As Dave has stated, AI is a powerful tool that is driving meaningful value today across multiple retail verticals. Although there is a lot of hype around generative AI and some of the more creative and qualitative aspects of AI, there is no doubt that the quantitative aspects of AI are the most important ones for retailers today. In fact, Gartner specifically calls out 26 different use cases for AI in retail with price optimization, promo optimization and demand forecasting as the clear top use cases for value and feasibility. In a highly inflationary market with shifting brand loyalties and endless disruptions, the data is clear -- retailers using sophisticated AI solutions for their pricing have stolen share and customers profitably from retailers who haven't made the leap. While a lot of AI capabilities may not be a sound investment today, there is no doubt that retailers trying to compete on price without sophisticated tools are at a strategic disadvantage.

Levi Strauss announced plans to test customized AI-generated models with the goal of multiplying the number and diversity of models that customers can see. The denim giant partnered on the test with LaLaLand.ai, Currently, shoppers on Levi.com typically only see one model for each product. The AI technology, according to Levi's, "can potentially assist us by supplementing models and unlocking a future where we can enable customers to see our products on more models that look like themselves, creating a more personal and inclusive shopping experience." The project supports Levi's broader diversity, equity and inclusion objectives.

The new concept is built upon machine learning algorithms, according to the retailer, that "produce tailored, real-time recommendations for each …

IBM and Target were cross-referencing car license plates back in the early 2000s. This is just business as usual. How many times do people stare and scan a McDonald's menu and order the exact same thing they did at least 20 times before! To suggest this is using AI is a stretch at best. It's simply using available information to shorten speed-of-service – an important metric for McDonald's. It should be noted that the latest 2019 QSR Drive-Thru Survey Chick-Fil-A was the clear winner for accuracy, service, and taste.

Artificial Intelligence has great promise to help retailers be more nimble and respond to customer/consumer needs. However, a retailer must step back and have the foundational data pieces in place before trying to implement any AI solutions. I mean foundational pieces such as clean POS data, clean loyalty data and adequate IT systems to allow AI to deliver against its promises. A retailer needs deep pockets to set up their own AI shop with the expertise to manage AI on their payroll. Most retailers will look to the outside for help and a retailer needs to find an outside solution provider that is strategically interested in helping the retailer get their foundational data right FIRST before implementing any AI solution.

Most brands and retailers haven't even approached 1 percent of AI's potential. I agree with Bill's statement "Enhancing your analytics engine with AI can make it possible to optimize individual experiences at scale" but… that is only a first step and will fall short of meaningful personalization in the long run. The biggest blunder I see everywhere AI is employed in a consumer/user-facing scenario is keeping it under the covers away from users. AI is most often employed as a secret analysis mechanism which limits it to being only as good as underlying algorithms and the assumptions driving them. There is a complete fear of using those assumptions as a basis of asking consumers/users if the AI-generated conclusions are correct or if not, where they are wrong or what their preferences are.

Artificial intelligence (AI) is offering the retail industry numerous opportunities to innovate for the better -- specifically in marketing, product innovation, pricing and promotion. But some of us just don't get it. Intelligent machines are already affecting what we see and experience online and in real life, and how we react to the world around us. And given the intensely competitive retail landscape and ever-accelerating market changes, these capabilities are a must. Especially in marketing, AI is becoming too beneficial to ignore.

The conventional wisdom is that being in the right location is critical to success in retail. As one Japanese convenience store pursues an expansion, it may be getting some non-human help to decide where its stores should go. Convenience store chain Lawson is considering using artificial intelligence (AI) to determine where to place its new store locations, according to the Japan Times. The chain plans to use AI to collect marketing data, such as household distribution patterns and traffic volume, to determine a given store's chances of success in an area. Generally, the chain makes such decisions based on information gathering and analysis of an area carried out by staff.

Deciding when to take steps into tech investments is always a matter of timing, but a study from Accenture finds companies across industries are significantly shortchanging their workforces when it comes to empowerment through artificial intelligence (AI). As part of the report, "Reworking the Revolution: Are you ready to compete as intelligent technology meets human ingenuity to create the future workforce?," In retail, Accenture estimates that if stores invest in AI and human-machine collaboration at the same rate as top performing companies, revenues would climb 41 percent by 2022 and employment levels by 10 percent. A barrier is perhaps evident in the finding that only 26 percent of execs feel their workforce is ready for AI adoption. Yet a survey of 14,000 workers as part of the report found 69 percent agreeing that it is important to develop skills to work with intelligent machines and 62 percent believe AI will have a positive impact on their work.

According to a survey from SLI Systems, 54 percent of mid-size retailers are using or plan to use artificial intelligence (AI) as an online tool in the next 12 months. The most popular applications are expected to be personalized product recommendations, customer service requests and chatbots. The online survey of 234 e-commerce professionals primarily in the U.S., Europe, Australia and New Zealand showed that 56 percent are either using or planning to use AI for personalized product recommendations. That was followed by customer service requests, 41 percent; chatbots, 35 percent; and visual search, 32 percent. VR/AR, voice-activated apps and virtual buying assistants scored lower.In a note from late September, according to Barron's, R.W. Baird's Colin Sebastian indicated that the "overriding theme" at the Shop.org Noting that AI chatter had risen significantly at e-commerce conferences over the last two or three years, Mr. Sebastion said the message being relayed was that "machines will learn about and communicate with individual customers."