Chinese EVs are electric cars made by companies in China. The news is important because it could bring more of those cars into Canada, especially after tariff changes.
Stellantis is a big car company that makes lots of different brands. Here, they’re talking about using one of their Canadian factories to build electric cars.
Deceptive pricing means a seller doesn’t clearly show the real cost, or presents prices in a misleading way. In car buying, that can lead to legal trouble and consumer harm.
Lindsey Automotive Group is a dealership group mentioned here because it settled a case involving claims of misleading pricing. It’s an example of how compliance issues can affect auto businesses.
Artificial intelligence is computer software that can make decisions or help with tasks. The point here is that if lenders use AI, they still have to follow the rules and avoid mistakes that could cause legal problems.
Operational efficiencies are ways to make a business run faster or cheaper. The host’s point is that AI can help, but you still have to make sure it follows the rules.
A “bare bones” assembly plant typically means minimal local manufacturing—often limited to final assembly rather than producing major components. The labor critique implies this approach may bring fewer jobs or less investment than workers expect.
“Tailwinds” are favorable forces that push an industry in a positive direction, and “tariff tailwinds” means reduced import taxes make vehicles more competitive. The segment says the industry lacks these tailwinds, implying fewer external pricing benefits for EVs.
Lindsay Automotive Group is the dealership group referenced in the FTC/attorney general settlement. The segment highlights how regulatory scrutiny can lead to penalties and potential customer restitution when pricing practices are alleged to be misleading.
The Federal Trade Commission is a U.S. agency that helps protect consumers from unfair or misleading business practices. In car sales, it can investigate things like surprise charges or add-ons that weren’t clearly explained.
Mercedes-Benz is the car company behind the investment and production decisions being discussed. They’re trying to build more cars in the U.S. for both sales and shipping.
An export hub is a manufacturing location that produces vehicles for shipping to multiple countries. The segment argues that the U.S. plant in Vance, Alabama can serve both domestic sales needs and global exports for Mercedes’ top-selling model.
Geopolitics and trade are about how countries’ relationships and trade rules affect business. For carmakers, it can change where they decide to build vehicles.
The Mercedes-Benz GLS is a bigger Mercedes SUV than the GLC. They mention it because Mercedes is building multiple SUV models in the U.S. to keep the factories running efficiently.
The Mercedes-Benz GLE is another Mercedes luxury SUV, larger than the GLC. The point in the episode is that Mercedes builds these SUVs in the U.S. to keep production capacity busy.
Utilization is basically how busy a factory is—how much of its production capacity it’s using. If demand drops for one type of car, companies may shift production to other models so the plant stays productive.
Concept
EVs going down
They’re saying fewer people are buying EVs than expected. When that happens, factories have extra capacity, so automakers try to use it by building other models instead.
Generative AI is software that can write or generate content, like text. In lending, the concern is whether what it produces is accurate and follows the rules lenders must follow.
The Truth in Lending Act is a U.S. rule that makes sure loan companies clearly explain loan costs and terms. The show is about whether AI can help lenders follow those rules correctly.
The “prompting paradox” is basically: AI only works well if you give it the right instructions and details. But doing that carefully can be harder than people expect, especially when rules and paperwork must be exact.
When you buy a car, the total cost often includes taxes, title paperwork, and other fees. Those amounts can change the loan calculations and the APR number.
APR is the “price” of borrowing money, shown as a yearly interest rate. It helps you compare different loan offers and figure out what your payments will be.
FTC is a U.S. federal agency that helps enforce rules meant to protect consumers. Even if federal enforcement feels lighter, the message is that states can still crack down.
Before using AI, do a careful check to see where it could cause problems. Some tasks are safer to automate than others, and the risky ones need extra review.
“Validation of fees” refers to using AI as an external check to confirm that fee amounts and structures are correct. In a compliance context, this is meant to reduce the chance of incorrect or noncompliant fee handling.
If something looks suspicious or high-risk, don’t just let the AI decide—add extra review. It’s a way to prevent mistakes from slipping through.
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Welcome to Daily Drive. For Friday, April 3rd, 2026, I'm Kellen Walker in New York City. Today
on the show, Stellantis is in talks to produce Chinese EVs at its idled Canadian plant.
Automakers are bracing for more volatility after a week first quarter, and Lindsey Automotive
Group settles allegations of deceptive pricing for $3.1 million. Plus, senior retail editor Dan
Shine sits down with Sara Milovich from Carleton to talk about the compliance risk of artificial
intelligence for auto lenders. So there is this balance of ensuring that you're creating operational
efficiencies. You're using AI to the best of your ability, but also with this compliance and legal
check that needs to be embedded in it. Let's run through all the news you need to know to keep up
in the auto industry. Stellantis is discussing options for building EVs with its Chinese partner
Leap Motor at its idled Canada plant. The companies are in early stage talks, according to people
familiar with the matter. If they decide to move forward, this would mark the first major
Chinese auto investment in Canada since the nation reached an agreement with China to reduce tariffs
on these vehicles. Uniform Canada's largest private sector union says the prospects of
Stellantis using the facility as a bare bones assembly plant for Chinese EVs doesn't meet
the automakers' commitments to workers. Automakers are bracing for continued volatility
after a week first quarter. Many automakers saw US sales decrease for the start of the year
and the factors that drove that decline, including vehicle affordability, rising gas prices,
lackluster job growth, and decreasing consumer confidence continue to weigh on the market.
And on top of that, the loss of the federal tax credit continues to drag on EV volume,
and the industry doesn't have tariff tailwinds pushing consumers into dealerships.
Consumers face pressure across the car ownership experience, limiting showroom traffic experts
say. The state of the market is signaling the potential for a repeat of 2025's uncertainty.
And Lindsay Automotive Group agreed to pay a $3.1 million penalty to settle allegations of
deceptive pricing tactics. But the group could have to pay more than $75 million in restitution
to customers. The Federal Trade Commission and the Maryland Attorney General's Office
originally filed the lawsuit in late 2024. The allegations include the use of unadvertised charges
on vehicles and deception about add-ons. In the settlement, Lindsay Automotive did not admit
or deny any wrongdoing. And those are today's headlines. You can find more details on all
those stories at AutoNews.com. Mercedes-Benz plans to invest $4 billion into its Alabama plant
through 2030. The bulk of that investment will go into localizing the production of the GLC
crossover, one of the brand's most popular models. I'm here now with our own Erbash Kakarya to talk
about what the investment means for Mercedes. Erbash, welcome back to Daily Drive. Hi,
Kel. Thanks for having me back. Hope you're doing well. I am. Hope you are too. So Erbash,
why is it so important that Mercedes increase U.S. production of the GLC crossover?
So the GLC is a midsize crossover and it is the number two seller. Mercedes is number two seller
in the United States. It's also the automaker's number one seller globally. And the factory
in the U.S. in Vance, Alabama near, in Tuscaloosa County near Birmingham is a major export hub as
well. So the GLC, bringing the GLC production to the U.S. serves two purposes. It creates local
production of one of the high volume sellers that Mercedes has in the U.S. but then it also creates
a export hub, production hub for its number one seller globally. So Mercedes gets a two-fer
by localizing U.S. production here. So what role did tariff pressure play in this investment?
So Mercedes has obviously tries to downplay that as the reason but the reality is that
geopolitics and trade definitely played a role. These decisions to put production in the U.S.
take a while. It's not like it can be done overnight. But Mercedes announced, we actually
reported that the GLC was coming to the United States a couple of years ago and then last year
or rather late 2024 they officially confirmed that the GLC would come to the U.S. So it hasn't
been that much of a lag. We previously reported based on supply chain sources and our conversations
with Mercedes executives that production would begin in late 27. But earlier this week when I
talked to the CEO, Mercedes Benz CEO about the timing for GLC, he said it was more likely now
in 2029. So that basically creates enough of a lag for production to sort of ramp up in the U.S.
which sort of lends credibility to the theory that tariffs definitely drove this decision.
And if the GLC is the number two seller, they would be paying, they are paying
15% tariff on every GLC that they bring in, that they ship into the United States from
Bremen, Germany. So this is a big tariff bill that they're paying. So localizing it makes all the
sense in the world. However, I don't think tariffs are the only reason. I think all automakers want
to build where they sell. And by building one of your high volume vehicles here, they can lower
the cost in terms of shipping. They can avoid disruptions again due to wars or supply chain issues.
And then they also help bring capacity, bring utilization to their existing factory here in the
U.S. So in the U.S. they build the GLS and the GLE along with their electric variants. And obviously
with demand for EVs going down, they're building far fewer of those electric vehicles which has
created more capacity that needs to be utilized. And by bringing the GLC here, they help make the
plant operate at as much utilization as they can, which then makes the plant more efficient.
Perfect. Irvash, always insightful. Thank you so much for joining me.
Thank you. Have a great day. Coming up, we'll talk about if lenders can rely on generative AI to be
compliant with the Truth in Lending Act. That's next on Daily Drive.
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Welcome back to Daily Drive. I'm Kellan Walker. Can lenders rely on generative AI to be compliant
with the Truth in Lending Act? Why lenders are at fault when AI-generated compliance calculations
fail? As AI adoption accelerates across auto-financial services, a critical question is going largely
unaddressed. Is generative AI for Truth in Lending Act compliance quietly building systematic risk
into lender portfolios? Sara Milovich, general counsel and vice president of compliance at
Carlton, spoke with senior editor Dan Shine about how lenders can make sure generative AI
doesn't harm its compliance efforts. Sara, thanks so much for joining me on the FNI Friday edition
of Daily Drive. Thanks for having me, Dan. So AI is the big thing. Everyone's talking about AI and
how it makes our lives easier. And in many cases, that is true. But you have kind of an interesting
perspective that in auto-finance, there are some great things that AI can do. But there's some
cautionary tales. There's some troubling things that when it comes to AI and decisioning and
auto lending, talk a little bit about what you think the issues that loom out there for lenders.
Sure. At the outset, my background is in compliance and legal. So obviously, I'm coming from a very
skeptical viewpoint where I am proceeding with caution. So I recognize the difference between
the hats we wear in addressing the AI concept and ensuring that the legal and compliance aspects
are met as well as business efficiencies. So there is this balance of ensuring that you're
creating operational efficiencies. You're using AI to the best of your ability, but also with this
compliance and legal check that needs to be embedded in it. When we talk about in the dealer context,
there are various different ways that dealers may be looking to use AI. But the word of caution that
I would say is the the role of a human still being in the loop in the process, the role of
ensuring that there is accurate checks in place to make sure that any use of AI still has that
quality check that's being part of the process. I think that is a critical element that needs to
be considered, still be maintained throughout any process that you're trying to build in
efficiencies with the use of AI. There's something called the prompting paradox. Can you kind of
explain that? Yes, the prompting paradox is the idea of always ensuring that your prompt is both
well thought out, that your prompt includes the necessary information, that your prompt includes
the necessary amount of details for whatever context you're using it. And from a compliance
and legal perspective, I offer the caution that the output that you're going to get is only as good
as the prompt that you use. So in a very simple context, if you ask for at work in the world of
calculations, so at Carleton, we're really focused on a calculation engine that does payment
calculations, tax title and fee, but also APR calculations. So in the context of APR, which
you use an AI tool to calculate a TILA APR, and you just simply ask produce a TILA APR
through an Excel file or whatever mechanism, well, AI does not know what context you're
talking in. So it could start pulling in mortgage concepts about particular charges and fees,
that maybe the naming conventions are similar, but the context is so different and can create
differences in how the amortization schedules are run and how the process is done that you don't
even know is an issue that is behind the scenes in the underlying assumptions. That's really the
paradox we have with prompting is the prompts are only as good as the level of detail that you
provide in creating them. Right, AI can't fix an incomplete prompt, you know, or doesn't know
what stage you might be in or doing a loan for, you know, the state-specific
regulatory stuff. And the prompt that you can give, say you're trying to do an amortization
schedule and you give a prompt for creating an amortization schedule. Well, if you don't know
to say whether or not compounding is involved, it can produce a very legitimate amortization
schedule that includes compounding, which violates state law. So although in a different context,
that is a perfectly legitimate amortization schedule, recognizing the differences and the
different rules is still a critical piece in using AI. Yep, and I would imagine things can be
compounded if you're a multi-state lender. Absolutely. Also, tell us how. Yeah, that's
absolutely the case. Not all fees are the same. That's just one simple takeaway. So if you're
looking in one state and the treatment of a particular fee, and then you're looking in
another state, and perhaps the taxation of a particular fee can be different on a state
by state basis. So trying to create rules that are overarching and that would apply to all states
is just ripe for error, because states are so nuanced and complex in how they deal with various
fees, treatment of interest calculations, various components like that.
And I know when we talk a little bit about at the highest level, the FTC and things like that,
and how I think dealerships, maybe FTC is not going to be as enforced as much as maybe in
the past under this current administration. But we always say, well, at the state level,
you have to be careful too. And I would imagine at the state level for this as well, that there
is going to be probably increased scrutiny to make sure that AI is not doing something that is
wrong or illegal. No, you make a great point. The idea that you can ever blame AI for errors,
that's not going to fly with state regulators. So especially as state regulators are handling
more enforcements, are trying to be a little more active, that's what we're hearing and seeing.
But as states become more active in their enforcement actions, the idea of saying, well,
we just use this AI tool to create this process, that's never going to fly. You have to be able
to answer to your calculations, answer to your processes, answer to the reasoning behind those
processes. You can't blame AI for, you know, if the state's attorney general comes knocking on the
door, you can't say, well, it wasn't us, it was a tool. You can try, but good luck with that.
That's legally speaking, that's your legal opinion. Yeah, that's my official legal advice there.
Got it. And summing up this, what advice do you have for dealerships, for lenders,
for the FNI manager out there who wants to use AI and can help him or her? What kind of advice
would you have for them? I think doing a full risk analysis. AI can be very beneficial and very
helpful for various processes. So when it comes to some different potential processes of advertising
scripts or finding markets to target or doing different tools for maybe validation of fees
as an external check, but any area that is high risk from a compliance perspective,
proceed with great, great caution. So there are low risk items that the use of AI is great for
creating some of those efficiencies, but recognizing that there are certain triggers or flags that do
rise to the level that you want to have an extra layer of scrutiny built in in order to ensure
that you're not opening yourself up to risk unintentionally.
Created by Sarah, great conversation, very interesting stuff. Thanks for your time.
Thanks so much, Dan. That's Daily Drive for today. I'm Kellen Walker. Thanks to Automotive
News executive producer Jake Nier, as well as our own Riley Hotter, Irvash Krakaria,
Vince Bond Jr., Larry Belliquette, and John Hutter for their reporting for today's podcast.
You can get the latest news on dealership lawsuits, industry turmoil, partnerships with China,
and everything happening in the auto industry at AutoNews.com. Come back over the weekend for a
weekend drive edition of the show. I'll sit down with our own Larry Belliquette and Jack Wallsworth
to talk about first quarter results and all that happened at the New York International Auto Show.
The consumers that are coming in to buy new vehicles are more what he called have to customers.
We'd love to hear from you. Let us know what you think of the show and the topics we cover today.
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About this episode
Stellantis is weighing early talks with Leapmotor to produce Chinese EVs at its idled Canadian plant, a move that could clash with worker commitments and comes amid ongoing tariff and trade shifts. The broader market outlook stays shaky after soft first-quarter demand, affordability pressures, and the lingering drag from EV tax-credit changes. Lindsey Automotive Group settles deceptive pricing allegations for $3.1 million. Mercedes also plans $4B in Alabama to localize GLC production. Separately, a compliance-focused chat warns auto lenders that generative AI can create Truth in Lending Act risk unless humans, prompts, and state-specific calculations are tightly controlled.
Sarah Milovich, general counsel and vice president of compliance at Carleton Inc., talks about the compliance risks auto lenders are facing when they use artificial intelligence. Stellantis is in talks to produce Leapmotor Chinese EVs at its idled Canadian plant. Plus, more on Mercedes’ $4 billion investment into its Alabama facility.
