Lenovo AI VP: Focusing on high RoI AI solutions for Indian enterprises

We know exactly which verticals we are valuable in. It is retail, manufacturing, banking and financial services, smart buildings, smart city, and health care. We are trying to find innovators across all these verticals to find solutions to problems that will arise in these verticals. One of the most popular AI we’re running right now is queue management and people tracking. That solution can be useful for a stadium, a hospital, or a retailer. So, our solutions apply across all verticals. Not only are we trying to find innovators that provide interesting solutions, but the first thing we’re going to do is we’re going to do what we call a responsible AI audit on them. Some of these innovators we’ve talked to, don’t have the strongest data practice security. They create a cool IP, but they’re unaware of how to protect data sanctity or prevent bias. We do not want that as well, so we are auditing our innovators as well.

Two years ago, conversations around AI would have been more novel. But right now we are focusing only on solutions with a solid ROI. We are not selling hardware and software or an Intel CPU; we are selling a cognitive capability, and I think customers are comfortable with that. Especially if they don’t have deep AI skills. What we are seeing now is far more focused, and those cases will have a return on investment for customers. One of our biggest projects is with the US grocery store Kroger. At this chain, they lost a lot of inventory during the self-checkout process when an item might be miss scanned. We can use computer vision here if it detects when an inexpensive item gets scanned while an expensive product is put into the bag without being scanned. The program will immediately stop the scan. Now, that is a billion-dollar problem for Kroger right there. While you do not need a costly AI system to fix this problem.

The Lenovo CIO study found that India will adopt AI pretty fast. India’s only behind Korea regarding gen-AI investment and AI at the edge. Some of your big competitors, like Japan, are at the very rudimentary stages of deployment. So I believe that Indian clients, Indian customers, know that they’re in a very competitive global marketplace. They’re looking for ways to differentiate in a very big way versus what the competitors are doing on a legacy basis. They don’t have a lot to lose. They’re coming into a lot of these markets for the first time. So, they get to start with smart data practices. They get to start with a foundation on top of which they can easily plug into AI. And I think that’s pretty exciting. So, I was really happy to see how many Indian clients were embracing AI. So, Indian manufacturing, retail and BFSI are well poised to adopt AI. 

I think you’re better; it does exist, but I think you’re better off because of how you educate your engineering teams and data scientists. You’re better off than a lot of places around the world, including the United States. There’s a huge shortage of data science skills, even in the United States and Europe.

As I mentioned, 153 of the CIOs we talked to were from India. But you can see that of all the economies around the Asia Pacific, India is looking very heavily at the edge, and most of that is edge AI spending. Again, this recognises  that you will do the AI out close to wherever your data is. The majority of data in the future will potentially be created in a cloud. It will be created potentially with smart appliances to tell when that door is open, and intelligent  HBA systems, and things we didn’t automate before.