As part of Omni Talk’s new Ask An Expert Series, Azita Martin, GM Artificial Intelligence for Retail and CPG, NVIDIA, shares her tips on how retailers are using AI to respond faster to consumer buying behavior and staying ahead of the game.
Consumers who walk into supermarkets or click to shop online might assume little has changed these days beyond mask requirements and COVID-related supply shortages. Aisles look the same, and Amazon, Jingdong and Alibaba Group continue to dominate e-commerce sales.
Retailers know different. The $23.4 trillion retail market is undergoing significant change, being disrupted by a pandemic that has made inventory forecasting difficult, created massive supply chain disruption and accelerated a shift into online shopping.
To respond quickly to these challenges, retailers are using AI to provide safer contactless checkout lanes, which also helps reduce shrinkage in stores by at least 50%. AI also helps retailers optimize store layouts. Retailers are merchandising better by understanding consumer behavior in stores, and they’re using AI to measure crowd density to ensure the health and safety of customers.
At the same time, with consumers shifting to online shopping, AI is helping retailers optimize the omni-channel experience by enabling customers to order online and pick up at curbside or have items delivered speedily to their homes.
NVIDIA has been working with retailers as well as software startups that provide some of the most innovative AI technologies to help retailers deploy AI solutions that can quickly be a boon to their bottom line.

Source: National Retail Federation and IBM Institute for Business Value
We see three areas where AI is delivering the greatest business value:
#1 – Supply Chain Optimization
AI-based forecasting is enabling retailers to run daily forecasting on millions of combinations of SKUs and stores, improving accuracy. For example, using NVIDIA’s RAPIDS software libraries and NVIDIA GPUs Walmart has improved forecasting accuracy by 4 percent, resulting in hundreds of million dollars in cost savings, but most importantly ensuring the right product is available at the right stores or distribution centers at the right time for customers.
Intelligent warehouses powered by AI, expedite distribution center throughput, improve order accuracy and accelerate order fulfillment. These solutions include intelligent multi-shuttle cabinets, adaptive speed conveyors and pick and pack robots that intelligently automate how items are unloaded from trucks, stored and retrieved for the right orders.
Hand-in-hand, these technologies remake the supply chain, everything from better and faster forecasting, to faster throughput in distribution centers to robotic carts and arms for faster order fulfillment.
#2 – e-Commerce Optimization:
Recommender systems: Studies suggest that as much as 15% of an ecommerce site’s revenue is derived from delivering recommendations that are much more personalized based on a person’s interests and purchasing history. Stitch Fix, for instance, is using deep learning recommendation systems on NVIDIA GPUs to help stylists offer its 150 million active users more personalized styles from its existing inventory.
Other retailers are using deep learning recommendation systems optimized with NVIDIA’s Merlin application framework to provide more personalization than ever before.
Automated data labeling: Using computer vision, NLP and image recognition, startups such as Clarifai and Crowd use AI algorithms that learn from data scientists how to tag data and automatically generate meta-tagging to label and enrich data. Retailers can automatically label their ecommerce catalog at attribute level, which enables more personalized recommendations and helps customers find the right products on their e-commerce site.
Visual search: computer vision technology has improved visual search, helping consumers find exactly what they are looking for on e-commerce sites.
#3 – Intelligent Stores: AI solutions that leverage computer vision are helping retailers bring intelligence to their retail stores.
Autonomous shopping: Frictionless checkout, or intelligent ‘grab-go’ stores use data from cameras and sensors to enable faster cashier-less checkout which is becoming increasingly popular with the younger generation of shoppers. These AI solutions enable retailers to redeploy workers to other areas, including fulfillment and curbside pickup.
Asset Protection: The bane of retailers is shrinkage, which costs retailers 1.4 percent of annual revenue, according to the National Retail Federation. Retailers in the US alone lose $63 billion nationally to shrinkage. AI is the only solution that can in real-time detect ticket switching and miss-scans at every checkout lane, aisle and distribution center, saving retailers hundreds of millions of dollars across thousands of stores.
Stockout and Curbside pickup: AI is also helping retailers eliminate stockouts, by notifying associates in real-time when shelves have to be restocked and ensuring store associates deliver the right order to the right car at curbside pickup.
NVIDIA’s Application Frameworks, including Metropolis for video analytics, RAPIDS for data science, Jarvis for conversational AI and Merlin for e-commerce recommendation systems are being used by over 150 of the most innovative AI startups as well as customers who are building their own AI solutions to improve the accuracy of their algorithms by accelerating training and optimizing compute performance.
Retailers can avoid the costly and time-consuming go-alone approach by adopting solutions provided by NVIDIA’s ecosystem of software partners and deploy AI in months instead of years. For example, software partners like Everseen and Malong are helping retailers reduce shrinkage by conducting 60-day proof of concepts, and then implementing across hundreds of stores. This has helped retailers reduce annual shrinkage by hundreds of millions of dollars per year.
These AI solutions aren’t just skunkworks technology projects for retailers. They are driving profitability in an industry that has notoriously thin margins.
A good path forward for retailers who are evaluating AI is to first evaluate the overall AI solutions that would help them become more agile and efficient in meeting the ever changing customer’s behavior and then select one or two use cases that would deliver the greatest business value in the short term. We see most retailers starting with asset protection and AI-based forecasting.
Keep in mind that you don’t have to build everything from scratch if the cost justifies the buy versus build model. Consider working with startups and system integrators that already have proven solutions to enable you to deploy AI solutions in months.
And NVIDIA’s Inception and retail teams work with startups and ISVs who can help select the best solutions for your challenges.
*Article composed in partnership with NVIDIA*