Until very recently, it was common to hear an analogy comparing business strategy to that of a chess match. Of course, the similarities between them invite this comparison. Chess encourages us to study our opponent’s movements, to get ahead of them, and to exploit their weak points. However, the metaphor of the chessboard comes up short when discussing the new rules of the market. In contrast to chess, the digital strategy of the 21st century demands that we conceive of a much more difficult match: we are no longer only fighting against black or white pieces. Our rivals are not only the ones we have come to know in the past. On the other hand, the movements of this game do not correspond with a static and previously understood set of rules, especially when technologies like Artificial Intelligence (AI) enter the equation.
Despite not being even a remotely recent development (the term was coined in 1956), the profile of AI has risen significantly due to a leap from the world of research to that of products and services. What has caused this? In brief, the availability of algorithms, large-scale data, and processing power combined allow many business problems to be automized with an exceptionally low margin of error (less than that of a human operator in the case of tasks like the classification of images).
How can retail benefit from AI? It must be said that nowadays Artificial Intelligence has potential applicability along all the points in the value chain. As a highlight and example that could serve as inspiration, AI can help us to design new successful business models like that of AirBnB, which despite not owning a single hotel is able to compete with the strongest players in the market. How do they do it? By investing in data science. These examples range from dynamic price analysis to automatic detection of household goods and utensils at accommodation locations. AirBnB has created a new service adapted to the needs of its target market, to which it offers an increasingly “hyper-personalized” experience.
“Hyper-personalization” of experiences is without a doubt one of the fields in which AI can have the greatest impact, and where companies like Spotify have been able to make Artificial Intelligence one of their most powerful weapons. By combining affinity-based recommendations from your social circle, cultural vectors determined via natural language processing, and analysis of similar audio tricks through neural networks, Spotify has set the industry standard in music streaming services.
To conclude, I would like to point out that AI can’t (nor should) only apply to the area of product and service design, but also to that of improving our internal processes as a company. Jeff Bezos was once asked in an interview about the use of technology at Amazon, specifically automation and AI. He answered that the most important ones, far beyond what generates headlines, were the uses that were not publicized. And he was absolutely right: AI is going to mark a paradigm shift, and we must be prepared as companies in order to understand it and maximize its benefits, to incorporate it into our internal processes, technological platforms, and talent pools as a competitive advantage. We must keep all of its potential risks in mind, always seeking a positive social impact. One way to do this is to approach the topic of automation of work with the mindset that AI can “augment” human efforts rather than substitute them. An example is wemuse, which uses its own AI algorithm to detect which employees have the best business sense. It empowers them and amplifies their opinions above the rest. Here, wemuse is able to learn over time, starting from the feedback provided by store teams, the very best asset available to retailers.
