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Running the AI Race: What Retailers Should Know

To unlock the full potential of artificial intelligence, retailers need a strategy in place to guide their efforts.

J.P. Pressley is a contributing writer to BizTech magazine and an editor at Manifest.

The race to adopt artificial intelligence has begun, and powerful tech leaders from Amazon, Google and NVIDIA have all embraced its power. Right now, the retail sector ranks second among industries worldwide in its spending on AI, according to IDC. Retailers are expanding the set of use cases for how AI can help with supply chain issues, staffing shortages and customer service.

A whopping 97 percent of business leaders say AI is a growing priority for their organization, according to a 2023 Cisco study. But such urgency can also cause a frenzy. That’s why IT leaders must orchestrate their efforts intelligently and create a strategy for how AI factors into their current IT environment.

Here are some best practices and use cases for AI that retailers should know:

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The Biggest Use Cases of AI in Retail

There’s a simple reason why retailers are investing in AI: It works, and it’s versatile. It also drives results. A recent IHL Group study reported that retailers achieve two times the sales growth and three times the profit compared with competitors that aren’t leveraging the technology.

“We’ve been using AI for many years to support our team and drive speed and efficiency across all of our operations,” says Brett Craig, executive vice president and CIO at Target. “Everything from our supply chain and inventory management systems to applications in the checkout lines at our stores and on our website and app.”

Target’s use of AI to optimize inventory management, for instance, has helped the retailer solve for product availability, ensuring customers can purchase what they need, where and when they need it.

We’ve been using AI for many years to support our team and drive speed and efficiency across all of our operations.”

Brett Craig Executive Vice President and CIO, Target

Often, these use cases connect to customer experience. For example, AI-powered chatbots accelerate customer support because customers can get their questions answered 24/7. And generative AI can predict consumer behavior, enabling retailers to personalize shopping experiences.

To be successful in their efforts, retailers must determine the best places to deploy AI within the customer journey and create a strategy for how these tools will integrate into their existing technology.

AI Best Practices Retailers Should Consider

For AI investments to work, they must be purposeful. It’s imperative that business leaders have a plan for how this tech will support larger transformation efforts and align with larger goals. IT leaders must also make sure AI tools pair with their existing tech stack. Otherwise, cybersecurity risks increase.

It’s also important to remember that each business may approach artificial intelligence differently. For some, this may mean implementing it across the board; others may start small and focus on one problem area, such as inventory management, where AI can help with product counts and tracking.

3x

The increase in profit growth seen by retailers after deploying AI

Source: ihlservices.com, “Retailers That Use AI Enjoy Over 2x Sales Growth and Nearly 3x Profit Growth Compared to Competitors,” Dec. 14, 2023

Wherever you are on your AI journey, here are some best practices that can benefit retailers of all sizes.

Focus on quick wins: Financial rewards, such as doubling revenue or tripling profits, aren’t going to happen overnight. But there are other, smaller wins retailers can rack up. For example, use AI to automate routine, repetitive tasks. If you automate the basics, this low-hanging fruit can improve workflow efficiencies and reduce employee burnout.
Use AI as a test-and-learn tool: Test a specific use case, such as chatbots in customer service, or run a pilot program to gauge the ROI and sort out any kinks. These incubators for experimentation allow retailers to evaluate the results, give AI more inputs and fine-tune the functionality ahead of broader implementation.
Prioritize data quality improvement: In modern retail, data is gold, but too often retailers fail to adopt advanced analytics. AI’s algorithms can help sort, analyze and clean data. From there, retailers can implement data governance strategies to maintain proper data quality, privacy and compliance. The cleaner the data, the better the results.
Invest in employee training and collaboration: AI works best with human oversight. Give staff the chance to become familiar with AI capabilities through training sessions. IT leaders should also foster a culture of collaboration to help employees learn the data language of AI. Take, for example, Lee’s Famous Recipe Chicken: The company’s transition to Intel’s drive-thru AI attendant led to a 95 percent order accuracy rate and happier customers. But the results would be different if employees weren’t trained on AI.
Don’t view AI as an all-in-one solution: AI is not magic. It’s a technical tool that can support and amplify the efforts of your business. Stay focused and be precise in how you implement AI — have a reason for applying it to any area of your business.

Using these best practices, IT leaders in retail can gain a competitive edge. They can also give their organization the operational efficiency it needs to keep running the race.

UP NEXT: The 4 most effective uses of generative AI in retail.

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