The retail industry continues to be a hotbed of innovation, with activity driven by convenience, operational efficiency, and the growing importance of technologies such as artificial intelligence, facial recognition, and autonomous vending. In the last three years alone, there have been over 133,000 patents filed and granted in the retail industry, according to GlobalData’s report on Artificial Intelligence: In-store product recognition.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
70+ innovations will shape the retail industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the retail industry using innovation intensity models built on over 128,000 patents, there are 70+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, autonomous vending, skin care recommender systems, and AI-assisted surveillance are disruptive technologies that are in the early stages of application and should be tracked closely. Autonomous delivery vehicle navigation system, autonomous delivery management, and planogram modelling are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are virtual contact centre automation and checkout object identification, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the retail industry
In-store product recognition is a key innovation area in artificial intelligence
The demand for technologies that automate supply chain processes and improve customers’ shopping experiences is increasing. Objection detection and product image recognition have become easier with the rise in artificial intelligence and deep learning. The retail industry already has a lot of visual data in the form of footage from CCTV cameras. The current focus is, therefore, on using computer vision techniques to process and analyse data.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 30+ companies, spanning technology vendors, established retail companies, and up-and-coming start-ups engaged in the development and application of in-store product recognition.
Key players in in-store product recognition – a disruptive innovation in the retail industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to in-store product recognition
Source: GlobalData Patent Analytics
Leading players in the AI-based in-store product recognition space in terms of patents filed are SoftBank Group, Strong Force Lot Portfolio, Nant Holdings Ip, Walmart, and Toshiba. Toshiba offers Elera Produce Recognition, which at checkout enables retailers to offer more satisfactory experiences to customers using artificial intelligence. With the help of this technology, retailers can have optimised produce recognition that encourages self-checkout.
Leading players in this space in terms of application diversity are Strong Force Iot Portfolio 2016, Walmart, Magic Leap, and Nant Holdings Ip.
Leading players in the AI-based product recognition space in terms of geographic reach are Visa, Tiliter, Yi Tunnel (Beijing) Technology, and Procter & Gamble.
AI-based product recognition enhances scanning accuracy and reduces the requirement for code input manually. It also minimises the need for intervention by store associates. As a result, more retailers are likely to adopt the technology in the future.
To further understand the key themes and technologies disrupting the retail industry, access GlobalData’s latest thematic research report on Artificial Intelligence in Retail.