The Cadillac DeVille is a big, fancy car that was made for many years, known for being very comfortable and stylish. It's like a classic luxury car that people often think of when they imagine a smooth ride and lots of space inside.
Turnaround investments are money that a company spends to fix problems and make things better. This can help them produce more cars or improve their business.
AI and machine learning are computer technologies that help machines learn and make decisions on their own. They can help car companies make better products faster.
Magna International is a big company that makes parts and systems for car manufacturers around the world.
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Want to win the inventory game? With Kelly Bluebook instant cash offer, you can lock in trade-ins before your competitors even blink. Faster deals, better margins, lock in and load up today at b2b.kbb.com Welcome to Daily Drive from Monday, October 6th, 2025. I'm Kellan Walker in Las Vegas, today on the show. Stellantis reportedly plans $10 billion in US turnaround investments.
A report says JLR is working on a loan to help out its suppliers. And Senator Bernie Moreno says President Trump is considering significant tear relief for vehicle makers. Plus, Magna International's Todd DeVille talks about how the supplier is implementing AI and machine learning to make its production more efficient. Imagine you have millions and millions of data points that don't quite align. That's where the AI tool sets can come in and really accelerate that very quickly.
Let's run through all the news you need to know to keep up in the auto industry. Stellantis is planning to invest about $10 billion in the US. That's according to people familiar with the situation who spoke with Bloomberg News.
The people say Stellantis may announce about $5 billion in fresh money on top of a similar amount earmarked earlier this year in the coming weeks.
The investments over several years could be funneled into plants including re-opening, hiring, and new models. The people said it can go to states including Illinois and Michigan.
Stellantis spokesperson told Bloomberg, quote, as part of the preparations for the company's strategy update and capital markets date next year, the CEO is leading a thorough evaluation of all future investments.
The process is ongoing, the spokesperson declined to elaborate. The Times of London reports that JLR is preparing a loan of as much as $674 million to support its suppliers.
Just after a cyber attack last month brought the automakers production to a standstill. The loan is separate from the $1.5 billion euro state-backed guarantee by the UK government.
A phase restart of JLR's global production facilities is due to begin today. Although the Times of London said there was a broad consensus that the company is not likely to be fully up and running again until after Christmas.
And President Donald Trump is considering significant tear relief for U.S. auto production that could effectively eliminate much of the cost major car companies are paying.
That's according to freshman U.S. Senator Bernie Moreno and auto officials who spoke with Reuters. Moreno said, quote, for Ford, for Toyota, for Honda, for Tesla, for GM, they'll be immune to tariffs.
Moreno is a longtime auto dealer from the Cleveland area. He said he thinks Trump will make a final decision soon.
And those are today's headlines. You can find more details on all those stories at autonews.com.
Auto makers are under a lot of pressure in 2025 to cut cost and they're telling suppliers to find ways to be more efficient.
In a few minutes, we'll hear from Magna International's Todd DeVille about how North America's largest auto supplier is using AI to do that.
Joining me now to talk about it is our own John Erwin who covers the supply chain for us at Automotive News.
John, welcome back to Daily Drive.
Thanks for having me back.
So John, you wrote a piece in this week's edition of Automotive News about how auto makers are putting pressure on suppliers to use AI tech and their factories to be more efficient.
We're about to hear how Magna is reacting, but what about smaller suppliers? Are they going to be able to adapt?
Yeah, it's interesting. Smaller suppliers, you know, we've talked about on the podcast many times over the past couple of years or under a lot of financial pressure themselves,
obviously lately with tariffs and those costs, but going back before that to just rising labor costs, various supply chain issues that have really taken their toll on suppliers, especially smaller ones, over the past several years.
A lot of them aren't as well capitalized maybe as some of the larger ones, like a Magna per se.
So yeah, those smaller suppliers, like a larger supplier like Magna, might be under some pressure from auto makers to adapt a lot of technologies that utilize AI to help to make their factories more efficient.
To help data maybe transfer against between auto maker and supplier and throughout the supply chain a little bit more, kind of increasing transparency throughout the supply chain as companies figure out what's going on in their supply chains.
Make sure that they're going to keep production moving, but like I said, a lot of these smaller suppliers are maybe less well capitalized.
They would like to maybe implement some of this stuff if they had the ability, but in a lot of cases they might not be able to, but on their own, but that's where we're seeing a lot of partnerships come into play, you know, some of the larger suppliers are working with smaller suppliers to, you know, maybe help them implement certain things were possible.
Absolutely, kind of a long process because there's so many suppliers throughout the supply chain, but you know, clearly, you know, we've heard from GM, for instance, about how they want to, you know, maybe essentially create a digital twin of their entire supply chain and that sort of requires a lot of cooperation between suppliers and auto makers to make that happen.
And, you know, the CEO of Martin Rea International, which is a large supplier and himself, maybe not on the scale of magna, but a large tier one, you know, he was mentioning how that a recent center for automotive research event, he was mentioning essentially how automakers and suppliers should work with these smaller companies to, you know, help them find resources to implement some of these tools where possible.
Making sure that they know they don't have to reinvent the wheel here, that there are tools they can go out and purchase or maybe work with some of their customers.
So yeah, it'll be interesting to see kind of the pace at which some of the smaller suppliers adopt some of the stuff, some of the concerns they might have about sharing data and making sure that they don't give up any competitive advantages they have as well.
That's an interesting topic that's being brought up, but we'll see what happens.
It's definitely there definitely under a lot of pressure from automakers and even their larger for talking about a tier two supplier, a lot of the large tier ones are also kind of applying pressure on them to adopt a lot of the stuff and I'm sure some of them will be receptive others might want to push back a little bit more, but we'll see what happens.
And you spoke with Magnus Todd Deville on the latest episode of shift, which we're about to hear a bit of what did you take away from the conversation.
Yeah, that was a really interesting conversation. He's basically in charge of that magna of thinking about what the factory of the future might look like.
And for a company like Magna, the largest North American supplier, extremely diversified, they work in some of different spaces, supply for a lot of different companies, factories all over the world.
There's really interesting kind of hear his perspective on what the factory of the future looks like considering every factory that magna has might be kind of set up differently depending on where they're at, what they're building for, etc.
But it makes clear that a lot of the stuff that we've been talking about with artificial intelligence and some of these AI tools, they're not something that's just being talked about.
They can implement it already in their factories. I know it's the case at other large suppliers as well. They're able to spot, you know, maybe potential issues on efficiency issues on the factory floor, sooner than they would have otherwise, or maybe it becomes a product quality.
I've already seen a lot of that and I think moving forward, I think magna and a lot of other suppliers as well, kind of see an opportunity to become even more efficient and more nimble.
And I think that's something that companies coming off of the last several years, with the pandemic all the way through now with changing trade policy, they're really more than anything else wanting to become nimble.
I think they're seeing an opportunity here. Obviously with a lot of these tools, there's always the concern from some about is AI are robotics, are they going to replace labor, human labor, and at least in Magna's case, he had mentioned how for them it's not about that, it's more about making sure that they're re-skilling and training their workforce to be able to utilize these tools so that they can become more efficient.
And that sort of thing, so that'll be curious to see how that evolves moving forward as more of these tools are adapted.
But it was a really interesting conversation again coming from someone kind of in charge of, you know, thinking about how this massive company is going to evolve over the next several years and it should be a good one for everyone to listen to.
Perfect. John, thank you so much for joining me. Thanks so much.
Coming up, a piece of John's conversation with Todd DeVille, Magna International's Vice President of Advanced Manufacturing and Corporate R&D. That's next on Daily Drive.
Automotive news shift podcast brings you the latest on automotive technology, trends, and transformation. I'm Hannah Lutz.
And I'm Molly Boygon. We're the new co-host of Shift, and we're excited to bring you new conversations with experts and industry insiders like this one with Larry Dominique, president of LD Management Consulting.
Do you believe the legacy OEMs are falling into a trap? They've got to find a way to, in some ways, build new airplane while they're still in flight.
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Welcome back to Daily Drive. I'm Kellen Walker. Automakers and parts makers are quickly adopting artificial intelligence and machine learning in their factories, and urging their suppliers to do the same.
On the latest episode of the Automotive News Shift podcast, our own John Erwin, speaks with Magna International Vice President of Advanced Manufacturing and Corporate R&D Todd Deville. Here's a piece of their conversation.
You know, for Magna, what does AI and ML, how are you guys applying that in your factories today? I mean, I feel like a lot of times we've been talking about that as maybe the future, but in many ways this is happening right now.
For sure, it's now, right? I mean, we think of these as theoretical and out there in advance. The truth is, use properly these AI and ML tools are embedded in everything we touch, and you don't even know.
If you think about some of them, you know, some of them, you don't, but think about in the factory, which you asked about vision systems is a big one, an early one, right? Because that sort of came out of early development in the last 10 years, especially, right?
Coming from the tech industry, using AI, neural networks to analyze images, video, et cetera, hugely powerful, relatively low cost, very accessible, something we can use and apply today.
That's in the plants now. Other areas, I would say the emerging right 12 predictive maintenance is there now, a lot of standard analytics can be used where AI comes in is layered on top of that when you want to look at like really massive multi variable scenarios with a lot of data coming from disparate places, the AI tools can kind of augment more classical data analytics tools and providing sites.
So those are a couple of them. And then I think robotics, I'd mentioned right is the vision systems fit into robotics already. So those are running today in many, many places. That is going to significantly magnify. I think over time, as we get out of just using them for vision analysis and start using AI tool sets for things like identifying objects, learning, training, programming, path planning, all of those types of topics.
Yeah, and there's so many applications. I mean, want to delve into a few of these, but we're dealing right now with I think tariffs and everything else where companies are looking deep into their supply chains to learn where their parts come from, where their materials come from, is magnet utilizing AI and able to really dig in on that and how are your suppliers thinking about AI and ML and those applications, maybe others.
For sure, I mean, what you're talking about is getting deep into highly complex data sources coming from many, many different places, the formats are all different, huge issues around just data quality, cleanliness, the basics naming conventions, these kinds of things is enormously challenging. Yes, that's where AI and some of the ML type tool sets can come in to make that much, much easier. Imagine you have millions, millions of data points that don't call it.
It's quite a line in the old days, right, you had to sort of look at the each text and you're looking at the characters and this is the same as this different. Do I need to erase the space or this dash and that kind of stuff. That's where the AI tools sets can come in and really accelerate that very quickly.
So that data cleaning data handling layer critically important, highly labor intensive, but you need it without that you're not doing any of the analytics that comes next.
Yes, that's being used. Then you get into the analytics of, okay, what do I do with this information now getting deep into the supply chain? What's what's coming from where? What's common? What's not common? How do I just use that right?
How is the adoption of AI and these ML tools impacting maybe your relationships or your collaborative efforts with your customers? How are they thinking about this and how are you guys working together?
Interesting question, right? Good question. I think our customers, obviously, we follow our customers as we need to and should in many ways. I think it's the same on many of the AI tools set topics.
And then as our customers need more and more transparency, they're building their digital twins of, you know, well, product engineering are already deeply involved. We use the same tools. We often co-locate, right?
We have to, you got to be right embedded with the customer using the same tools, the same function. So at that level already there, you get into the manufacturing side and you start to want to build for our customers to build say complete digital twin of their operations.
They're going to need inputs from us because there will be pieces of this that only we have only we can provide. Similarly, when you go down to our suppliers and vendors in the supply chain and it sort of works its way down the chain, we have to do this together led by our customers, but we got to move together.
You can hear the full conversation between Magna International's Todd DeVille and our own John Orwin on the latest episode of the Automotive News Shift Podcast. That's available now, wherever you get your podcast.
That's daily drive for today. I'm Kellan Walker. Thanks to automotive news executive producer Jake Near for his help on today's podcast. You can get the latest news on suppliers, US investments and everything happening in the auto industry at autonews.com.
We'd love to hear from you. Let us know what you think of the show on the topics we covered today. Send us an email at dailydriveatautonews.com or leave us a voice mail at 313-444-2774.
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About this episode
Stellantis is gearing up for a significant $10 billion investment in U.S. operations, with plans to enhance production facilities and create new models. Meanwhile, Magna International's Todd DeVille discusses the integration of AI and machine learning in manufacturing, emphasizing its role in improving efficiency and data management. The episode also touches on JLR's financial strategies post-cyberattack and potential tariff relief for automakers from President Trump. Insights from industry experts highlight the evolving landscape of automotive manufacturing and supply chain dynamics.
