Data Insight September 20, 2024

Retail Charges Ahead on AI, Responsible for 24% of Demand-Side Implementations

The retail industry is charging ahead on putting AI into practice, responsible for 15% of all the cases in our AI Hub and the most of any other industry on the demand side specifically (24%). Here’s the data, details, and examples of what companies like Macy’s and Target are actually doing.

Jalen Thibou Avatar
Jalen Thibou
Strategy

The Data

  1. 1

    15% of all supply chain AI implementations in our AI Hub come from the retail industry.

  2. 2

    Retail is the industry with the most implementations when we zoom in on the demand side of The Loop, responsible for 24% of all examples when looking at the Sell, Use, and Regenerate functions.

  3. 3

    Retail companies leading the charge include Walmart, Walgreens Boots, and Target, which account for 32% of all retail examples in our AI Hub (supply and demand side).

Capitalize on a Changing Environment 

As demand signals remain strong as ever and marketing bandwidth continues to rise in the age of social media, leaders are considering the best ways to keep pace with a changing environment. Facing challenges like creating feedback loops, maintaining product availability, and optimizing shopper experience, the retail industry is using digital tools to overcome and even capitalize on these difficulties, making it a good place to look for inspiration on the use of AI.  

Our data shows that the retail industry is responsible for 104 AI implementations (15% of The AI Hub) across The Loop, from purchasing to replenishment. And if we focus on just the demand-side functions (Sell, Use, and Regenerate), retail has the most examples, being responsible for 24% of implementations. The most common cases are customer journey optimization (nine use cases), product availability (seven), and product recommendations (six).  Further, these companies are touting these implementations as money makers in signals to the market through press pick-ups and in earnings calls.  

Ring chart showing breakdown of AI use cases cases by function in the AI Hub (retail industry only); list of top three brands in retail.
Source: The Zero100 AI Hub

So, what do these implementations actually look like in practice? We share some examples below. 

Getting Ahead with GenAI and ML 

Macy’s 2024 earnings calls highlight priorities including omnichannel experience, revitalizing product assortments, and improving customer experiences. This translates into reality in the form of the use of tools from Blue Yonder, RFID solutions, and robotic goods-to-person systems throughout its network. These have enabled Pick-to-Last Unit strategies that left inventory available to purchase on their website down to the last unit, maintaining customer levels and avoiding in-store markdowns. In addition, Macy’s is using genAI to connect more closely with its online shoppers. 

Target’s 2024 earnings calls focus on driving growth in digital channels and the orchestration of strategies that include AI. It is rolling out a genAI tool, Store Companion, across its nearly 2,000 stores to enhance team efficiency and improve shopping experiences. The AI chatbot answers operational questions, speeding up service and training for team members on the floor. This is an expansion of the ML and computer vision solutions the company rolled out in 2023, which minimize out-of-stocks and optimize inventory flow to its stores. 

The Takeaway 

As 2025 approaches, digital leaders focused on AI keep coming out ahead, seeing better revenue and margin growth among other gains. To prioritize this capability, we recommend ensuring executive buy-in to be able to move from vision to implementation. Then take inspiration from your peers – retail, for example, are reacting to industry-specific trends but also broader supply chain challenges by investing in areas like inventory management and network optimization. Take your first steps by aligning your AI roadmap with your own business priorities. 

Reach out to us at hello@zero100.com to learn more about our AI frameworks and the Zero100 AI Blueprint, which is how we help companies mold their data-centric supply chain strategies and prioritize AI investments. 

Methodology 

Zero100’s proprietary data and analytics are a combined effort between our data scientists and research analysts. We provide data-first insights matched with our own research-backed points of view and bring this analysis to life via real-world case examples being led by supply chain practitioners today.   

For this study, we analyzed 542 supply chain organizations and 613 unique references of brands scaling AI implementations from The Zero100 AI Hub. We’ve also analyzed 2024 earnings calls for 150 brands pulling relevant insights and categorizing keywords, phrases, and sentiments. 

Further Reading