AI in Retail – Is the Value Real or Artificial?

Conversations and analysis around AI are omnipresent — however several important elements are being missed. First, most arguments are focused on the debate between AI optimists (see Andreessen Horowitz world-saving view) and AI pessimists. There is so much focus on what AI can do to replace humans, if it’s good enough (according to the genius hypothesis, it can equal or even raise the average— intelligence, creativity, creative output— but will never equal genius), and if humans can adapt. The real question, however, is not just how AI can be used to increase productivity. The larger questions are about what new ways it can be used to create value and what business models could capture this.

Reshaping the Retail Value Chain

In many industries, AI has the potential to fundamentally reshape the value chain. Retail is no exception. There are many problems that AI could potentially help solve by:

1. 1. Picking up on changes in consumer demand patterns – on a category, brand and product level. AI can aggregate data from multiple sources to identify patterns and help manage inventory to meet rising demand.
   2. Simulating impact to weigh different strategic initiatives – assessing impact on revenues of different merchandising strategies, promotions, shopper marketing, performance marketing etc.
   3. Enhancing customer relationship/increase cross-selling by predicting the Next Best Purchase – the most likely purchase given patterns from both internal and external data sources brought together
   4. Sharpening targeting through a Personalized Shopping Assistant (in-store and online) assisting with search, best fit, suggestions etc.
   5. Optimizing customer service through dynamic scripts, face and voice recognition, predictive equipment maintenance etc.

However, the real value of AI goes beyond revamping current activities – ultimately, it will be in making entirely new retail models possible, where the very relationship with the consumer is reinvented. A few examples, among many others, could be:

Creating Worlds and Experiences – Beyond Transactions

Imagine planning a dinner party. You put in a theme and receive a dinner planned by Gordon Ramsay. As you select recipes, ingredients in the right quantity for your party automatically appear in your shopping cart – and a cooking flow is set for you with videos, instructions and timely reminders. Table settings for your theme dinner are delivered right on time with suggested wine pairings. AI can help create a world of experiences – where value is derived not just from the purchase transaction, but from the experience and interactions that these enable.

Lifestyle Ecosystems – Beyond the Category

Imagine putting in the occasion for your next office party and receiving outfit recommendations, removing the traditional consumer angst of not knowing what to wear. Imagine your style choices then connect you to a community of like-minded aficionados (Recent years have seen the formation of many such lifestyle communities, from cottagecore to farm chic or now momcore that has recently been reinvented). This lifestyle community would bring together an ecosystem of providers, from clubs to sports, leisure and entertainment, supported by a stream of “endless” content. These ecosystems will not just foster a stronger sense of belonging and loyalty – each interaction will enhance the value of interactions to come.

Co-Creation: Sharing Creativity

In the traditional model, consumers are subjects – on the receiving end of the brands’ creativity, branding and advertising. Recently, brands have been exploring reversing that pattern – putting consumers themselves in charge of advertising the brand – from Apple featuring consumers’ photography in its ads to Yeti’s UGC campaign. With the democratization of creativity brought about by AI, this can be taken one step further – with much more ease, consumers will be able to ideate, script, design and even produce an ad – and disseminating it to their networks, creating the sort of viral effects that create exponential growth.

Every retailer knows well that beyond satisfying consumers’ functional needs, there is a large market in meeting consumers’ deeper needs of feeling seen, taking control of their narrative and connecting with others. Through data and matching algorithms, AI can give consumers the ultimate control over their narrative – expressing their values, personality and lifestyle choices. In such an ecosystem, value would be created through much more than transactions – through the interactions that will create data that will ultimately enhance the value of the ecosystem at large.

The ultimate question is how these retail models will lead to new ways to increase value – an increased customer relationship leading to higher loyalty; better targeting to increase spend; and belonging to a community leading to increased frequency. This is when the AI opportunity will become real.