Data Center / Cloud

Top 3 Pillars of AI Enabled Edge Computing in Retail

Global retailers and suppliers are faced with navigating rapidly changing consumer demand, behavior, and expectations. These changes are driving uncertainty in forecasting and putting pressure on global supply chains as well as omni-channel and store operations. Real-time agility is required to navigate the rapidly evolving challenges for the retail industry.

Artificial intelligence offers a powerful solution for retailers to rapidly and more accurately forecast daily demand and automate supply chain logistics. This has a major impact on in-store supply and last-mile delivery cost challenges, while meeting consumer expectations on delivery timelines. For online shoppers, AI is helping create personalized shopping journeys and product recommendations. In-store, retailers are using AI to reduce shrinkage and stockout, while creating frictionless experiences and ensuring the health and safety of employees and shoppers. 

The financial opportunity is significant across the $26 trillion retail industry, which historically has averaged a 2% net profit margin. An estimated 3X increase in profit margin with AI-enabled solutions would lead to over a $1 trillion increase in annual revenue for retailers, according to analysis by the McKinsey Global Institute. From customer engagement, to operational agility, to seamless omnichannel management, AI at the edge is transforming retail.

Retailers Adopt AI for Improved In-Store Experiences, Less Shrinkage

Retailers are leveraging AI at the edge to analyze data from in-store cameras and sensors, and create intelligent stores. One application alerts store associates when shelf inventory levels are low, reducing the impact of stockout. Another is decreasing shrinkage—the loss of inventory from theft, errors, fraud, waste, and damage—which costs the industry an estimated $100 billion per year globally. AI helps retailers protect their assets with store analytics that monitor points-of-sale and floor merchandise to prevent ticket switching, misscans, and shoplifting. 

Deep North, a computer vision startup, uses intelligent video analytics to power in-store analytics, providing insights to customer traffic and heatmaps, determining dwell times, queue/wait times, conversion metrics, demographics, and more. These insights help retailers improve inventory planning, store layout and merchandising, and improve the customer experience and conversion. 

Frictionless store concepts are being tested where shoppers can skip the checkout lines entirely and be automatically billed for their purchases. AiFi is a leader in these AI-enabled autonomous stores from nano stores to full-sized grocery chains. These “grab-and-go” stores are rising in popularity and locations are projected to expand 4X in the next 3 years.

Figure 1. AiFi provides autonomous shopping solutions leveraging computer vision powered by NVIDIA Metropolis for in-store analytics and the NVIDIA EGX platform for AI at the edge.

AI Personalizes Online Shopping

Personalized experiences are critical in ecommerce, which can account for as much as 30% of revenue for the world’s largest retailers. Underlying ecommerce are sophisticated recommender systems (RecSys). GPU-powered machine learning and deep learning enable recommenders by learning how customers shop, personalizing their shopping experience, and finding related items that shoppers are most likely to purchase. NVIDIA has deep domain expertise with our data science teams winning three global RecSys competitions in 5 months.

To support the online personalization and recommendations, global retailers are using AI to automatically generate metadata for new items listed in their vast digital catalogs. With up to millions of new products to onboard, comprehensively and accurately labeling and describing every product is a daunting task. AI quickly produces accurate, comprehensive, and engaging product content that a RecSys engine uses to provide personalized recommendations that attract a shopper’s interest.

Visual search is a key trend for retailers to provide a customer-centric experience with product search and discovery. Clarifai, a startup and NVIDIA Inception member, uses computer vision and AI to deliver more relevant search results and hyperpersonalized product recommendations quickly. With “snap-and-search” capabilities, shoppers are able to take a photo of a product they’re interested in with their mobile device and automatically have the photo matched to a product catalog. Related products to complete their desired outfit, room, or other look are also shared. 

Smart virtual assistants, used by hundreds of millions of users each month, are also driving growth in ecommerce. Retailers are looking to improve the digital customer experience by introducing voice ordering to replace text-based searches with voice commands. With voice ordering, shoppers can easily search for items, ask for product information, and place online orders using smart speakers or other intelligent mobile devices.

Creating a Resilient Global Supply Chain

AI empowers retailers to create more resilient supply chains that respond quickly to changing consumer demand and effectively manage inventory distribution. 

Walmart, for example, uses AI to run accurate daily forecasts of millions of item-to-store combinations across thousands of stores in the United States. Built on open-source data processing and machine learning libraries, this AI-powered platform enabled Walmart to get the right products to the right stores more efficiently, react in real time to shopper trends, and realize inventory cost savings at scale.

In smart warehouses, AI improves operational efficiency and throughput with customer orders automatically picked, packed, and shipped by robots. These robots use edge computing and intelligent video analytics to identify, position, and sort packages while adjusting the speed of conveyor belts to minimize product damage and machine downtime. 

KION Group simplifies the deployment and management of AI at the edge— including autonomous forklifts and pick-and-place robotics—across thousands of retail distribution centers.

Figure 2. KION uses pick-and-place robots in its intelligent warehouses with AI deployed at the edge.

AI delivers end-to-end visibility that combines data from GPS, weather, traffic, and construction to determine optimal shipping routes. This can significantly reduce overhead costs for last-mile delivery associated with fuel, transportation, and delivery personnel—and can provide more accurate delivery windows that enhance customer service and create more satisfied shoppers.

Future of Edge Computing in Retail and Beyond

Billions of connected sensors are coming online in retail stores, city streets, hospitals, warehouses, and more. By deploying and managing scalable, secure AI at the edge, enterprises can turn this data into faster insights and more robust services and applications. 

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