Artificial Intelligence AI in Retail Market Size & Share 2022-27

Asia Pacific is expected to witness the fastest CAGR of 31.6% from 2022 to 2030. The region’s expansion can be attributed to technological advancements in countries such as China, Japan, and India. The rapid adoption of smart devices, and the widespread use of 5G technology in the retail sector, are the primary factors driving the growth of Asia Pacific AI in retail market.

These are the powerful engineers of several new innovations benefitting the retail industry. Some are mature companies, and others are part of the NVIDIA Inception program, NVIDIA’s startup incubator, where they’ve developed game-changing, GPU-based AI tools for retail. Explore who’s at the forefront of the fourth Industrial Revolution, powering new capabilities for intelligent stores, warehouse logistics, and omnichannel management. In August 2020, Mastercard has announced a new suite of frictionless solutions for retailers for their physical shopping experience.

Sales Channel Insights

Intel technologies may require enabled hardware, software or service activation. // Intel is committed to respecting human rights and avoiding complicity in human rights abuses. Intel’s products and software are intended only to be used in applications that do not cause or contribute to a violation of an internationally recognized human right. With AI, you put your store in a better position to make smarter decisions, boost sales, and ultimately enhance customer retention. So, now couldn’t be a better time to begin implementing AI in your daily functions.

Powered with AI technology, businesses became able to enhance customer experience tremendously. Already mentioned smart chatbots and voice assistants powered with natural language processing algorithms are the trend’s real-life embodiment. AI in retail is used to improve demand forecasting, generate optimal prices, improve customer experience, enhance inventory and supply chain management. According to Juniper Research, retailers will spend $7.3 billion on AI by 2022, compared with $2 billion spent in 2018. What it means is that AI solutions implementation becomes a general trend rather than a unique capability available for market giants only. It’s about converting data into insights, which inform actions that drive better business outcomes.

What is the study period of this market?

These days people simultaneously occupy physical and online worlds, so they expect businesses, including retailers, to consider their lifestyle habits and provide omnichannel experience with a personal touch. “Customers are looking for a complete omnichannel experience,” notes Katie Boschele of Lucidworks. “As AI is growing in the retail sector, you are going to see a trend in customers wanting their experience to move from online to mobile apps, to in-store, and to be mapped to their personal preferences. For example, an AI-powered experience should allow me to browse online, check prices on the app, and then go to a store, buy or be shown similar items to my online experiences in one seamless transaction. Customers want their retailers to know them and the items they would like to purchase,” concludes Katie. Services are likely to record immense growth throughout the forecast period.

Both on the stores’ websites or integrated into retailers’ mobile apps, chatbots of different complexity help users to make purchases quickly and easily with no need for managers to get involved every time. The retail industry has already witnessed the power of AI through in-store robots. The impact of artificial intelligence in retail in the future of retail business cannot be imaginable.

Using retail AI to predict consumer sentiment

The opportunities for industry expansion as significant investments are being made in AI projects and related research and development activities. The global artificial intelligence in retail market is expected to grow at a compound annual growth rate of 23.9% from 2022 to 2030 to reach USD 40.74 billion by 2030. The virtual assistance segment is anticipated to witness the fastest CAGR of 25.1% from 2022 to 2030, coming on the heels of the high penetration of smartphones and other advanced tools. The retail sector has explored opportunities in virtual assistant technologies to streamline the supply chain, including invoicing, ordering inventory, and bookkeeping.

• Some are mature companies, and others are part of the NVIDIA Inception program, NVIDIA’s startup incubator, where they’ve developed game-changing, GPU-based AI tools for retail.
• Document the skills, competencies, and experiences you’re acquiring for life during and after college.
• In the retail business, the dataset from which AI learns is actual sales data connected to consumer data.
• Things are looking up and by the end of 2021, we expect to see even more impressive statistics.
• Retailers are using AI and technology like machine learning to power decisions about inventory and the customer sales journey and behind-the-scenes tasks that impact profit margins and efficiency.
• NPUs with enhanced processing capabilities to deliver highest performance for machine learning inference.

In 2017, the eCommerce heavyweight created a buzz with its pop-up Tao Cafe. The Seattle-based company isn’t the only one working on checkout-free shopping. Let’s travel overseas and look at how Chinese tech giants have been developing in the same field.

Retail consulting

It is one of the best Use Cases of AI in Retail that takes retail businesses to new heights in 2022. Based on the product quality, pricing, delivery, and response services, customers build their trust in a brand and revisit the store. O2 is one How To Use AI In Retail Industry high-street store that has started to use AI technology and video analytics to measure dwell times. The overall aim is to understand more about the in-store customer experience so that they can boost conversion rates on specific products.

• The growing data in the retail industry is further driving the implementation of artificial intelligence.
• Walmart uses ML-based systems to forecast demand for its enormous product list.
• Flywheel 2.0, its AI-based Marketplace Optimization Platform, allows retailers to create and manage advertisement campaigns, automate search engine optimization growth as well as track insight and inventory data.
• Retailers that plan to use data wisely, must consider technical aspects, from storage options to deriving key business insights, thinks John Radosta, enterprise solutions architect and data engineer at KaizenTek.
• Decisions can then be made in regards product listings that help to boost conversion rates.
• The company’s Emotive Platform is where users can customize their marketing messages and track related engagement analytics.

So, we are in 2021 and Artificial Intelligence solutions still have plenty of room to grow. However, we can already present to you some examples of real-world AI applications with proven business value. Building this solution started by using the existing security cameras in the store and setting up just a few additional cameras. We had used the YOLO model with pre-trained weights because of its effectiveness in identifying people.

Information & Technology Clients

The products that are sold at a rate lower than MAP can adversely affect business for the retailers. Thus, it is necessary to track sellers who play around with the MAP price. Using retail artificial intelligence, brands can prevent violation of their MAP pricing by tracking and monitoring products in real-time. In a survey, 70% of respondents revealed how they would be a lot more loyal to the brands that added features of personalization in their outlets. With transactional data, AI, and machine learning in retail, brands can easily track and then analyze past purchases, customer behavior, and loyalty cards to deliver more customized offerings. One of the major elements of the mere concept of a factory of the future is made of a smart, connected, and very efficient supply chain.

Similar to the AI-driven surveillance used in checkout-free stores, AI-enhanced theft-prevention platforms help to prevent shoplifting by monitoring in-person shoppers through CCTV footage. These systems are intelligent enough to identify potentially suspicious behavior and alert security guards, a significant improvement over CCTV systems that must be monitored by humans. Here, lunch-goers place their selected food and drink products on the Mashgin device, which uses deep learning and AI recognition software to identify each item and display a bill on a credit card-based payment portal.

The responses are based on what the AI was able to deduce from the dataset regarding the subject. Now that we have looked at the different ways AI can be incorporated in your brick-and-mortar retail space, let’s look at some of the real-world examples of AI in the retail industry. For instance, H&M utilizes big data and AI for analyzing the store returns and receipts for the evaluation of purchase per location and then stocks the inventories on the basis of these insights.

NetSuite are being used by clothing manufacturing brands such as Ralph Lauren to optimize inventory management with machine learning and predictive analytics. The platform can generate models of future customer behaviors and deliver reports related to purchasing patterns, improving inventory management over time. Zeta analyze customer data from multiple customer interactions with mobile apps, email campaigns, and website clicks to identify patterns related to online shopping behaviors. These insights empower digital retailers to make more effective product recommendations and improve the online shopping experience according to each customer’s specific preferences and behaviors.

Systems based on Machine Learning tag goods and sort them in different categories for customers who are seeking a particular type of product. Lalafo sellers can just upload the image of the products they want to sell and Machine Learning retail software with computer vision would recognize it, classify it, and even suggest a price. This platform already processes more than 900 requests in a second, improving sales with relevant content leveraging Machine Learning Models. From the retail edge to the cloud, AI means more opportunities to personalize experiences.