How AI can fuel future growth for retailers

by Vawn Himmelsbach, a technology and business writer
Montreal, Quebec - September 29, 2021

In retail, artificial intelligence can provide more accurate predictions based on near-real-time data, right down to the store level — helping retailers sustain their business through a global pandemic and get a competitive edge as the economy recovers.

Retail has always been a competitive, often cutthroat, industry — but perhaps never more so than in the past year and a half. Amid rolling lockdowns during previous waves of COVID-19, brick-and-mortar shops were forced to cut their hours and limit customer capacity. And some have fared better than others as we move toward the ‘next’ normal.

While some retailers, such as grocery and hardware stores, have thrived during the pandemic, many others — whether mom-and-pop shops, national retailers or franchisees — were forced to shutter their doors. But the challenges of the past year and a half also forced many retailers to speed their transition into the digital realm, offering customers options to purchase products online for delivery or curbside pickup.

But for CEOs, the goal isn’t just to survive a period of disruption, but to come out of it stronger and be ready for growth in a post-pandemic world. And with AI, there’s opportunity to fuel that future growth, says Clement Bourgogne, VP Strategic Programs at Scale AI, Canada’s artificial intelligence supercluster.

“With the pandemic, we’ve seen a massive change in terms of how people consume — and competition has become truly global. At the same time, the pace of innovation is accelerating, increasingly driven by access to more and more data.”

Clement Bourgogne, VP Strategic Programs at Scale AI, Canada’s artificial intelligence supercluster.

Planning ahead for future growth

And while we often hear that ‘data is the new oil,’ more data isn’t helpful unless you can glean insights from it — which is where AI comes in. 

“That’s why CEOs need to care about AI, because it’s about setting up the company for future growth,” says Bourgogne. And they need to invest in AI now, “because if you wait a couple of years, you’re going to be really far behind.” 

An AI algorithm needs to be trained on your data to discover patterns (and continually adjust as it’s exposed to more data) and it takes at least a year or two to build those internal capabilities. And by then, if your competitors are already using AI, their algorithms will be far more sophisticated.

“So it’s not just a year or two that you’ve lost — it’s also the ground that you’ve lost to your competitors that you can’t make up. You can’t speed up the training of your algorithm. So it’s important to start as soon as you can because every day that you lose, you’re losing ground.”

Clement Bourgogne, VP Strategic Programs at Scale AI, Canada’s artificial intelligence supercluster.

AI for forecasting

In the retail industry, the level of investment in AI will vary depending on the proportion of a business that’s online. But the use of AI in digital marketing is already quite advanced because the business case is obvious to most CEOs: helping to predict what a consumer will want to buy, and when, based on historical preferences.

“One of the most popular applications that we’re seeing right now is using AI for forecasting — trying to predict how much you’ll sell at a given point or during a given period,” says Bourgogne.

This has become even more important during the pandemic, when global supply chains have been strained and certain components, such as microchips, are in short supply.

Without AI, forecasting is based on historic sales. But there’s no precedent for COVID-19, so historical data has become, in some cases, null and void. “That’s where an application like AI is extremely powerful because it’s able to correlate what happened with certain events,” says Bourgogne.

Not only does AI provide more accurate predictions based on near-real-time data, it also does so at a much more granular level. For example, retailers can drill down into the data for each store, instead of by region or province.

“It comes down to building resilience. By deploying these tools, you have a lot more visibility into what you have and what you’re doing.”

Clement Bourgogne, VP Strategic Programs at Scale AI, Canada’s artificial intelligence supercluster.

CEOs need to lead the charge

But CEOs need to lead the charge. AI is a long-term commitment, so that commitment needs to come from the top. And the first step is knowing why you’re using AI in the first place. “You’re not doing AI because everyone else is doing AI,” he says. “It needs to come from a specific business need — perhaps better sales forecasting, perhaps optimizing the way your inventory is managed.”

Data may be the new oil, but people mistakenly think that the more data they have, the richer they are. “That’s the wrong way to look at it, because data is only valuable if you can access it and you use it easily,” says Bourgogne. “Right now, companies are collecting all sorts of data and structuring it and storing it in many different locations, which makes it difficult to then leverage it for training algorithms.”

A better approach is to work with directors and lines of business to focus on the key datasets that matter. That can help retailers maintain their competitive advantage, gain new customers and gain new markets. But they shouldn’t sit on the fence for long.

“You don’t activate AI by flicking a switch — it’s a long-term investment,” says Bourgogne. “CEOs care about the long-term growth of their business and AI will be a key source of growth in the company’s competitiveness, but it takes time to fully deploy its potential insights.”

Download our full “AI in Retail” white paper. What you’ll learn:

  • How AI can create business value in retail and why you should invest now to stay competitive;
  • AI Success Story: An In-depth Look at Canadian Tire;
  • Learn more about funding, expert guidance and Scale AI’s community;
  • Get started with your AI project.

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