Bonus Episode: How Is Artificial Intelligence Transforming Manufacturing?

**Allison Ryder** (0:02)
Hi, everyone. Allison here. You might remember our first bonus episode back in January, which was an excerpt from an interview at the World Bank event at Georgetown University about how artificial intelligence is transforming organizations.
This episode also features a talk from that event, this time focused on manufacturing.
Sam moderates this panel and puts Shervin in the hot seat as one of our panelists alongside Nesh Shroff, Director of the AI Edge Institute at Ohio State University, and Matthew Wilding, the co-lead of the Digital and Artificial Intelligence Program at US. Steel. To learn more about how artificial intelligence is shaping manufacturing, as well as a little bit about Shervin's background in chemical engineering, tune into the rest of this episode. We hope you enjoy it.

**Sam Ransbotham** (0:44)
Tell us a little bit about your background and what you're doing.

**Ness Shroff** (0:49)
I'm Nesh Shroff and I'm a professor of electrical and computer engineering, as well as computer science and engineering at the Ohio State University.
My research interests are in telecommunication networks and for the last decade or so in artificial intelligence. I lead one of these National Science Foundation AI institutes that's led by Ohio State. And the goal of that institute is to develop AI technology for designing future generation wireless networks, as well as enabling distributed intelligence, so democratizing AI. That's one of our goals. Pass it over to you.

**Matthew Wilding** (1:35)
So my name is Matt Wilding. I work with United States Steel, so I'm the co-lead for our Digital & Artificial Intelligence Program.
My background is actually in chemistry, so I was a classically trained chemist, worked at the Department of Energy for a while, and wanted to work for solutions that were a little bit closer to the end consumer. Did some time in management consulting and then landed at US. Steel. Where I've led successive digital transformations kind of different areas of our business. So starting in people analytics, then growing that into thinking more about talent acquisition, recruiting visa programs. How do you do those things in a manner that's digitally enabled and is actually making intelligent decisions? Then currently, again, leading the actual global initiative for United States Steel around digital and artificial intelligence.

**Sam Ransbotham** (2:20)
We'll go to Shervin. Even though you just heard from Shervin, some people may have joined the live stream here. So, Shervin.

**Shervin Khodabandeh** (2:26)
Hi, Shervin Khodabandeh. I'm a senior partner with the Boston Consulting Group, and one of the leaders of our AI business.
Many of you might have heard of BCG as a strategy company. You might not know that we do a fair amount of AI work, both in terms of strategy and design, but also in terms of building solutions and implementing them.

**Sam Ransbotham** (2:46)
All right. So manufacturing, nothing to do with artificial intelligence. It's just processes, it's machines running.
Prove me wrong, Matt.

**Matthew Wilding** (2:55)
Could not be farther from the truth. I'll start there. You told me to be adversarial, so I've prepared. One of the topics that we've talked about is introducing new processes with artificial intelligence versus reimagining processes that are already out there.
And there aren't more process-heavy organizations than manufacturers. You know, everything we're doing is starting with the raw material, it's starting with energy. We're consuming that to convert it into some sort of work in progress that's then a finished good that goes to our end consumer.
And so along every one of those potential steps where we are either touching the product, touching the consumer, or touching our customers, you actually are making decisions that are very, very data-enabled, right? Because all of our equipment is recording information so that we can actually produce within good tolerances, with good quality, with good yield. And so we've got a plethora of data that actually gives us a really great, rich platform to be one of the first movers in pulling some of this information forward. And the risk profile, we heard from folks who were in healthcare this morning, again, the risk profile is a little bit easier when we're making decisions on yield or production than if we are actually making decisions on diagnosis of a disease in a clinical setting.

**Sam Ransbotham** (4:06)
But perhaps a little more pressure, and we can come back to that. But you mentioned data. Ness, I know that you've thought a lot about how you get good quality data from a lots of different places at the same time. And that seems like the core of what Matt was just talking about. Hey there, Sam here. If you're like me, then you love hearing from thinkers who are shaping the business landscape and are seeking solutions to the world's most complex issues. Which is why you have to check out If Then, the new podcast from our friends at Stanford Graduate School of Business. If Then is made for curious people looking for answers to challenging questions. Each episode centers on an in-depth conversation with its Stanford GSB professor about the innovations and insights they're most excited about. And why they matter to us, our lives, our work, and our future.