NEW YORK, Jan. 14 (Xinhua) -- Retail will be the fastest among the industries in terms of artificial intelligence adoption, industry players said Monday.

"Technology will continue to strip friction from brick-and-mortar retail and AI will become retailers' go-to technology," Deborah Weinswig, CEO and founder of U.S. retail and tech consultancy Coresight Research, said at a panel discussion on artificial intelligence revolution during the National Retail Federation (NRF) 2019 Retail's Big Show,

"Retail will adopt AI technology the fastest in the next three years," said Weinswig, as AI adoption rate by the industry is estimated at 54 percent over the next three years.

That surpasses the adoption rate in banking, manufacturing and healthcare, which have largely utilized the high-end technology in recent years.

Weinswig said data also showed that the retail industry ranked first in spending in AI with 3.4 billion U.S. dollars in 2018, followed by the 3.3 billion U.S. dollars for the Banking industry.

She said AI has underlined key aspects of retail ecosystem, including communication, optimization, rationalized inventory and experiential retail, with technologies adopted the most including rule-based reasoning, machine learning, natural language processing, and machine vision.

AI has helped retailers improve customer experience without adding staff, thanks to smart chatbots able to respond to customer requests, AI voice recognition blurring the difference between the computer and human interface, and data analysis to predict customer preferences and make recommendations, according to Weinswig.

AI-powered dynamic pricing enables retailers to not only set precise price for their products, but also to change prices rapidly in response to competition and demand, she said.

China's e-commerce giant JD.com attributed its growing cross-border retail business to AI technologies and strategic partnership with Google, Tencent and Walmart, said Hui Cheng, head of robotics research, Silicon Valley Research and Development Center of JD.com.

He said that AI has enabled the company to achieve same or next-day delivery, and gain the flexibility to fulfill hundreds of millions of orders during peak sales.

Besides, data-driven AI solutions also allow JD.com to make accurate demand prediction, new product development, optimized inventory placement and transportation, according to the researcher.

"AI is not only the brain, but also the hand, the mouth and the feet and everything in between including the heart (for retail business)," he said.

Edward Park, senior vice president of U.S. clothing brand Guess Inc., mentioned the upgraded customer experience at the company's AI-driven concept store in Hong Kong.

The store, co-built with China's e-commerce giant Alibaba in July, 2018, incorporated advanced technologies into offline shopping.

Customers in the AI-powered store can select clothes shown on the digital screens of the store, which will be prepared for them in the fitting room. The fitting room is equipped with "magic mirrors" which provide 360-degree views with digital technologies.

The mirrors also allow customers to choose a different size or even new items to try without leaving the fitting room, and offer three mix and match recommendations based on a model of Alibaba with customers browsing and shopping history.

What's really cool about this store itself is that "each item in the store is enabled with a carried Bluetooth RFID and the motion sensors which enable all movements to be tracked and to be analyzed" for the store's traffic patterns and customers' interest, Park said.

Weinswig also predicted that China would be the top country, followed by the United States, in AI spending from 2017 to 2022, because of its massive investment, presence of large tech firms such as Tencent and Alibaba, supportive government policies and a huge amount of data based on its large population.

RFID, or radio-frequency identification, is a technology to record the presence of an object using radio signals, which can be used for inventory control by identifying and tracking tags attached to objects.