Artificial intelligence in retail is being applied in new ways across the entire product and service cycle — from assembly to post-sale customer service interactions, but retail players need answers to important questions:
Which AI applications are playing a role in the automation or augmentation of the retail process? How are retail companies using these technologies to stay ahead of their competitors today, and what innovations are being pioneered as potential retail game-changers over the next decade?
In this article, we cover a variety of examples in which AI is being integrated with the retail industry, broken down into the following sub-categories:
- Sales and CRM Applications
- Customer Recommendations
- Logistics and Delivery
- Payments and Payment Services
Innovation is a double-edged sword, and as with any innovation, results are a mixed bag. While many AI applications have yielded increased ROI — this case study of AI in retail marketing segmentation is one example — others have been tried and failed to meet expectations, shining a light on barriers that still need to be overcome before such innovations become industry drivers.
Below are3 brief use cases across five retail domains or phases. Each provides a fraction of a glimpse as to how AI technologies are being used today and which are being created and piloted as potential retail industry standards in eCommerce and brick-and-mortar operations.
Readers may find additional insights into the retail space which were recently covered in our report on business intelligence.
Sales and CRM Applications
Emerj wrote an entire report on current CRM applications at Salesforce, Oracle, SAP using AI, and more for further insights on this topic.
Amazon’s touted brick-and-mortar locations, known as Amazon Go, employ check-out-free technology that allows customers to shop and leave Customers use the Amazon Go app to check-in, but thereafter the entire shopping experience is designed to be automated. Sensors track which objects customers pick up and put in their basket and customers’ Amazon accounts are automatically charged after exiting the store.
The intended launch hasn’t been without its barriers, and at the end of March 2017 sources close to the retail giant announced that Amazon was delaying the opening of its convenience stores while it worked out “technology glitches” in the automated shopping and purchasing process.
AI in Retail — Concluding Remarks
In many of our interviews with retail-focused AI vendor companies, we’re told that “big box” retailers (Best Buy, Target, Walmart, etc) are extremely slow to adopt cutting-edge technologies. Because it’s mostly large companies that have the budgets and data volume required to make the most of many of today’s best AI technologies, we outright surmise that an “AI revolution” in the retail space is unlikely. It may be another three to five years before most large retailers have substantial, business-critical AI applications in manufacturing, supply chain logistics, or customer service.
Applications that have the highest likelihood of broader retail adoption are those that have a direct, hard-line return on investment. “Improving customer engagement” — even with case studies and examples — is a softer benefit than “reducing lost packages by 6–10%.” Our retail executive guests using AI expect that the relatively stodgy committees in these large companies are likely to be extremely critical, safe, and bottom-line focused (for more insights from machine learning industry executives, visit our AI podcast interviews channel).
As with many areas of AI innovation that are led by bigger industry players, the future will likely be dictated by the retail AI use-cases that are proven effective by leading industry players. It’s safe to say that every at-scale retailer in the world is looking to Amazon for hints on “next steps,” and we can expect that the broad swath of relatively smaller retailers will be looking at Amazon, Walmart, Best Buy, and others for their ideas on strategy.
We advise businesspeople interested in retail AI applications to look closely for successful traction in AI use cases (i.e. applications that drive profitability for the firm, not flashy R&D projects) from Amazon and other large players over the coming 18 months.