NEW YORK — After years of talk about the power of artificial intelligence and machine learning to transform retail operations, the tools are beginning to make an impact in brick-and-mortar stores, as well as e-commerce. “Customer-driven commerce: How predictive, personalized digital fulfillment capabilities are transforming consumer experiences,” a session at the National Retail Federation’s Big Show — the first of two parts of which was conducted virtually earlier this month — explored recent advances and future applications in the field.

Hardeep Kharaud, senior vice president of merchandising and promotions at Loblaw Cos., and Cheryl Williams, chief information officer at Wakefern Food Corp., offered insights about the use of AI and machine learning in the supermarket sector during a discussion moderated by Wayne Usie, executive vice president of market development at Blue Yonder, a digital supply chain and omnichannel commerce fulfillment company.

Inventory management is one area where both Loblaw and Wakefern are now effectively leveraging the technologies.

“We have implemented AI and machine learning for our store replenishment,” said Williams, adding that product categories involved thus far include dairy, milk, eggs and some produce. “We’ve had a legacy system for many, many years, and it is pretty sophisticated. But it really required our stores to understand it and utilize it correctly. What we found with AI is that it really doesn’t require the skillset necessarily from our store associates. So it takes away a lot of the work that they had to do in terms of knowing what levers to adjust or tune to handle things like holidays and first of the month.

“AI has been a great success from a customer perspective, increased our in-stock position significantly and helped those stores that were not as sophisticated with the tool we previously had really accelerate in terms of in-stock ability. Another thing that it did is allow us to utilize the time that we would have spent on those other things to really focus on inventory, because inventory is the key to success, right? If our inventory is correct in the store and we know that that inventory is correct, then AI takes over and makes sure that we’re in stock.”

Loblaw has also had success with work in selected categories.

“We’ve been working on implementing AI and machine learning for numerous years and to various degrees,” Kharaud noted. “We started off with small tactical things that really helped unlock value for people. We found the best adoption was really making people’s jobs easier, delivering better value to them, freeing up time to do other things, but also delivering benefit.

“As a result of those projects, we’ve become more comfortable with AI and our ability to implement it. And, similar story, we have done work in fresh. That has been tremendous. We looked at it for a long time, looked at different technologies and really started with this small pilot and grew it. The surprising thing for us was how fast people were able to adapt and adjust.

“To pick up on Cheryl’s point, it was really the hands-off approach we were able to take that made the change of management easier at the office, but also in the stores where we work with lots of colleagues. When people see the results, the change part of it became easier as well. It became a pretty contagious thing because people heard others talking and that actually helped us accelerate. Similar to Wakefern, we’re getting benefits around availability and inventory in the right spot, which ultimately helps reduce shrink and increase customer satisfaction. It’s been a great journey so far.”

In addition to giving retailers better visibility and control of inventory, reducing waste, and freeing employees to perform other tasks, the application of AI and machine learning promises to enhance pricing and promotions. What’s more, the impact of the technologies should not only benefit retailers, but reverberate throughout the CPG supply chain.

“When you back that up all the way in the supply chain to the distribution node and back to the supplier, being able to help suppliers understand the needs of the retailer much better and clearer and predicting at a higher accuracy only adds value,” said Kharaud.