IBM Watson X: Where AI Meets Human Wisdom in Retail

I enjoyed being immersed in IBM’s Watson X at the National Retail Federation’s Big Show last month. The crux of what IBM Watson X is all about is keeping the humanness of this new kind of smart computer technology called generative AI.

My colleague Neil Saunders said, “The challenge [with AI in retail] lies in finding the use cases that will actually be revolutionary and separating it from those that are mere flights of fantasy. In many cases, retail remains a very human-centric business and that should not be forgotten.”

The important distinction is knowing the difference between artificial intelligence (AI), which has been around for a while, and generative AI. The former has been around for many years and can take big data sources and find patterns. The breakthrough Watson showed the world over a decade ago was that it could take vast amounts of data, find the patterns, and generate new responses.

Many have touted how an individual could use generative AI to create customized ad content, email subjects, and product descriptions that could bring a unique touch to each shopper’s journey. 

Generative AI is in the early stages at the consumer level, but IBM has been using artificial intelligence to support large enterprises and their digital transformation for years.

Nancy Greco, Global Tech Sales, Distribution, and IBM Distinguished Engineer shared that there is always a human checking IBM’s Watson X generative AI so it doesn’t hallucinate because generative AI is most powerful when combined with human evaluation, feedback, and decision-making. It is not a stand-alone product or technology. 

Before I get too deep in the weeds, let me offer my explanation of generative AI because many people either dismiss it or fear it. Those people can become paralyzed by fear and not see the innovation and possibilities. They only see that they will be replaced. 

Consider this…

You’ve seen those cooking shows where everything is pre-cut for the chef. From the rinsed, chopped, and sorted lettuces to the exact 1/8 teaspoon of Cumin, all set out in bowls so the chef can create.  “With generative AI,” Greco said, “you are the chef. It opens so many possibilities.”

Four main buckets are needed to get the right results from your data via Generative AI. I’ll stay with the cooking analogy.