#RetailTrends2020: AI to transform retail

There is no denying the immense and disruptive potential of artificial intelligence (AI) for the retail sector. Artificial intelligence, which uses algorithms and data inputs to enable computers to simulate or imitate ‘human-like’ cognition (i.e. sense, reason, act and adapt), is poised to transform retail engagement models and streamline business operations with a force not seen since the early days of Internet commerce. 

However, despite the level of expectation and optimism around the potential applications of AI in retail, the industry, with few exceptions, has exhibited an alarmingly slow rate of adoption. In fact, more than three-quarters of AI projects in the retail sector remain in experimental stages, such as proof of concept and prototyping. Retailers often struggle to understand how to best drive business value through AI and those that have figured this out have typically failed to execute and scale AI applications due to organisational, technological, budgetary, cultural and/or skill-based constraints.

After years of failed promise and with some of the noted barriers to adoption still firmly in place, it would be naïve and perhaps misguided to suggest that 2020 will be the year that AI finally breaks through into retail’s mainstream. However, in order to compete with Amazon, who continue to set the bar high for AI retail, and due to consumer demands for transparency, widespread adoption of powerful 5G networks, and increasing investments in the requisite data and advanced analytics platforms, architecture and talent, AI has emerged as the one technology most likely to transform retail in 2020. And while the potential applications of AI across retail are infinite, five AI-powered use cases look best positioned to leave their mark on the sector during the year ahead.

Content curation: In this emerging reality of tailored experiences, machines will use browsing patterns and evolutionary computation to learn about the customer’s interests, style preferences and shopping habits, and by the time they reach the retailer’s website or open the mobile app, the AI will have assembled a curated, contextualised and personalised gallery of content, images, and product recommendations that are most likely to resonate with the customer at that precise point in time based on where they are in the shopping journey.    

Dynamic pricing: Retailers are beginning to invest in AI to fine-tune algorithms to price products dynamically against an ever-changing market. Dynamic pricing algorithms consider factors such as competitor pricing, consumer behavior, location, time of day, and seasonality to determine how much shoppers are willing to pay for a product or service. AI will enable pricing solutions to track buying trends and determine more competitive product prices either at the local store or individual customer level. While static pricing keeps prices absolute, AI-powered dynamic pricing adjusts prices in real-time to offer customers different prices based on external factors and their individual buying habits and propensity to buy.

Digital stores: The last few years have witnessed the increased adoption of in-store digital technologies including smart shelves, sensors, beacons, clienteling apps, interactive displays, cashierless checkouts, virtual fitting rooms, kiosks, and more. However, despite the emergence of these technologies, network challenges and inadequate data platforms have often left experiences far short of expectation and at best, episodic. With the rollout of high powered, super-fast 5G networks and increasing investment in more advanced digital platforms, much of this will change. The next iteration of the digital store will be characterised by the extended use of AR and VR to create highly interactive customer experiences, while the accelerated transfer of data from device to device will enable the delivery of hyper-personalised, location-specific, AI-powered interactions in real-time.  

Conversational commerce: Social interaction is becoming a fundamental part of the way people and companies do business with one another. With conversational commerce consumers engage with retailers through text, chatbots, social messaging apps, voice assistants, or a mix of each to receive a highly interactive, personalized service, anywhere and anytime. The rapid development of natural language processing (NLP) and AI systems is poised to take this capability to the next level, with more ‘human-like’ experiences. In the new world of conversational commerce, retailers will look to leverage voice controlled digital assistants, either alone or in tandem with digital screens, to enable and support a much more complete and seamless end-to-end shopping journey, providing personalised recommendations and guidance throughout the process of researching, selecting, purchasing and even assembling and using the products themselves.

Computer vision: In computer terms, ‘vision’ involves systems that are able to identify items, places, objects or people from visual images. As we move into 2020, due to recent advances in AI technology, we are going to see computer vision equipped tools and technology rolled out for an ever-increasing number of use cases. In addition to visual search and checkout free stores, computer vision is being rolled out by a number of retailers to analyse the baskets of in-store shoppers in order to recommend other products the shopper might like or send an employee to assist customers who, based on sentiment analysis, seem to be having trouble. As this technology continues to advance, before the year is through, expect to see further applications of consumer vision for inventory management, dynamic planogramming, resource management, theft pro