Retailers Making The Most Of Ai

Walmart, Lululemon and Home Depot are among the retailers making the most use of artificial intelligence, a new study from analyst firm IHL Group concludes. Overall, the top 207 North American public retailers and restaurants could see nearly $1.6 trillion financial impact through the end of the decade according to IHL’s 2024 AI Readiness Index.

In addition to providing an AI readiness score comparison, the index also gauges financial impact for individual companies from sales growth, gross-margin improvement and sales/general administrative cost improvement.

The research includes rankings for the companies in several segments and is composed of a nine-part algorithm for rating companies (0-100) based on data maturity, analytics maturity, alignment with key vendors, scale (revenues) and free cash flow as well as other measures from public and private research. This is then combined with the latest annual financial results for companies to project potential financial impact from 2022-2029.

Below are the leaders in each segment (Readiness Score, Potential Benefit by 2030):

• Ecommerce – Amazon (85.4, $353.7 billion)
• Fast-Moving Consumer Goods – Walmart (77.0, $264.2 billion)
• Apparel/Shoes – Lululemon (top score – 63.2), Nike (top potential – $18.4 billion)
• Hard Goods – Home Depot (65.0, $57 billion)
• Health and Beauty – CVS (63.0, $132.4 billion)
• Restaurant Chains – Chipotle (top score – 56.7), Starbucks (top potential – $9.8 billion)

“AI is already transforming the retail market behind the scenes with traditional AI/ML [machine learning] improvements,” said IHL Group President Greg Buzek. “Generative AI simply adds to that potential financial impact, but there are wide disparities among retailers on readiness. I equate it to someone trying to get from Times Square to LaGuardia Airport. Our leaders are through town, through the tunnel and at the toll booth ready to accelerate. But many others are stuck on 42nd Street in bumper-to-bumper traffic because they have not done the data work.”

Click here for more from the IHL study.

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