Why Most Retailers Will Never Transform With AI (And That’s Okay)

Hello Walton’s Weekly Wramblings Fans!

My last two weeks of wramblings have been quite, let’s just say, quote heavy, as I figured the retail executives that we interviewed at NRF and FMI Midwinter could highlight the trends much better than I ever could.

This week, however, I am going back to my roots. Rambling, pontificating, relaying whatever the heck is on my mind. Getting things off my chest, so to speak. 

Because, for some reason, I just can’t stop thinking about how retailers should approach the implementation of AI throughout their organizations, which is a topic that is no doubt on the minds of many of you. It is a question that wakes me up in the middle of the night, forcing me to write down various notes on my phone in the wee hours of the morning, so I can only imagine the consternation it is causing inside retail organizations.

Or maybe it’s just me?

Grow, Improve, Or Transform?

My retail nerdiness notwithstanding, one framework I us to piece apart how I should assess things is the idea that every good CEO is in charge of three basic ideas. He or she can either: 1) grow the business 2) improve the business or 3) transform the business. By “grow the business,” I mean increase revenue. By “improve,” I mean cut costs or find ways to be more productive. And, “transform?” Well, by that, I mean turn the business into something altogether different, with fundamentally altered business model economics.

Transformation Ain’t Just A Mirage In The Desert: Amazon and Walmart Are The Exception, Not The Rule

The last of the three is exceptionally hard. Which is why, when I evaluate the retailers that have done it well over the past decade, the list is pretty small. You have Amazon, by way of AWS, and I would also throw Walmart into the mix, given the recent $4 billion valuation for its financial services arm. Fanatics could also potentially crack into this category. 

Other than that though (and I just scanned the NRF Top 100), there is nary another established U.S. retailer that has “transformed” itself of late. Many have hit ups and down, and have come roaring back with a vengeance (Abercrombie comes to mind), but they almost always do so atop their same underlying business model economics.

AI’s Real Promise Is Improvement, Not Transformation

I bring this framework up because there are many people in the media that would have you believe that AI is going to be transformational. I don’t share that opinion. It will be for some retailers, but in the long-term, the core of retailing, i.e. getting people to buy products they need or desire, won’t change all that much.

It will no doubt will be transformational for some, perhaps even for the next Amazon, whom we can’t even see and whose business model hasn’t crystalized yet, but for the average retailer, the chances of finding “transformation” via AI are about as short as this paragraph.

However, that isn’t to say that AI isn’t still important. It most certainly is. It is just how you decide to harness it that matters most.

Hence the framework I outlined above.

For my money, I would walk past all the shiny pennies on the ground waiting to be picked up and forgo the transformational ideas, and even some of the grow the business ideas, in that order. Instead, I would be focused 100% in the short-term on improving the business. Retail is one of the oldest businesses there is. It isn’t going to change overnight. We still need to put products on shelves or on people’s doorsteps, but the “how” we do it is where all the value from AI is waiting to be unlocked.

If you are leading a retail organization today, I would 100 percent look internally first, at your warehouse operations, your store operations, and even your internal operations before even sniffing consumer facing use cases. 

Look Internal First: Warehouses, Stores, and Operations

It will be easier to find value in any of them than it is to find value in the buzzword that 99% of people onstage at conferences are always uttering, and by that, I will just come out and say it, “personalization.” In fact, if I were to start a new drinking game at Shoptalk in March around the word “personalization,” my hunch is I wouldn’t even make it until noon on the first day of the conference. People would need to drag me back to my room at the Mandalay faster than you can say, “agentic,” which is kind of ironic because I would actually need someone to carry me.

But I digress.

Let me explain what I mean. Take a warehouse. Is it that audacious to ask – how can we run one building with 80% less managerial staff? And then design a new process, leveraging AI to do so? And then test your way into it?

Or take a store as another example because I wish I had this knowledge back in my Store of the Future days at Target.

Instead of designing a new shopping experience, I wish I had approached the problem differently and asked how I could run a Target store 25% more efficiently? That is the question I should have asked then, and that is the very same question others should be asking now because the technology may actually exist to make a sizable dent in the goal. Robotics, intelligent store management solutions, and computer vision AI all come to mind.

AI Exists to Simplify the Hard, Not To Make Easy Things Fun

The application of AI, as told to me this week in a soon-to-be-released podcast interview with Experion Technologies Global Head of Data and AI, Siraj Alimohamed, all starts with the outcomes you want to achieve and then designing new processes to reach them. Retail has never been rocket science. It is about as block and tackling as one can get, especially for anyone not named Amazon or Walmart. But that also doesn’t mean retail is easy. 

Far from it.

It is about as hard of a business to do well as there is. So let’s not delude ourselves by following the fancy buzzwords that seem fun and easy just because they are new. AI, in reality, exists to simplify the hard. It won’t be fun. It won’t be easy.

Then again, nothing worth doing ever is.

Be careful out there,

– Chris and the entire Omni Talk team