Unisys is a global technology solutions company that helps the world's leading companies thrive. Our solutions in cloud, AI, digital workplace, logistics and enterprise computing help our clients disrupt the status quo and realize their full potential. Click here for more information.
Todd Pruzan, HBR
Welcome to HBR Video Quick Take. I'm Todd Pruzan, senior editor of research and special projects at Harvard Business Review. Advances in AI create new opportunities to streamline operations, improve processes, and enhance stakeholder experiences. But maximizing the value of AI — from competitive advantage to market innovation — depends heavily on the quality of an organization's data assets.
Today we're speaking with Peter Altabef, CEO of Unisys, a global technology solutions company that recently celebrated its 150th anniversary. Peter, thank you so much for joining us today.
Peter Altabef, Unisys
It's an honor to be here, Todd.
Todd Pruzan, HBR
Peter, Unisys has been in the technology industry for a long time, what keeps the company relevant and what keeps you excited about the future?
Peter Altabef, Unisys
That's a great question, and I think what excites me most about the present and future is the intersection right now of data analytics, artificial intelligence, and quantum computing. The combination of these three is going to create opportunities that people haven't even imagined before.
Well, Unisys has been at the forefront of innovation for 151 years. We were founded in 1873. The first thing we built was the first commercially available QWERTY typewriter. If you think about typewriters and keyboards, everything we use is QWERTY. That was us.
As we move into the 20th century, we introduced the first commercially available general-purpose computer, the UNIVAC I. So when we think about the 21st century, we're looking at the quality of data from the typewriter, the quality of computing from the UNIVAC, and then we add quantum to the mix.
The speed and efficiency of responses, and the ability to craft questions that previously couldn't be answered in a timely manner, is breathtaking. It's incredibly exciting for all of us.
Todd Pruzan, HBR
That's really cool. How is Unisys leveraging advances in technology, such as AI, to address specific industry challenges and improve business outcomes for its customers?
Peter Altabef, Unisys
Everyone is trying to get the most out of AI. So we decided to make it a company-wide initiative. That meant everyone in the company, regardless of their role, was trained on AI. Today, over 96% of the company is trained on AI. Until everyone is comfortable with AI, it's hard to innovate across the company.
And the first thing we did was look at what we call cross-industry solutions. Think about your hybrid cloud environments. Think about your data stovepipes. Instead of just consolidating them into one, organize them and get rid of the erroneous data and the excess data that you don't need. So we have solutions that organize the data stovepipes across industries.
And finally, you get to industry solutions. A great example of one of our solutions is Unisys logistics optimization. We look at logistics. Take air freight, for example. We actually figure out the most effective, efficient way to get your package to the air freighter, and then to your office or your home. That's the entire lifecycle. And when you start adding in quantum, artificial intelligence, great data, our experience with data, we've been in this business for over 40 years, it's a little bit magical.
Todd Pruzan, HBR
That's amazing. Peter, how is Unisys helping its customers access data more efficiently and effectively, and what role does advanced data analytics play in that strategy?
Peter Altabef, Unisys
The first thing I want to say is that while AI is relatively new (20 years) and generative AI has only been around for a few years, they do have a lifecycle, so when we work on generative AI for clients, we really consider the lifecycle of generative AI, especially since it's relatively new.
So it starts with picking the best LLM. It starts with picking the best available data set and getting immediate results. How do you answer questions? How do you get innovation? How do you get ideas that you can't get any other way?
We'll move on to phase two in a moment. Phase two is how to ensure proper data governance so that the data that goes into the system is not just the best data available, but better quality data, because data is so important. That's phase two.
And then the third step is probably the biggest takeaway: You've answered the question, but what do you do with the answer? The analogy I use here is ERP systems. When ERP systems started coming onto the market, they gave you a unified view of your data, which was good. They gave you faster answers. But people realized that you couldn't maximize the benefit of the answers unless you changed the operations that ran your company. Same here.
So over time, we expect that companies will start to take the questions and answers that AI gives them and figure out how to actually optimize their business operations, which we think is the ultimate outcome.
Todd Pruzan, HBR
Well, Peter, thank you so much for being with us today and sharing all of your insights.
Peter Altabef, Unisys
I'm really glad I came here.
Todd Pruzan, HBR
We spoke with Unisys CEO Peter Altabef.
