The Four Current Traits and the Future of Retail
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The Four Current Traits and the Future of Retail

By Dr. Mark Chrystal, Chief Analytics Officer at rue21 & Co-Founder, MachineCore, Inc.

Future of RetailDr. Mark Chrystal, Chief Analytics Officer at rue21 & Co-Founder, MachineCore, Inc.

My duties as the Chief Analytics Officer for a large retail chain and the founder of an Artificial Intelligence (AI) company have caused me to spend a considerable amount of time contemplating the application of AI in the retail industry. The more I study AI, and its applicability, the more I am convinced that AI is going to reshape our industry fundamentally. Yet, finding an immediately useful AI-based application is currently a needle-in-the-haystack search. In this brief article I am going to address where I see the current AI landscape, the four traits of current best in class AI, and how I think AI is going to change the entire business landscape.

The Current State

Nine out of every ten solicitation calls I receive from software vendors makes some claim about the usage of AI in their technology. I hear that with this application of AI our gross margins will increase by 5 percent or more, or with that application of AI, our sales and conversion will grow more than it could otherwise. When I question the type and quantity of data required to support these applications, invariably I am told not to worry and that they can take care of any data quality or quantity issues. When I dig deeper into the analytics, it is not out of the ordinary to discover that it is not what I consider to be a modern application of AI at all. It appears that any decades old machine learning algorithm can be repackaged as cutting-edge AI. I also suspect that I am being pitched vaporware or Mechanical Turk solutions on a regular basis. AI has become the modern-day snake oil, the cure-all solution that every retailer needs and will be left behind without.

"AI is going to grow up rapidly; Moore’s law may apply for a while, but its development will almost certainly outpace anything we have seen before"

What many software vendors see in the retail industry is a target rich environment. The retail industry is at the edge of chaos. The bedrock of retail has shifted rapidly towards analytically savvy consumer-centric models and away from the traditional ‘merchant prince’ and intuitively based models of the last century. This seismic change has seen a large number of retail organizations fall into the abyss, and some great new concepts emerge. There are still countless numbers of retailers struggling for a foothold and slowly sliding towards the edge. To stall their slide, many retailers are populating their Board of Directors (BODs) and executive teams with deep traditional retail expertise. While this expertise has slowed the decline of some, it has perpetuated a robust level of data science naivety amongst the C-suite and BODs, given how little those with traditional retail success have had to rely on their knowledge of data analytics. Enter the technology providers and their suitcase full of AI-based applications that will quickly allow any struggling company to be competitive again.

While the current state of the retail AI software landscape very much embodies the words caveat emptor, there are some useful applications. In my opinion, the current best in class AI providers share four key traits. First, they have a very clear application of their technology; a very clear problem is being solved by their solution. Second, they have an application that is focused on automating rote tasks or identifying patterns in the data that are not as easily identified via other means. Third, the data they rely on is readily available in large quantities (table stakes for an AI model is hundreds of thousands or often millions of records). Fourth, the data should not require heavy manipulation and cleansing for it to be useful to their AI model.

Think of the current standard of artificial intelligence as being at the level of a young child; a very diligent, task-oriented, mathematical genius of a young child, but nevertheless, one that is only good at processing large amounts of data to produce specific and simple outcomes. Alexa and Siri are great examples of this, and current best in class AI applications. Amazon’s Alexa and Apple’s Siri exactly fit my definition of best in class AI: 1. They are applied in a very clear way (voice-based Q&A), 2. They search the web for answers to the questions they are asked, without requiring the user to type in a question, 3. The input data they rely on is readily available in large quantities (anything you can say), 4. They don’t require the user to fundamentally change the input data being used (they recognize accents, slang speech, filter background noise without you thinking about it). However, if you ask complex or compound questions, Alexa and Siri struggle, just like a young child would.

The Future State

In my opinion, AI is going to grow up rapidly; Moore’s law may apply for a while, but its development will almost certainly outpace anything we have seen before. The future of retail is not what we are currently witnessing at the top end of the retail food chain, it is yet to emerge, and it is retail that is founded on an AI-first model. AI will progress to the point that we no longer need to perform rote tasks. AI will allow us to focus only on work and our experiences with friends and family. Want to go on a trip, our AI-butler will find the best deals, places, and itinerary of activities to fit our individualized preferences and book it all for us. AI will order the clothes we need, and the food we like to eat. There will be no need to go to a mall, or a grocery store, or visit a shopping website, or get in line for a Black Friday deal. Our personal-AI will do all of that for us, while we spend the majority of our free time only doing what we enjoy. We will see retail transform into lifetail, fuelled by AI. This is inevitable, and not that far away.

Conclusion

Think about problems that fit the four key traits of best in class AI, and focus your solution acquisition efforts there, and only there, for now. Be wary of AI providers that offer to develop AI models for you or those that don’t have highly defined applications of their AI-based technology. Be wary of AI vendors who can’t take your readily available data and produce immediate results with it. Most of all, be wary of not using AI to reposition your business towards the AI-centric model that it is destined to become.

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