There are so many ways to use AI technology in retail to improve customer experience, optimise supply chains and reduce waste.

Yet it seems to me that most innovations in the retail industry over the last 30 years have focused on automating labour-intensive tasks.

In my personal opinion, the retail customer experience has not improved markedly in my lifetime, and in some cases, it has gotten worse. Anyone who’s ever interacted with a self-checkout machine will know what I mean.

So, what is next for the retail industry and what can technology and data science do to improve efficiency and customer experience across the many disparate parts of retailing?

To answer these questions, I recently spoke to Shantha Mohan who is a true expert in the field.

Shantha is currently an Executive in Residence at the Integrated Innovation Institute at Carnegie Mellon University, where she co-delivers courses, contributes to curriculum design, and mentors students in their projects and practicums.

Shantha is also a co-founder and long-time executive of Retail Solutions Inc (RSi) where she ran the company’s worldwide product Development team that built the products & services which made the company a leader in retail analytics solutions used by consumer packaged goods companies and retailers across the globe.

She holds a PhD in Operations Management and a Bachelor of Engineering in Electronics and Communication Engineering.

In this episode of Leaders of Analytics, we discuss:

• The applications of AI in retail with the most potential, for online and in-store shopping respectively
• The differences between retail in developed and developing countries and how AI must be customised for different markets across the globe.
• The typical consequences of items being out of stock and how can AI and other relevant technologies help combat out-of-stock problems.
• Whether AI in retail will increase or diminish the ability for small retailers to compete, and much more.