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Artificial intelligence (AI) was at the top of the heap in terms of buzz on the Shoptalk showroom floor and topics and questions in the sessions at this year’s conference in Las Vegas. A recurring joke at the conference was that some words become so commonly mentioned that it becomes like buzzword bingo. Unlike past terms/technology that fit this description, AI seems to have legitimate staying power and use.
A session on Monday, “New Applications of AI and Machine Learning,” featuring Patrick Duroseau from Under Armour, Barkha Saxena from Poshmark and Anshuman Taneja from Peapod Digital Labs, was moderated by Lauren Wiener from Boston Consulting Group in a lighthearted but informative way.
There are mixed perspectives on AI in the market now. Some think it will be revolutionary and others are cautious, worrying that it will take over the world. Mr. Duroseau provided a balanced approach, saying AI is just like any other technology: “You just have to understand the context where it belongs, how to absorb it, how to leverage it and really just embrace it the proper way.”
Two key elements of embracing it the proper way are collaborations with other leaders and promoting and executing in a responsible manner. Companies need to work together to forge consensus on the appropriate governance and usage of data and algorithms with a technology that is quickly evolving. Mr. Duroseau said it is important for companies to participate in organizations that unite to promote the responsible use of AI, such as the Data & Trust Alliance.
Ms. Saxena continued the theme of establishing and managing governance to ensure good use of human-level AI models. She explained that it is hard to answer all questions using AI for chatbots. Simple answers are made for AI chat. Individual associates with specific topic expertise, however, are best at responding to specific second-level questions.
Mr. Teneja said there are opportunities for retailers to deploy AI to improve customer experiences and supply chain performance. Grocery has some of the highest frequency of visits and repeat purchases, which drive a lot of data about types of trips and varieties of baskets that can continuously feed machine learning efforts. There is also a great deal of data on promotions, pricing, loyalty, digital touchpoints and other influences on shopping. This volume and completeness of data can go a long way in using AI for convenience.