(upbeat music)
- Hello and welcome to the Free Find Podcast.
Your source for all things freight transportation.
I'm Chris Campos, Chief Scientist at D.A.T.
Frame Analytics, and today I'm joined by Dr. Jason Miller,
Professor of Supply Chain Management
at Michigan State University's Eli Broad College of Business.
This is Jason's fifth time on the Free Find Podcast.
I last had him on about a year ago to discuss tariffs
as they were impacting the market.
This time I wanted to talk about the current truckload cycle.
We both agreed that it started in December 2025,
but that it took a couple months really through the first quarter
to make sure it wasn't a false start,
like what we saw at the end of 24 beginning of 25.
And Jason notes that this expansion is unique
'cause it's supply-driven,
and it's essentially a mirror image
of that demand-driven bull market that we saw in 2017, 2018.
And he notes that while aggregate demand remains flat,
we are seeing what he turned a feeding frenzy
in specific sectors like data center construction,
steel production, mainly due to the rapidly expanding
D.A.T. center networks that ecosystem by hyperscalers.
And sticking with the AI theme,
we kind of turned the conversation from transportation
to the trillion dollar question of AI's actual return
on investment or ROI.
Jason shared his skepticism regarding the current hype,
discussed the high cost of compute,
the issue of model drift,
and while we haven't seen a true labor substitute in AI yet,
I am more an optimist and think that the cost of AI will drop
and that it is a long-term mass of benefit to the workforce.
But it's always great to debate these topics with Jason.
He always comes with an opinion and with data,
so that's always a great debate.
Whether you're navigating the routing guide failures
that we're seeing now more frequently
or trying to separate AI, hope from hype.
Hopefully this episode gives you some data-driven clarity
'cause that's what Jason always brings
and me to understand where this current capacity driven cycle
is headed.
Following my conversation with Jason,
I will present the truckload market update,
so let's get started.
Hi, Jason, welcome back to the FreeFine podcast.
- Hey, thanks for having me back, Chris.
- You're joining an esteemed crowd, Jason.
You're my third fifth timer.
I've been doing, this is my 178th, 176th podcast
and I've, you joined Bill Cassidy in Kevin's wires
a five time, so I'm not gonna send you a jacket
but I might send you a coffee mug.
So we'll see how that goes.
- Hey, I'll take him and that's awesome.
- Yeah, so I wanted to talk back because as you might know
that the truckload cycle has changed again
and we're in another cycle that seemed to start.
And I wanted to talk to you about that.
And first question is, when do you think this cycle started?
When do you pick the date?
- I ping it as December of 25.
So if I had to say, when did this cycle turn?
It was December 25.
- Me too, me too.
And what is your signal?
Everyone, I've had students look at this
and people have little fine points.
How do you define when the market transitions
from a contraction to expansion vice versa?
- Yeah, so the one index that I've used a lot
is basically just taking DATs, contract rates, spot rates.
And if you do contract minus spot over the average
of the two, there's seemingly has been
this magical 10% threshold that whenever you sort of
dip below that significantly,
that's when it seems that a market has flipped.
- Yeah.
- And so in retrospect, that's when it flipped.
I don't think any of us really started to feel confident
though saying the market had truly flipped
until probably I'd say mid-February or even March.
And the reason was as we had,
you've always got the December holiday tightening
moved into January and it actually felt like
it was loosening a little bit.
And then you had some really horrible winter weather.
- Right, right.
- And so that then created the,
well, maybe it's the winter weather narratives.
And that was late January through like mid-February.
And then things just never really started
to sort of loosen up again.
And actually started tightening more and more.
And so that's when it felt,
certainly by March it was okay.
We are in the January, February time.
We're concerned, is the tightening due to ice
or ice the weather or the border control stuff
that it's freaking people out.
And seemed like it was a coin toss.
But go back to December of 2024.
To me, that felt exactly like December of 2025,
but it didn't have the stickiness.
In January, once the new administration came in,
the tariff started hitting and it just dropped.
But it seemed like we're in the exact same spot,
but then it just changed.
What do you think happened in 2004,
the stopped air 25 rather than it stopped it
from turning to the cycle?
- Yeah, so you were starting to see sort of a nascent
manufacturing recovery, you know, December 24, January 25.
And then you just had the tariff.
And I think even more so is the tariff uncertainty
that caused sort of not much chaos.
Because at the end of the day,
the tariffs have generally proved to be much more bark
than actual bite when you look at where effective
tariff rates actually settled in at.
And so I think what you had was sort of a big cap X pause
by a lot of firms, you didn't see the machinery demand
and things like that.
And through most of 25 that we would have expected,
plus you also had just this continual decline of capacity
all through 25, even setting aside any type
of English language proficiency in non-domicile CDLs.
And I think part of that was a lot of carriers entered 25,
thinking this is the year it's finally gonna turn.
- Right.
- And then when that didn't happen,
you started to see operations that were borderline
just finally closed up shop.
And so, you know, when I look right now,
you know, freight volume today isn't much above
where it was in 25.
But supply is down, you know, several percentage points.
And so I think we finally sort of just tipped over
that threshold where you start to see more routing guide
failures and we have so much more pricing visibility today
that, you know, once it became clear that spot prices were higher,
you started to see a quick adjustment of bidding behavior
by carriers and then that starts to, you know,
build the feeding frenzy cycle.
- Right, right, let's, before we get into the driver exodus,
'cause I wanna talk about that, this cycle,
you made a reason LinkedIn pop post that said,
you thought this looked like the 2017-2018 cycle,
which lasted what, 48 months?
Is that right?
Or four years, three and a half, something like that?
What makes you think it looked like this?
And what does that have to be?
- Well, so I'm saying it's the mere image of that
because 17 and 18 was all about demand growth.
We were seeing one in debt, I co-author,
trucking Tom Milindex, that was growing three to four percent
in 2017, then through most of 2018.
And then it really, growth really started to cool down
in Q4 of that year and then 2019 was flat.
And so when you look at sort of that expansionary cycle,
I kinda date that from a pricing standpoint,
from about June of '17 through,
if you wanna call it October of '18 or December of '18,
that's kinda your somewhere between about a 15 to 18-ish
month bull market.
But that was almost all demand-driven,
little bit of supply-driven with the ELD mandate.
- ELD, sure, sure.
- But not much.
This is the exact opposite that we're in,
and that this is 90% supply-driven
and maybe 10% demand-driven,
but it's not aggregate demand.
It's demand for certain goods.
So it's the data center build out.
It's the AI ecosystem.
Because we'll see sectors right now.
Construction steel production is up 8%, 10%
from where it was last year.
But major appliance production is down 6%, 7% from last year.
And so you've got a lot of sort of the imbalance issue,
I think from what carriers we're expecting
heading into this year.
- But so that's a really good point.
I think we all agree this is a capacity-driven cycle,
but usually which one ends faster,
because when the price is going up,
a lot of capacity is just parked, right?
A lot has gone out and we knew,
we'll talk about drivers in a second,
but a lot of that can come back in rather quickly.
Do you think that what's the fundamental differences
between a demand-driven cycle
and a supply or capacity-driven cycle in your opinion?
- Well, so we've never seen a supply-driven cycle like this.
Like if you go back and you look back the last 30 years,
every expansionary market was demand-driven,
whether it was the 1990s.
It's '04 through about '06 with the housing boom.
You know, the '13, '14 fracking boom.
And so it really comes down to, I think, assumptions
folks make about where capacity can come from.
The view that this is going to be a very long-term,
expansionary pricing cycle because supply will be constrained,
seems to operate under a lot of assumptions
that a lot of the driver pool is immigrants.
They're going to have a harder time getting jobs
with this administration and the rules in place,
and therefore you're not going to supply come back as fast.
I tend to be a little bit more skeptical of that
because when you look at the studies
that have actually been published
of where the truck drivers are,
come from using the current population survey. So sort of the big survey. The Census Bureau
does to track unemployment. It suggests that there's a lot more nuance to this. A lot of people
that get into trucking are folks that worked on loading docs and they see the drivers interact
with them. They learn through whatever mechanism that, hey, the market's really hot. It's a good time
to start and say, hey, I'd rather be driving a truck than driving a forklift. Folks lose jobs
in manufacturing. Folks lose jobs in management and they go become truck drivers. And so when you
look at, there's a good paper by Berks and Monaco that's a public domain from the Bureau labor
statistics from 2019 that really kind of lays out where the drivers come from. And you don't see
any evidence that it's, you know, a disproportionate immigrant pool. And so I, that-- So anything that's
just an inflation of the popular press because a lot of the press coming out, you know, you have all the
videos come out and it's like we're being swarmed. So that's just an exaggeration in your opinion.
So I think that probably on the margin, you had a lot of capacity that grew and, you know,
more recently through the cycle that may have been a little bit more from there. But it's
important for everybody to remember, you know, we had, you know, because of COVID, there was a large
scale sort of crackdown on immigration. Sort of through that same period where trucking capacity
was growing a lot. That's a good point. You know, so, so I am just, to me, this is always just
supplied demand. This is just market dynamics. And this is where I really like to look at sort of
class aid orders. And where you look right now, I mean, they're high. They're, you know, more than
double where they were last year. And since December, they've been well beyond replacement level
of new trucks. Now, how much of that is due to emission standards changing? And that's where we
don't know. Okay. And so that that's the challenge. As we don't know how much of this could be in
emission standards. But my, my sense is is, you know, if you look, the correlation between year
over year change and line haul spot rates and new class aid orders pre COVID when I was like
0.9, we're pretty much back to where that was. And so I just have a sense the capacity will start to
make its way online, maybe Q four of this year. And through next year, because from a carrier
standpoint, I just think there's such a, you know, economists have called it an expansion drive.
There's this desire to grow. And for carriers that are out there that currently can't
service all the demand they're saying, it's hard to tell your customers, hey, I'm, I'm sorry,
I can only take 80% of your tenders. Because what's going to happen is next year that shipper's going
to say, look, I want 95% or by God, I am going to find somebody who is going to give me 95 plus
percent acceptance. And so you run the risk as a carrier that if you don't expand to meet that
demand, you may lose that shipper. Yeah. You know, this raises another question. It's really taking a
left turn here. Routing guide compliance, to me, I've been studying this and doing this stuff
since the 90s when I started doing bidding to create routing guides. I think that they're
fundamentally changing now about 30, 20% higher of different industries. The freight doesn't even touch
a routing guide. It goes straight to whether it's API or something informal. It's going straight
direct to spot, a directed dynamic call it whatever. So routing guides, since they're getting a lot
of the infrequent freight is not touching the routing guide, the routing guide compliance by nature
is going to be more consistent freight. So it's going to get better now anyway. So what are your
thoughts on how this whole idea of measuring routing guide compliance to me? That's like a partial
picture of it. No, I think you're making a good point. I think it too depends on the extent we're
calling compliance shipper to carrier versus shipper to broker. And so, you know, because to the extent
that we're having brokers turn down loads, because maybe they can't find capacity at that,
what that line hall rate is, that I think does provide at least a little bit more information.
But I mean, we're even seeing that now. So, you know, I've always liked freight waves,
tender rejection rates. And if you look right now, they're, I think, 16-17%. But if you go back and
look in 2018, they were 25% when they started publishing the data back in March of that year.
Right. And if you look at 21, they were, you know, tender rejection rates were 25 to 30%
through much of 2021. And so, this is where I, you know, it's tight out there. But I think from a
purely, I need to find a truck. I do not believe it is tight as tight today as it was back in the
worst of 21 or the worst of 2018. And so, I think it's another, you know, it's another metric
and that we have to put together. I haven't seen with CHR's most recent sort of average tender depth
indexes at. See, that's another one that's just because a lot of people, I mean, I've done a lot
of work with CHR over the years. And it's all out there and it's public. But the depth, they used
to go to 12, 13, 14. Now they, they pull the, the rip quarter three. So naturally, the long tail's
gone away. Because if you're waiting beyond the second, third, you're going to go to a different
mechanism now. I think technology has gotten so much smarter in real time that you don't need to
rely on that waterfall method for everything. So I think it's really changing the metrics. But we'll
see, we'll see how that changes. No, and that's one reason for me. I've like to, you know, rely on
dad's data, just doing, you know, contract minus, but because that's at least pure rate based
at that point. So it's hopefully a little bit less sensitive, even though again, it's not,
not maybe a perfect basket, apples, apples here. And you know, there's, there's no doubt like it is,
it is tight right now. I do, you know, is we're filming this and, you know, middish to late June.
It does seem, even though we're approaching fourth of July, it does seem that we're starting to
ask him to bet on rights. And yes, diesel, diesel's come down a bet. So why overall line haul is
likely up, but we do seem to be running into some resistance right now. I, you know, it's funny,
Jason. I was just running numbers this morning that comes in. It came in at Saturday as of that.
We do it every every week. We just look at the real time, even though we know it's going to bounce
around because stuff comes in. And I'm seeing exactly what you just described, especially for
reefer, reefer tailed out a little more. Now, new rates coming in in contracts are going through
the roof still because of exactly what you said in the beginning. But let me go back to the spot
versus contract because I also look at spot premium ratio, which is, and when we define spot
for DAT, the shipper side, it's, if we haven't seen the rate more than four days. And so we don't
rely on the shipper saying, yes, this is spot or not because they, they, every company has different
policies. So it's more dynamic. And when I look at as a spot premium ratio, and it's exactly what you
said when spot goes above contract, I don't even look at the 10% and this is all shipper by whether
from broker from carrier. But the point I want to make if I look at the last three cycles, the spot
premium ratio peaked out at about 25% each cycle. It's pretty start there. And right now we're
around 10 15%. So it looks like we have some headroom. But as you said, this is a different kind of
cycle. So I'm curious how far up do you think it's going to continue to go? Or do you think that
spot's going to start? It's going to start closing. I mean, so the challenge is like June,
this is end of quarter loading right now. We're getting around for fourth of July. We've got a
little extra freight moving because of fees and the world cup here right now. Because even though
folks would not necessarily think that generates a lot of freight, it does. I mean, people are eating more,
they're drinking at bars, things like that. Let me tell you about Boston. We're inundated with
Scott. And they were so much fun. And that whole thing about we ran out of beer. It's true.
It was the same Adam's brew house and familial hall and hensys right there. They literally had four
times the demand for beer than they do on St. Patrick's Day, which is insane. But there were so much
fun. So many skirts, so many quilts in Boston this last couple of weeks are very fun.
So this is the thing right is once you get past July 4, you got the auto industry goes into
model change over. So July tends to be a fairly weak month for overall freight demand because of
the auto sector being at the lowest capacity it is through the entire year. You start again past
peak summer building season. So we're going to start to see single family starts are going to
decline. So that means less bricks and things like that. And so, you know, my concern right now,
and is I think there's a decent chance that we're probably towards the spot peak right now at the
moment because you know, for up until maybe again, a December period, but that's just pure seasonality.
Because the challenges right now is it's difficult to see where there's an influx of freight
demand that is going to happen that is sustained. You may see an early peak season for containerized
imports because folks are going to try to run stuff in before whatever new set of tariffs are
going to kick in. But you're not going to have single family housing dramatically change this
year. You're not going to have discretionary consumer spending on furniture or major appliances
or motor vehicles. That's not going to change this year. What about back to school? That's just a
little blip. I think that's not that much. And you know, you're going to have, I think again,
cautious consumer. I mean, look at the technology products and how those are going to become more
expensive. I mean, you've had Wall Street Journal talking about iPhone 18 is going to be, you know,
a couple hundred dollars more.
expensive than what iPhone 17 was because of the memory shortage.
And so you're going to start seeing, you know, back to school, think of the electronic
side, a lot of Americans are going to have some sticker shock because tablets are more expensive
and all of this stuff.
And so, you know, I think the thing is, is when we started the year, we were all expecting
a couple of interest rate cuts, maybe two to three.
Now than most likely movement is going to be an interest rate hike at the rate where
I don't know.
So explain, you're an economist, I'm just a dumb trucking guy.
Why are the rates going up?
Was it employment?
What is, what is causing it to go?
You've had a huge energy price spike and even with, you know, futures prices accrued
oil right now.
I think they're around 75 issues were filming the set still way above where we started
the year at.
And it was really expecting oil to be around 75 and, you know, you've had a big impact
on the petrochemical ecosystem, you know, so you've seen plastic prices go up.
This stuff's got a filter it's way through.
And again, you have this dramatic, you know, memory chip shortage that has caused prices
to skyrocket and that's making its way into essentially so many not only consumer electronic
goods, but also producer goods.
And what's driving the memory chip shortage is really being driven by the AI data centers
sucking up all the other chips.
Yeah.
Exactly.
You've got, you know, as you're having so many so much GPU demand and things like that,
you have, you know, essentially what I'm going to say is a almost price insensitive set
of buyers and the hyper scalers that are buying Davidia GPUs because they need Davidia GPUs.
And therefore, Davidia is having to have Foxconn or and Hanhai precision build more of those
GPUs.
And that's just pulling all this memory demand and there's basically three memory producers
in the world.
You got SK Heinix and Samsung, which are South Korean and you got micron, which is US.
And so you just have essentially this almost insatiable demand that is pulling all of
this memory capacity and it's leading to massive price increases.
Now, do you think that's a short term when I hear about all the hyper scaling you read
about all this, I have thinking I think back to 2000 with global crossing and all the
fiber build up where they kind of, you know, overbuilt because they assume price would
be a certain thing and it collapsed, of course, but that capacity was used eventually.
So do you think the same thing is going to happen here because the AI, they seem to be
over building like there's a race and I don't think there's going to be a dominant AI.
I'm curious what your thoughts are, but it seems like the capacity is being way overbuilt.
So I mean, it feels a lot like the late 90s telecom boom, you know, you know, ecosystem
boom, you know, in a good example, this is production of energy wire and cable that is
actually an industry in the U.S. production peaked in 90, 90,000.
It's three times where it ended up being in 2017.
So you can imagine we're sitting so high it collapsed.
It never has even remotely gotten back to that level.
And so that's not even a global sourcing situation.
That's a, we just overbuilt, but that's, but, but that capacity got consumed.
I mean, that enabled other things that we didn't see coming, right?
And so this is the question I think in the AI space is what good is a data center for
other than running, you know, LLMs, you know, agentic AI?
And this really comes down to the question of can, you know, I mean, you know, being realistic,
there are two, you know, AI shops out there that really matter, open AI and anthropic.
Like those are the two that matter, no offense to Grock, but no one cares about, you know,
that AI, or, you know, some of these other more micro ones in the U.S.
So it's really comes down to open AI, you're discounting Google, just out of the box.
So I mean, Gemini is a decent platform, but when you look, I mean, that this all depends
on really can open AI and anthropic be profitable.
Yeah.
That's what we don't have an answer to right now.
You know, open AI's financials got leaked and they were burning a lot of money last year,
depending on it.
I'm shocked.
I'm shocked.
And I mean, we're talking burning money that is exponentially more than what Uber burnt
at the start of, you know, essentially trying to scale that business and create the network
densities and what, you know, Amazon did creating Amazon web services.
And so the question really is going to be, will customers pay the cost of compute, you
know, Wall Street Journal recently had a story that both anthropic and open AI are looking
at lowering their prices after they had raised them to a lot of, call them industrial customers
through the token-based billing, because folks found out, hey, we were spending, you
know, per engineer, $100,000 a month and somebody goes, ooh, where's the ROI on that right
now?
Yeah.
And so I think that, you know, that is the, right now, multi-trillion dollar question is,
because that, the build out of the ecosystem to support this is really supporting not just
the U.S. economy, but a substantially important share of the freight market, hauling the steel,
hauling the building materials, hauling the trade, hauling the transfer.
And so any slowdown to this would be, I think, catastrophic to the freight market and
the overall economy.
The challenge is it's about growth rate.
And I don't know how much more growth rate there can, there can be, you know, I think
the question is just going to be, you know, once these companies go public and which they're
looking to do in their share, right, right, is, do we start to see signs of approaching
profitability in a reasonable time period?
That's, that's, that's a big question, but two, two things that I want to raise the point
one is when the price goes up, I mean, the price, the token, the cost, the token is going
down dramatically because the pressure is on, right?
And so there's a lot of, we're so early days, three years ago, we didn't know where we'd
be now.
And I, I'm thinking with three years from now, but I think the price, the token is going
to continue to drop because we're much, there be much more clever.
And something way expensive and is limiting, you're going to put a lot of time into it.
But the second thing, I have a hypothesis, I'm curious what, if you would agree with me
or probably don't, one of the things that's happening is the electrical grid can't support
what's currently being put in, much less the EV transition for trucks, cars and all that.
My hypothesis is because we have these deep pockets of money right now and they're investing
into the electrical infrastructure, 20, 30 years from now, we will have cheap, plentiful
electricity because of this over build.
And a lot of the investment is going to be put in that we will then use for other things.
So what do you think about that, that the, the AI revolution is really funding the future
of solid, solidification of the grid in the US.
So what matters is whether those investments in the grid can be you, it can be essentially
that electricity can be transferred elsewhere.
So I'll pick on the state of Texas, right?
Texas is basically its own island.
I got my masters there, be careful.
Hey, I mean, I'll come horns now, but you know that.
So I think that it will, on the electricity side, it will really depend on again, the flexibility
of being able to move those electrons, potentially elsewhere, if needed.
On the AI side, the big question, you know, the questions I have is one, as will the cost
come down as use increases.
That is, I think that is the most important critical thing because the one thing for
everybody watching to understand is you can't just make one of these models and just, it's
not like a piece of machinery, the put in a factory, it's installed and then it just
operates.
You have to continually maintain this to make sure we don't have something called model
drift.
That is very different than as you think about maintaining machinery where, you know, your
machine is not going to drift as it ingest more information into it.
So this is a shockingly cap X intensive sector.
And so the real question is, is will people pay the amount of money this cost?
And so it comes down to, is AI a true, you know, truly revolutionary or is it something
kind of just like a different form of software, in which case we should not be pouring trillions
of dollars into it?
Yeah.
You know, I hate to say like, I'll pick on content I see on LinkedIn.
You can tell what say I generated most of it ain't very good.
You know, you can look at a graphic and say, oh, that's 100% AI is an academic.
I can read when people have used AI to write reviews and it's typically not very good.
I can read papers and be like, oh, this section was written by AI and it's not very
good.
What are your tells or can you not tell us?
Also, I mean, on academic papers, so tends to be certain language cues with how it's
written.
It'll wrap around itself, the logic continually.
And so it'll pick certain words out that show up a little too much.
Right.
The damn thing, I'll just hallucinate and create citations that don't exist.
That's, that's, that's my fear.
one of the words that I've seen is
delve. Yep, AI loves delve. Well, the thing is too, as you know, as an academic, when
you submit certain journals, you'll be sure to put in certain citations that you know
will appeal to them. Yeah, it won't, it won't do that. So I'll look through a citation
list. I'm like, man, you would never have found this. No, nobody submitting to ex journal
would ever have cited this completely unknown work. And so you like, okay, the, the, this
thing went out, you know, that's, that's like sloppy AI use. They're still good AI use,
but I have to give you a story. I looked at, I was reviewing a paper and they've cited
me in something with someone I've never heard of. Apparently we wrote a paper together
in 2017. And it was like, no, this is wrong. I don't know where this came from. But, but
this so is the reason I let it go through because I got the citation, right? That's what
I should do. Oh, yeah, yeah, I got a lot of, we keep track now. But the, here's the thing
though is what you're describing Chris shows you use it. But then you have to go put so
much work into it. You then ask yourself the question, was I better off just doing it
myself in the first place? Sure. And so that's where I think, you know, when you talk, when
you see a lot of this, the question is, is will it get progressively better or not? Because
again, all LLMs are doing is just predicting the next thing that's most likely on a string
of text or filling, you know, and so that's, that's from me sort of my, my concern is that
I think people are fascinated by this because it's new. It's the exciting thing, right? I mean,
this is it, but it will it deliver the value. That's where I don't know. And yes, you know,
you know, you know, and the trucking space you're seeing interesting applications talking
to brokers. Okay, we use adgenic AI to contact carriers that we've not talked to for four
hours to get an update on a load. It's like, okay, that is a, that is a valuable use. But
is this something that we as a society should be spending trillions of dollars for to basically
have that type of substitute? I don't, that's where I get a little bit more worried. I also
think what's gonna happen for a lot of companies that think, Oh, man, we can use AI to replace
our entry level workers. It's like, Oh, so you think entry level workers only do these
little things. I can't wait till senior managers actually have to go check this stuff and
realize like, Oh, man, I, I, I don't know about this. And I'm not sure that this thing is
done at right. And now who goes and checks it. And that's where, okay. So great story came
out of the Wall Street Journal today. Actually, they saw it. I don't know if you saw it where
someone from an editorial and talked about how actually AI is helping younger employees
make it have a bigger impact. And the idea was that enables a young employer doesn't need
to wait for to get gain this experience and whatever they can actually apply some things.
They're only limited by their curiosity. And I'd be, and also they're much more, I, you
know, when you get more senior, you have, which you must have, you have doctoral students,
you have had other people working with you for this stuff. And you've gotten to a level
to have that. So someone coming in, this is an assistant, if it's used correctly, that
gets maybe doesn't do the final product, but gets them to use tools, use things they
haven't had to have the experience to actually take years to collect.
I mean, my, my response to the WSJ on that is wire college students booing people when
they talk about it at commencement, because they're stupid. Yeah, I'm a lot of things.
Yeah, nobody, nobody to quote Ed Zittron, who's a fairly, you know, popular AI skeptic,
no one booed the automobile and air conditioning. Yeah. And so, so that's where I'm just, they
boo, busy calc. I don't know. I don't know. You got to look at these things.
That's where again, I'm, I'm, you know, I'll put anyone to the right of center. So
I'm going, let's get real here. Now, well, I guess my point is this is that while what
you're saying may be true, that's not how employers are going to, a lot of employers are
going to view this. They're going to view this as, ooh, I can substitute labor for machinery.
And I, I just didn't going to guess they're going to find out that it's not going to work
well. So, so here's, you know, some examples, some of the law cases where you've had AI
clearly being used to write it and it's created phantom citations to the point where judges
are saying to the federal government, what are you doing? Like you've submitted legal documents
with it with phantom citations. Like this is, and you know, stuff like that can cause you to lose
court cases. And so I think that that's going to be the issue is to the extent like hallucinations
are part of this process. They're not part of the normal human decision making process.
Until we figure out how to get around that when a hallucination could cost you, you know,
hundreds of millions of dollars, it's going to make that substitution more. But, but don't you
think the hallucinations are a growing pain? I mean, look at it was three years ago. When
it first came out, it was crazy what you could do with it. And now it's gotten smarter. And we're
smarter too, because if you have two different models, cross-check each other, the probability
of hallucination on both is very low. So they're, we're learning that stuff. I think something that
you've said earlier, you see the AI slop in your domain. I do a lot of like AI music because it's fun.
I can create songs and I don't play an instrument. But you can tell. And younger generations
have a near for it. Just like we have an idea, you know, we can filter through stuff that our
parents or grandparents probably would have been hoodwinked on. So I don't know. To me, the hallucinations
are growing pains. We're getting over that. So the question that is, again, it goes back to cost.
If you're now having to run two models to cross-check each other too on how much does that cost
versus, again, just having a human doing it? Yeah, but the cost of doing computing in early days
was tremendously high. And now that's gone down. So I think the cost of doing this analysis is
just going to drop. It's just going to continue. And that's the question is, will that cost come down
to justify it? And so this is where, you know, again, we have, there's no doubt the infrastructure
build out is assuming incredibly wide-scale adoption. But the only way to have wide-scale adoption
is for users to eventually put an ROI to this where it makes sense. And you know, the challenges
is right now the subsidization that is taking place for the average user. So I think the numbers I heard
were for chat GPT for the $20 a month subscription. If you have one user maxing out their tokens,
it takes 35 non-using accounts to basically make up for that. So they're basically subsidizing
that user 35x times. Absolutely. That can't continue. But then you have to ask somebody, okay,
rather than 20 a month, let's see, I'm just sitting here because I just don't do mental math
anymore, 20 times 30. At $700 a month, that user's not going to pay $700 a month for this. That is
almost a car payment nowadays in this country. Right. Right. And so how do we make that work out?
And yes, again, Uber subsidized on the ride sharing piece. Yeah, you could drive across San Francisco
for five bucks. That was not profitable, but that was inherently a network based system where you
had to come to scale on the demand and the supply side to make it work. But the economics were
super, super, super clear. So look, look at this. I see, I mean, who are the big players right now?
They are so flush. Right. They've got a lot of money now. Will they all survive doing this?
I don't know. But do you think one, two things? Do you think AI is just going to go away? Or do you
think it's going to settle down to one dominant one or some other few? What's going to happen five,
10 years from now? Do you think I so I think right now we are and you know, if you look at the
gardener's sort of hype cycle, we're on the trending up piece. I think we'll get to the disillusionment
piece within a year or two. I think you're going to probably have specialty AI's for different things.
I mean, you'll have one that's more focused on clothing. You're going to have one that's more
focused on health and medical and you will have that. So it will be a tool, but it will be like
computing. You know, it'll be like industrial machinery and factories. You know, when you look
at the US, we effectively automated away most manufacturing jobs that can be automated by,
I'm going to say 2010. And the reason I say that is if you look, you had these, you know,
sort of secularly, the big recession in late 1970s, early 1980s. A lot of very inefficient
plants got wiped out that were more labor intensive. 2001 recession did the same thing. 2008,
nine recession did the same thing. But if you look, that's kind of a manufacturing employment
in this country, bottoms out. And then it starts to climb back upward a little bit. And so,
you know, you've had, you know, essentially you sort of asymptote to the extent that you can
reasonably replace, let's say labor. I think that what we'll find is that AI is not the replacement
on the labor side that we thought it was. And because of that,
that is going to affect how much money companies can spend on it, because if it's not that
labor substitute that we think, then clearly we can't be spending, you know, there's
no companies that once were on token basebell and that are going to allow engineers to burn
$30,000. I agree, I agree, but to me that's, we have a lot of big companies chasing and
they think there's going to be a winner, a couple of winners, and they're betting all
for it, and there will be a fallout. They're just will. But I think at the same time,
the cost per token, I will make a bet with you. I don't even know what it is right now.
I don't know what the general market cost per token is. If that's the metric that we're
going to use going forward, I think it'll continue. There's got to be some correlation
to Moore's law. It's going to keep dropping, because we're not even, you know, when new
things happen, you don't try to be elegant. You just get the done. And now, when the focus
on cost, you get more elegant. And there's a lot of different ways we're not doing
just stupid searching. You know, it's more selective. You're doing pre selections for
these kind of things. So I think you're going to see a drop dramatically in cost per token
at the same time. But I agree with you, there's way overbuilt. But is there any silver lining
to that overbuilt? So where I would, where I would push back is it on the, it will get
cheaper. I mean, it's the point if you didn't go. No, no, no, it's just if you look, for
example, the, the producer price indices for stuff like semiconductors, that adjusts
for quality change. Okay. And yes, that plunged down. If you go from the 1950s through about
2019, it drops and it drops very sharply. It has been rising ever since 2019. So that
is telling you cost increases are over, or overwhelming, or should say price increases
are overwhelming, any additional quality improvement. You've now seen, because of the memory
shortage, this huge explanation upwards of that producer price index. And so the challenge
is that I see is how does computing become cheaper when you have GPUs, you know, costing
more because of memory. And so the challenges now is we've created such an insatiable demand.
We've pulled up the cost of all the material needed for the compute that it's hard to see
how that becomes cheaper any time soon, plus you're pulling up the cost of electricity.
And so that to me is going to be the big question is, you know, we've basically seen a sort
of a crap, you know, for lack of a better term, quality gains, overwhelming price increases,
and that has stopped in semiconductors even before this. And so that's where I get more,
you know, more questioning on that. It's the same thing the consumers experiencing, right?
As we're starting to see those consumer electronics becoming fundamentally more expensive
even holding quality constant because of this.
But I think it doesn't just get into, okay, if the price of any input goes up, then we
start using other inputs, we start looking for other things. And I'm not saying we're
going to have a difference of chips. I say the software, the way we're using it, we're
going to be clever there because we're not being clever right now because efficiency
is secondary at this point. They're just grabbing market share. But as soon as the focus
gets to be, hey, don't run the full model every time. Let's be a little more selective
on it. And there's a lot of work going here on that. And I think it's, to me, it's a
basic economics as a non-economist. When the price of something goes up, you look to use
less of it, you divert it, you try to find a better way to get that end result you want
using other inputs. No, absolutely. And we have, of course, you're going to see efforts
to that. The question is, yeah, really can't be. So I mean, and even tying it back transportation,
think about right now, you know, Intermodal and 26 is Intermodal in 2018. When you count
container and truck trailer, if you look at just container, you know, it's, it's higher today,
but that's because truck trailer, you know, there's less trailer on flat-car today because that
doesn't fit precision schedule railroading. But, you know, if you think about it,
modally from a transportation standpoint, you know, that we will see shifts over better
at the end of the day. There's a lot of structural constraints that are on systems that, hey,
you can't, can't lower costs anymore. You can't, you can't do it this way. Sure. And so,
that's really the question is how much room is there to change this in that AI space versus
are you hitting some type of, you know, physical physical constraint within the system, you know,
take, again, motor vehicles produced in the United States. We have physical constraints because
of our costs of inputs where we are not going to produce as cheap as Japan or as cheap as South
Korea. We literally cannot do that. And it no mound of creativity can overcome that issue.
Sure. And so, that's where, I know, it's going to be interesting.
I think AI is a little different in this respect. To me, it's a, but we'll see, we'll see how it
comes out. But I'm not saying we're going to have not suddenly new chips or anything, but there
is a lot of push on changing the way that we can use existing inputs. But let me change the topic
totally. I want to hit this before we're almost out of time. You were appointed by Governor Whitmer
to be on Michigan's commission for logistics and supply chain collaboration through 2029. First
congratulations. Thank you. And tell me, what does that role entail? What will you be doing for
Michigan? What is the, what's the objective here? So it's part of a group that is, you know,
sort of cross functional backgrounds. A lot of my role, we just had a meeting
earlier this month or quarterly meeting. And so for example, I sort of delivered a presentation
on sort of the state of manufacturing of Michigan because when you think freight generation,
it's still mostly manufacturing. And it's really, you know, trying to level set for folks and
thinking about, okay, where are their opportunities? So one of the conversations that came out about
that is Michigan actually has the second most diverse agriculture of any state in the country
outside of California. Yeah. How do you measure diversity? Different different types of products
grown and things like that. This is something that our, our ag folks have quantified. And, but the
challenge has been as historically Michigan was not that big of a food manufacturer, even though
we had all of these products. But if you look over the last decade, food manufacturing has actually
been the fastest growing manufacturing sector in our state. And it's the only one that I can point
to and say employment today is higher than in 1997. It's the only major manufacturing sector in
this state where we can say we employ more people than 1997. And so, you know, conversations like
that sort of provide a starting point say, okay, are there more opportunities to essentially get more
food manufacturing in this state by explaining the value to different constituencies, helping small
businesses that are maybe producing in one site, could they expand to a second site? So I view a
lot of my role as kind of bringing sort of the data piece. You know, same way it also allows me to
be networked with folks to say, okay, Gordy, how bridge, what are the economic implications of that?
I'm the person that can provide the trade data to say, look, this is what comes in through the
quote unquote port of Detroit. We can start to get a sense of these are the shipper verticals that
matter the most on an import side and an export side. And we go from there. So a lot of how I view
it as it's bringing, you know, data to these conversations and simplifying folks's life. Otherwise,
trying to find somebody who could collect, where's all the import data coming from? Well, I know how to
use a Census Bureau's USA trade online. That's great. So is this your first step for political
officers? Is this just something to apply data? My time as department chair was enough politics
for me. Thank you very much. I did my three years and let me ask a question about the food
manufacturing. Because that's really interesting. Do you think that's because there's less automation
in food manufacturing than in say auto? Or do you think there's something inherent?
I think part of it is certainly the automation piece, you know, the end of the day Michigan's
manufacturing and Michigan, you know, just huge drops after 2000. And most of that is industrial
robots because NAFTA is 1994. You can't blame NAFTA for magically hitting seven years later.
That would not fly from a from an explanation standpoint. So I think that's part of it. I think
it's more again, more plants, more, you know, diversity of food in the US has been continually
increasing. And so I think, you know, you have again, manufacturers taking advantage of being
close to various, you know, sort of diverse sources of of prod of inputs. And so I think that,
you know, there's a lot there. You know, cross-border trade has been immensely beneficial for us.
Canada provides a lot of agricultural inputs as well. How much of a hit has that taken over the
last two years? Um, so I know bourbon isn't going north anymore. Yeah. So it really depends on
whether it's stuff that's been targeted or not. So, you know, food imports from, you know,
from Canada that are coming in US MCA or, you know, tomatoes, things like that. Not as negatively
affected. Certainly has been a negative effect in the auto sector. And you know, we even see that
nationally, our imports of motor vehicles are down about 15% from where they were in 2023.
But our exports of motor vehicles are down 30% from where they were in 2023.
Um, and so,
This is where I'm gonna say there's, you know,
the challenge has been with the tariffs
is just making us more insular as a nation
because we're not only are we seeing less imports
in certain categories,
but we're also seeing less exports.
- Yeah, so I wanted, this is unfortunately,
I didn't get to half the topics I wanted to.
We'll have to save that for another time
because the whole import export
and how that's changing with a tariff impact
is a whole 'nother podcast.
But Jason, thank you so much for joining me today.
I always learned something new.
We don't always agree, but I respect your opinion.
- Okay, that's good, right?
I mean, you know, pure agreement
usually just leads to group thanks, so.
- Yeah, it was awesome.
- If two people agree on everything together
then one person's not needed, yeah.
Anyway, thanks a lot, Jason, appreciate it.
Everyone stay tuned for the truckload market update.
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- Hello, and welcome to the truckload market update
for 25 June, 2026.
In the drive-and-market,
we saw that the change in active contract rates
increased slightly, 0.4%,
spot rates increased 1.7%,
and the current level of replacement rates for drive-and,
is positive 8.5%,
which means on average, rates coming in
are about 8.5% higher than rates that are exiting.
The market gap between spot and contract
is 27 cents a mile, spot above contract.
And the year-over-year change in spot rates
is about 36% for drive-and,
and about contract is about 5%.
Okay, temp control.
We saw the contract rates actually dropped a little,
1.6%, over the last two weeks.
This is the second period in rows,
so we're seeing some leveling off there.
Spot rates increased 0.6%,
and we see the current level of replacement rates
for temp control to be 6.9% positive.
Again, which means rates coming in contract rates
are about 7% higher than those ever replacing.
Market gap between spot and contract is 16 cents a mile,
spot above contract.
Year-over-year growth in spot rates for temp controls,
24.4%, contract's about 3%.
Intermodal, we saw about a 2% increase in contract rates.
We saw spot rates drop about 0.4%,
but there's very little spot in Intermodal.
Current level replacement rates is negative 7.9%
for Intermodal, so we're seeing a drop there,
which is a little surprising.
I thought we'd see leveling out or an increase.
Market gap is negative 2 cents a mile
for spot versus contract, where spot is below contract.
And year-over change in spot rates for Intermodal
is about positive 6.4%, and about 8.5% for contract.
Finally, flatbed, we see the change in active contract rates
drop 0.5%, a little bit of a change we've seen recently.
Spot rates are still going up, positive 2.4%,
and the current level of replacement rates
between rates that are entering versus rates that are exiting
is positive 8% for flatbed.
Market gap between spot and contract is 19 cents a mile,
spot above contract, and year-over-year change in spot rates
for flatbed is positive 24%, and for contract rates
for flatbed is a positive 6.7%.
Okay, a lot of numbers out there.
What are we seeing?
Temp control is continuing to drop from a peak in May,
both for contract.
So I'm wondering if it's kind of leveling out.
It's still 24% higher than it was year-over-year,
but we're seeing it drop a little bit
for that spot rate and contract is only about 3%
year-change year-over-year.
Driving in a staying pretty steady.
Spot rates are up across the board,
except for intermodal, which has minimal spot anyway,
and comparing year-over-year, all the modes except intermodal
has spot between 24% to 36% above year-over-year,
and 3% to 8% for contract.
So we are higher.
The question is, how long will that stay?
Our replacement rates are going through the roof.
All are in the positive, 79% except intermodal, which did drop.
So we are seeing bids coming in are going to be higher
than the rates they're replacing.
Similarly, the gap between spot and contract is positive.
It's 16 to 27 cents a mile, except intermodal, which is flat.
All this is pointing out that the cycle that started tightening,
the expansion that started hit in December of 2025 is continuing.
Not at the same rate that it was.
So we'll see if how far that continues,
probably through 2026 into 2027.
We'll see how long that lasts.
We'll keep paying attention to the different metrics
to see if we see the canary in the coal mine
that gives us an indicator when the market will level out
or actually contract, because we all know
that it will eventually.
All right, that's it for the truckload market update
for 25 June, 2026.
And that's a wrap for this episode of The Freightfine.
The Freightfine podcast is hosted by myself, Chris Campos,
and is produced and edited by DAT Freight Analytics.
For more information or to catch up on previous episodes,
swing by our website at www.dat.com/resources/freightfine.
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If you have any feedback or questions
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at
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That's
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And finally, a big thanks from all of us at DAT for tuning in.
We hope you learned something new and you come back again.
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