With all the technological changes of our time, Artificial Intelligence (AI) is showing up just about everywhere we look. Chatbots are capable of communicating with customers on a multi-level, in-depth way, and can even respond appropriately to emotions they sense. Walmart is testing shelf-scanning robots that are designed to scan the aisles for low-stocked inventory, missing products and inaccurate prices. Another well-known example is Amazon Go. These stores are completely ridding checkout lines from their in-store experience. AI enables convenience and faster decisions at a significantly larger scale than ever conceived in the retail industry.
Even with the increased convenience and customer experience, not everyone is on board with the recent changes. Some worry AI could replace human intelligence. Recently, headlines noted Elon Musk predicts AI will someday pose a risk to human civilization. No one can really predict the distant future, but, for now, decision-making is a beneficial, symbiotic relationship between man and machine, powered by AI, but guided by people.
At this time, AI is extremely effective in extracting data from multiple sources, enriching it, quickly classifying it at scale, and generating insights. The retail industry has used AI to make online recommendations, help customers find the right products and even predict customers’ needs. KFC, for example is testing AI-powered facial recognition software to recommend fast food items to their customers.
Although AI has its perks, it also has its shortcomings. AI doesn’t work when goals are not clearly defined, or when multiple, competing outcomes have to be evaluated. It also fails to account for less quantifiable or intangible factors, such as reputation or brand image. In these instances, human intelligence is better at making judgments. That’s why man-machine augmentation is the sweet spot. Combining human and artificial intelligence enables more informed and intelligent decisions.
Augmented decision-making is better when there is clean data. AI is only as strong as the data powering it. That’s why it is critical to make sure systemic biases are removed from the data, to help separate signals from the noise.
Consider this example of a B2B distributor who, following a major acquisition, offered a wide-range of product assortments that was decreasing its margins. The company had to rationalize its range. Unfortunately, they couldn’t accurately point their customers to alternate products for the ones that were no longer available. This led to many customers not finding products they needed. For 80 percent of the out-of-stock products, there were no suggested alternates, which led to a poor Net Promoter Score and a 10 percent drop in sales.
To find a solution, product category experts worked with analysts to help them understand each category. After obtaining, reviewing and blending data, various matching algorithms were built based on the category manager’s feedback. On each iteration, the algorithm was further refined to provide better product matches at scale. This human + machine approach increased product coverage of alternate products from 19 percent to 78 percent, improved customer experience and increased sales by 5 percent.
Today, the relationship of experts, AI and data is accelerating and disrupting industries. AI no longer means ‘Artificial Intelligence’ but rather ‘Augmented Intelligence’ –an intelligent combination of man and machine.
Some of the content in this article originally appeared in Multichannel Merchant on August 31, 2018