February 21, 2022
Dr. Shantha Mohan, a software engineering leader and entrepreneur, mentors students as Executive in Residence at the Integrated Innovation Institute. She co-founded Retail Solutions, Inc., a leader in retail analytics in the consumer packaged goods (CPG) domain, and has a proven track record of growing and mentoring technical teams and generating ROI for customers around the globe.
Shantha recently contributed a chapter on AI in retail to the publication “Demystifying AI for the Enterprise,” released in early 2022. We talked to Dr. Mohan about her chapter in the book, her experience in retail, and her predictions for AI applications in the future.
Q: Tell us a bit about your involvement with the book. How did you get tapped for this project? What chapter did you contribute?
A: The book’s principal author, Prashant Natarajan, has published several popular books for the enterprise. He reached out to me on LinkedIn about the possibility of working on this book. He had six other experts in the enterprise lined up to collaborate, and I was pretty impressed by what they were doing in their domain.
I have been working at the Innovation Lab in our institute on students’ summer projects that involved AI, and I am fascinated by how AI could help businesses solve problems. At the same time, I am highly aware of the hype surrounding AI. Most business executives hear about AI in trade journals but are hesitant to take steps to use it. It was exciting to express my thoughts on how enterprises can use AI, the caveats, and the benefits.
I am a retail domain expert, having led the company I co-founded in retail analytics, and felt that I could contribute to artificial intelligence (AI) in that domain. So that is the chapter I wrote. I also invited two industry practitioners to contribute case studies.
Q: What audience did you and the other authors have in mind when writing? Perhaps it’s a broad one.
A: It is a broad audience—business owners in healthcare, retail, etc., corporate executives, and business problem-solvers. I would include AI/ML scientists who have all the knowledge to make it happen but need the business context.
The content takes the readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey. It concludes with expert advice on everything an organization must do to succeed. We discuss the need for quality data, debunk myths, and present excellent case studies by industry practitioners showing those thinking about AI how you do it.
Q: It seems there is still a considerable amount of apprehension or, perhaps, confusion around AI. In your opinion, what is the biggest misconception or myth about AI?
A: There are many myths. The biggest one, in my opinion, is that it is a panacea. Just with any other technology, it is all about how you make use of it. It has many benefits, but it is not needed in many instances. Good statistical tools probably suffice in many cases.
It is essential to analyze the problem to ensure you need AI and have the quality data required to use it. I have seen several projects where the management dictates the use of AI without understanding the availability of data to make the impact, or underestimates the effort to get clean, usable data.
Q: Your chapter of the book focuses explicitly on the use of AI in retail. Can you share more about how your background made you poised to write this chapter?
A: I was a novice in retail operations when my cofounders and I started Retail Solutions in 2003. We began as an RFID (radio frequency identification) company to help suppliers and retailers understand their businesses better by tracking the products that move through the supply chain. It turned out the RFID technology wasn’t mature enough to do what we wanted to do, so we pivoted and started using traditional retail data—POS, inventory, and other supply chain data.
We grew the company to be a leader in our niche, serving consumer product goods (CPG) companies and retailers. We provided solutions for out-of-stock, promotion management, inventory, and other supply chain management.
My role as the head of software engineering was to develop these solutions, and I learned a tremendous amount about retail in serving our customers such as Procter & Gamble, Unilever, Kraft, PepsiCo, etc. The first step in developing solutions is to understand the problem, and I learned from my customers and my colleagues, who were industry experts.
Q: Are there ways that brick and mortar retailers can leverage AI differently versus eCommerce retailers?
A: Omnichannel retailing—serving customers seamlessly with both eCommerce and brick and mortar stores is the way of retail today and the future. Even a small retailer with a couple of physical stores can leverage a platform like Shopify to have the eCommerce capability.
The brick-and-mortar stores have a lot of challenges in common with eCommerce but have some that are different and unique to them, such as staffing the stores. Many retailers such as 7-Eleven are starting to implement cashierless stores, which I talk about in my chapter. AI solutions that address this are gaining momentum.
Another challenge is to manage physical inventory and prevent out-of-stock. We are seeing the use of AI-powered robots and drones addressing this challenge. We will see productivity-boosting mobility solutions to empower store associates to serve their customers better.
While automation may displace some staff from their jobs, retailers hope they can be freed up to serve the customers better by having more time to attend to the shoppers’ needs. Retailers are also looking at physical stores to showcase products that can be tried using AI-enhanced mirrors for clothes, cosmetics, etc.
Q: How do you see AI applications in retail evolving over the next three to five years?
A: Edge technology is going to advance retail operations in a big way. Edge enabled, AI-driven solutions for payments, customer experience, digital content, etc., will become more usable in omnichannel operations, with customers expecting a seamless, frictionless experience. Lessons learned during the abnormal consumer behavior during the pandemic will make the AI algorithms more robust.
Store automation such as cashierless operation and inventory tracking will mature. Advances in voice technologies will help retailers serve their customers better. Drones and autonomous vehicles will help the last mile delivery. Store personnel will be assisted by mobility solutions to make their lives easier and service customers better. Augmented and virtual reality solutions aided by AI will start to help consumers. In all this, security and privacy cannot be afterthoughts. Solutions need to be designed to be highly secure and protect individuals’ privacy.
There is no limit to how much can be achieved, but we also need to be realistic about how quickly the retail industry will move. Legacy solutions hold back many retailers and other businesses from realizing the full benefit of today’s technology. Yet, we have seen how the pandemic has accelerated digital transformation.