortening the time between having an idea and putting it into action. For example, in June 2021, Talkdesk, Inc. released Talkdesk Retail Smart Service, which is based on artificial intelligence (AI). This service gives customers automated self-services so that support agents can focus on other major tasks that bring in more money. These services help consumers by giving them personalised suggestions and better ways to connect.

Also, chatbots that use artificial intelligence to help customers are becoming more popular in the retail industry because they are so good at serving customers. This chatbot gives customers answers that are specific to them and personalised, which makes customers happier. Computer vision and other technological advances in the retail sector are becoming more popular in stores. Computer vision is a type of deep learning AI that interprets and "sees" visual data. It is used in retail. This new development gives new retail the chance to improve inventory management, demand forecasting, customer service, and other areas.

For example, Intel Corporation, ASUSTeK Computer Inc., and Microsoft Corporation worked together in June 2022 to release AI DevKit, the first AI on PC Development Kit in the world. Deep neural networks and computer vision applications for the PC are used to make the AI on PC Development Kit. Integration of software and hardware, along with tutorials and source code that help people make interesting AI apps and make it possible for new apps to be made.

Market Dynamics

LATEST TRENDS

The number of people using e-commerce sites and virtual shops is growing quickly. Today, people can search for new products in new ways, such as by using images, videos, and their voices. Visual search uses artificial intelligence to make the most of its features by processing queries and mining the metadata. AI is used by the visual search engine to analyse, track, and predict growing shopping trends, which improves the shopping experience and keeps shoppers interested.

Syte Visual Conception Ltd.'s 2020 report says that almost 80% of shoppers have started their shopping with a visual search. So, AI-based search engines are now a must-have for retailers who want to improve customer service and increase sales. Also, search features that are powered by AI help retailers learn important things about consumer trends and make good business decisions. AI-powered search engines are expected to give retailers a lot of data and growth opportunities in the coming years.

DRIVING FACTORS

Chatbots powered by artificial intelligence are becoming very popular in the retail industry because they are so good at helping customers. Chatbot gives customers answers that are specific and tailored to them to improve their experience. In 2018, 91% of customers were more interested in shopping for brands that offered personalised recommendations and services, according to Accenture insights.

Natural language processing (NLP) and machine learning (ML) are used to help the AI chatbots understand what people say. These technologies give real-time information about what customers want. It also helps the chatbot understand how customers feel and how they act, which helps the chatbot answer customer questions and build relationships. For example, Levis has a platform called Levi's Virtual Stylist that is a chatbot that makes suggestions to the customer. For quick suggestions, the bot asks users for basic information like size, fit, material, and even preferred brands. So, the AI-powered chatbot is expected to make AI more popular in the retail industry.

RESTRAINING FACTORS

Well-known retail brands keep investing in new technologies to improve customer engagement. However, the growth of the Artificial Intelligence in retail market is likely to be limited by a number of factors. Artificial intelligence has already been used by large businesses and global retailers like Walmart to run their stores and manage their online portals. But today, it's hard for small and medium-sized businesses to use the technology because they don't have the right infrastructure or technical know-how. IBM's cloud-data service insights show that 37% of respondents said they couldn't use AI because they didn't know enough about it. The high cost of putting the intelligent retail solution into place is also a big problem for small retailers, which slows down the process. These things are likely to stop the market from growing.

Segment Overview

By Offering Analysis

Increasing Automation in Retail Industry to Fuel AI-based Solution Segment

The artificial intelligence in retail sector is divided into solutions and services based on what is being offered. The remedy is ruling the marketplace. Smart shop, digital commerce, intelligent consumer insights, smart delivery, intelligent supply chain, and other solutions are taken into consideration. The retail business is anticipated to be driven by new and inventive automated solutions due to the increasing difficulties in managing diverse retail activities. Retailers may manage logistics, supply chain operations, warehouse management, and enhanced consumer experiences with the use of the AI-based retail solution. This is anticipated to accelerate the use of AI in the retail industry.

The predicted period is expected to see strong growth in the service sector. The vendor must provide the merchants with additional assistance with regard to particular services like installation, management, maintenance, and more. As a result, the demand for services is being driven by the quick adoption of AI technologies.

By Function Analysis

Growing Demand for Efficient Operations to Boost Operations-focused Segment

Artificial intelligence in the retail sector is divided into two categories based on function: operations-focused and customer-facing. Focus on operations increases market revenue share. Intel Movidius VPUs, Taskdesk Virtual Agents, RetailNext Store Layout, and ViSenze merchandising planning are the operation-focused solutions under consideration. In order to increase the effectiveness of their operations—including merchandising, logistics, supply chains, on-time delivery, and other areas—retailers are integrating AI. Effective backend administration gives merchants more time to concentrate on revenue growth and fresh growth initiatives.

Due to the rising demand for a solution to enhance the customer experience, customer-facing is predicted to develop quickly during the forecasted period. Retailers are implementing AI-driven solutions to decrease consumer complaints and increase brand loyalty.

By Application Analysis

Rapid Changing Customer Behaviour to Drive Predictive Analytics Segment

Predictive analytics, in-store visual monitoring and surveillance, customer relationship management (CRM), market forecasting, inventory management, and others are some of the applications that make up the market. Predictive analytics led this market in 2020, and some of its most important applications are labour optimization, shelf management, store operations, and demographic segmentation. To better comprehend potential future market prospects and consumer behaviour, retailers are employing AI-based predictive analysis. The AI is also used to obtain analysis based on many demographics, like region, country, culture, gender, age, and others.

A growing need for enhanced client involvement will lead to substantial growth for customer relationship management. Retailers can retain solid client relationships and loyalty with the aid of AI-driven virtual assistance, chatbots, search engines, and other tools. Due to the erratic and quick changes in consumer purchasing behaviour, there is an increasing demand for AI in market forecasting. The use of AI for in-store visual monitoring and surveillance is also anticipated to rise steadily. The ongoing monitoring provides strong security and gathers information about customers, alerts for shelf replenishment, controls for fraud and shrinkage, face recognition, and more.

By Type Analysis

Increasing Virtual and Online Shopping to Fuel Online Segment’s Growth

Artificial intelligence (AI) in the retail sector is divided into online and offline categories based on type. The highest revenue share is generated offline, and it is anticipated that this trend would continue during the projected period. The ability of the technology to manage in-store operations, improve merchandising and assortment, and automate personalised product recommendations, among other things, to improve customer shopping experiences, is driving up demand for it. Online is anticipated to rise quickly due to an increase in virtual and online shopping. Retailers are using artificial intelligence technology to enhance their online customer service capabilities. ViSenze, for instance, provides a variety of intelligent e-commerce solutions, including cross-device usability, astute recommendations, discovery, and motivational SEO marketing.

By Technology Analysis

Highly Accurate Customer Insights to Boost Natural Language Processing Segment

Computing technologies such as computer vision, machine learning, natural language processing, and others are used to categorise artificial intelligence in the retail sector. Throughout the projection period, natural language processing is anticipated to have rapid growth. In order to offer specialised and individualised services, businesses pay close attention to client behaviour, emotions, personality type, and other factors.

The segment's revenue share is most likely to be dominated by machine learning. Machine learning is useful in delivering individualised experiences to its clients and provides quick deep insights from the gathered data. It aids merchants in streamlining supply chain plans and demand projections to increase inventory productivity. Amazon Inc., for instance. Machine learning models can be deployed via Amazon Sage Maker, a fully managed service, for any application, from customer experience to predictive analytics. Similar to this, the use of computer vision in the retail sector is rapidly growing. In order to collect data from facial recognition and video searches, AI-based computer vision is being used.

Regional Analysis

In 2021, North America had the majority with a 38.5% revenue share. Given the significant expenditures being made in AI projects and related research and development initiatives, there are many potential for industry expansion. Regional retail suppliers are also focusing on extracting the available data on consumer preferences to increase the effectiveness of their customer care.

The market leaders use both organic and inorganic techniques, including Google Inc., Microsoft, IBM Corporation, Salesforce, and Amazon Web Services. For instance, Google Cloud launched Product Discovery Solutions for retail in January 2021 to promote individualised online buying.

From 2022 to 2030, Asia Pacific is anticipated to have the fastest CAGR, at 31.6%. The region's growth is a result of technical development in nations like China, Japan, and India. The main drivers of the growth of the Asia Pacific AI in retail market are the quick uptake of smart devices and the broad application of 5G technology in the retail industry.

Scope Analysis:

Recent Developments

• In September 2022, Microsoft partnered with Indian global IT company Infosys. The organizations wanted to enable companies to quickly redesign customer experiences, augment systems with cloud and data, and update processes through this alliance.
• In August 2022, the company introduced a new solution for personalized e-commerce product suggestions called ViSenze's Session-Based Recommendations. With the new approach, customers would get a more personalized experience without providing any personal information.
• In July 2022, Intel released novel reference kits. The new solution should make it easier for data scientists and engineers to understand how AI can be implemented in diverse environments, including manufacturing, retail, healthcare, and more.
• In July 2022, Askdata, a search-driven analytics company, was acquired by SAP. The company's post-acquisition goal was to improve its ability to help businesses make informed decisions through AI-powered natural language searches.
• In June 2022, Google and retail store H&M entered into a partnership. Through this partnership, the company intended to design and create an enterprise data backbone, including cutting-edge AI and ML capabilities, a core data platform and data products.
• In June 2022, Oracle and retail operator Komax collaborated. As a result of this partnership, Oracle would provide Komax with access to its suite of retail services via its cloud infrastructure to help the company launch the latest apparel, accessories and footwear from various well-known brands to customers across Latin America.
• In June 2022, NVIDIA and German multinational Siemens established a collaboration. The companies hoped to combine Siemens Xcelerator and NVIDIA Omniverse through this alliance to provide an industrial metaverse in addition to physics-based digital models.
• In April 2022, SAP and Kyndryl, a well-known provider of IT infrastructure services, merged. Through this agreement, the companies plan to focus on delivering best-in-class solutions to customers' most demanding digital business transformation concerns.
• In March 2022, Microsoft acquired Nuance Communications, an American multinational company that develops computer software. The company's goal following this acquisition was to integrate Nuance's industry-leading conversational AI and ambient intelligence into its respected and secure cloud products for the industry.
• In January 2022, Federos, a provider of IT consulting and services, was bought by Oracle. With network analytics, assurance, ad-automated orchestration, and AI-enhanced services, this acquisition aims to empower service providers.

Market Segmentation

This portion of the study on the Artificial Intelligence in Retail Market gives detailed data on the segments at the country and regional level, thereby aiding the strategist in determining the target demographics for the relevant product or service and the impending opportunities.

By Offering

• Solution
• Service

By Function

• Operations-Focused
• Customer-Facing
• Other

By Type

• Offline
• Online
• Other

By Application

• Predictive Analytics
• In-Store Visual Monitoring and Surveillance
• Customer Relationship Management (CRM)
• Market Forecasting
• Inventory Management
• Others

By Technology

• Computer Vision
• Machine Learning
• Natural Language Processing
• Other

By Companies

• IBM Corporation
• Microsoft
• SAP SE
• Amazon Web Services
• Oracle
• Salesforce Inc.
• Intel
• NVIDIA
• Google LLC
• Sentient Technology
• ViSenze