September 5, 2025 • 36 mins
How is AI really reshaping freight brokerages, and what’s the reality behind all the hype? Today, we have S&P Global’s Eric Johnson back on the show to discuss the latest trends in AI and freight tech!
We dive into how major companies are approaching AI differently, why 95% of enterprise AI projects show no ROI yet, the gap between marketing promises and actual performance, our insight on training large language models, balancing automation with human skills, and creative problem-solving!
About Eric Johnson
Eric Johnson is the Journal of Commerce's Senior Editor, Technology, where he leads coverage and analysis of technology’s impact on global logistics and trade. Johnson regularly reports on how shippers, carriers across all modes, and logistics companies use software, as well as new concepts impacting core freight transportation processes like procurement, execution, visibility, and payment. Johnson is a regular presenter and moderator at industry events and webinars. Prior to joining the Journal of Commerce in May 2018, Johnson spent 13 years with American Shipper in a variety of roles, most recently covering logistics technology and leading the production of a series of benchmark studies on the logistics industry. Johnson has a bachelor’s in journalism from the University of Wisconsin and a master’s in international business from the University of Leeds, UK. He has lived and worked in Southern California, the UK, and India, and now resides in the Washington, DC, area.
Connect with Eric
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- X (Twitter): https://x.com/LogTechEric
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:04):
Came back with a bank window down yelling now money anything hey oh got the foot on the gas pedal to the metal when I'm getting to the back hey Got the foot on the gas pedal to the metal when the lane moving fast hey Let them all cross if they hate then let them hate them Make a bigger balls hey.
Speaker 2 (00:26):
What is up, ladies and gentlemen?
We are back.
We are live.
It is the Freight Coach podcast, the top podcast in transportation, coming to you guys every single weekday, 8:30am Pacific, 10:30 Central, to break down some industry headlines.
But most importantly, you guys provide some actual insight into what we can do with all this information.
If this is your first time tuning in, welcome.
This is the real side of freight, ladies and gentlemen.
(00:47):
And I do say that before every single show.
And what I mean by that is I only speak with transportation professionals because at the end of the day, you guys, I want to talk to the right individuals who have done what you're looking to do or who are currently doing what you're trying to achieve, so you can take that information, apply it, utilize it, and see a meaningful difference in your business and your life.
Happy Friday, everybody.
And you know, we're going to jump in.
(01:07):
Sorry we're a couple of minutes late.
It's ironic that every time I talk about technology on the show, mine seemingly doesn't like to work on schedule and on par and everything.
So we're going to jump right in.
I got my good friend Eric Johnson back on the show.
Speaker 1 (01:21):
Thank you.
Speaker 2 (01:21):
To break down all things freight tech.
So, Eric, thank you for taking the time to join me today.
Speaker 3 (01:26):
All good, Chris.
It's, you know, it's like the curse, right?
Like whenever.
Whenever a technology company decides, sets up a meeting, like a month in advance.
Like, hey, we can't wait to show you this platform.
And they do the demo and it doesn't work, you know, so it's like, it's just the way these things go.
Speaker 2 (01:42):
Oh, man, this, you know, man, it's funny because it's.
It's so true.
And I'm like I was telling you, I'm the only one who, like, comes in here in my studio.
Nobody else touches this stuff.
I don't know how it works fine 99% of the time.
And then just all of a sudden, and I didn't do anything different, Eric.
(02:03):
I just kept hitting the power button and then back, boom, it miraculously turned on.
Speaker 3 (02:08):
You know, I think we have to come to terms with, like, the.
The tools we use have minds of their own.
They're they're mercurial, they have moods.
Like, some days they work great, some days they don't.
So yeah, it's not as uniform and like unemotional as we think it is.
Speaker 2 (02:27):
Dude, I wish it was that easy though, you know, where you can just show up.
Everything worked out all right.
We never had to worry about anything.
It would, you know, it would be pretty amazing if that was the case.
But.
So, dude, what's new, man?
You know, I always love having you come on the show because you're out there at the forefront of all things freight technology.
You're talking to a bunch of different companies and you know, I, I jokingly stay on the show every day there's five new AI companies that pop up inside of this industry and they're all here to revolutionize everything.
(02:58):
And you know, don't get me wrong, I'm a massive fan of AI and tech and everything that's out there.
But you know, it's kind of like what is going on?
Like, how much, you know, like, is this like the dot com bubble of, you know, the early 2000s?
Speaker 3 (03:13):
That's a great place to start.
I mean, I think we even have a more recent precedent is the blockchain bubble, you know, from 2018, I think.
Right.
I think that's the thing is I get most people asking me, is this like blockchain again all over again where like everybody cared about it and then all of a sudden it's like, well, it doesn't really work or it's too expensive or so there's so much to talk about on this.
(03:42):
I mean, just this week we've.
I'm actually posting a story on Joc.com this afternoon about it.
We had two massive fundraisings for two of those companies.
Augment, Happy Robot, both kind of logistics, mostly broker oriented AI automation type companies.
(04:04):
I think they both collectively raised like 120, 130 million, something like that between the two of them.
So we are sort of again in this like boom where AI has kind of captured the fascination of investors.
And it certainly is, it's certainly having an impact on the brokerage space.
(04:27):
Like there's hardly a broker I talk to who is not trying these things or have tried a bunch of them or using a bunch of them.
Right.
Like they are using them.
And it makes sense if you think about it from the perspective of if you're a broker and you don't own trucks and you don't own cargo you're the ability for you to be successful, especially against your peers, is to just be as operationally cost competitive as possible.
(04:57):
Right?
Speaker 2 (04:57):
Yeah.
Speaker 3 (04:58):
And if these tools have the promise of like doing a task faster or for 24 hours a day instead of eight, not getting distracted or you know, frankly just doing things that like humans don't have the capacity to do as quickly as these systems do, you're sort of fooling yourself if you just completely ignore it.
(05:23):
Right.
So it totally makes sense that this has kind of captured the attention of especially the 3pl space.
There was some interesting.
I was at a conference earlier this week talking about AI actually and one of the other presenters brought up this study that recently came out.
I think it was, can't remember if it was a consultant or MIT that did it.
(05:45):
Anyway, they said 95% of AI projects enterprise from enterprises are not.
There's no ROI on them yet because, you know, it's more like we feel like we need to do something and so we're doing something, but it's not turning into ROI yet.
Speaker 2 (06:04):
I think a lot of people, Eric.
And again, I always, like, I don't want to say like I always blame marketing, but I feel like the push is oh, you just have to implement AI and it's going to take off and it's going to automatically start working.
And I think like the messaging failure out there, at least as a consumer that I have experienced is like, no, with LLM large language models, like you have to train it's extremely smart and it can do a lot of great things but like you have to work with it a lot more in depth.
(06:35):
And I feel like the message is out there.
And again, maybe it's just me, but like I haven't really seen any of these AI companies directly come out and be like, hey, this is where it's at right now.
You have to do this to get it up to that level of efficiencies that you're wanting.
(06:57):
And I feel like, you know, you can kind of blame Grok or Chat GPT because it's like you can go in there and use that like it's Google and essentially it creates a bunch of stuff for you in the matter of seconds.
But the as the purchaser of it.
Yeah, and you also have to look at it as, it's like, no, if you want these AI tools inside of logistics to work for you have to be working with it to get it to that point.
(07:21):
Like if you are as good as you think you are in this industry, you got to train that bot to work 24 7, 365 the way that you want it to.
Because I feel like that out of the box, initial implementation people are going to, I, I feel like a lot of resistance is going to come out here in the coming months, Eric, where people are like, oh, AI is a fad, it's a joke.
Nothing inside afraid is going to work.
Speaker 3 (07:43):
So I mean, I think you're totally right that there's a danger that the things that have kind of happened with past software hype cycles is people get excited about it doesn't work as well as they thought it was going to or as well as it was sold.
They get disillusioned and instead of like going back to the drawing board and trying again, they sort of just like, nah, let's just go back to what we did before.
(08:09):
I mean that's definitely a possibility.
Oh, there's so many different aspects to this.
You're right that some of the marketing is to blame.
I think also some of the demand from companies is to blame.
Like there's a lot I hear all the time, like you read in any sort of corporate type magazine, like the demand at the corporate level to figure out how to use AI is off the charts.
(08:35):
Like they want this badly because if we're being totally frank, it helps them not have to hire people or it helps them reduce their headcount.
Like let's not beat around the bush.
The goal from corporate America is more, be more efficient, higher margin.
That's, that's what it boils down to.
And so if you combine the demand with the marketing that the demand wants to hear, it definitely can create some like it set you up essentially for a promise that was not kept.
(09:11):
Right now the interesting thing with the marketing thing that's going on, especially inside of freight right now is you have companies that are like AI, born AI, like they came, they started, their product was essentially let's use AI to solve this problem or to connect these two data sets or to automate this workflow.
(09:39):
There's other companies, there's a million other companies that were, that existed and have huge customer bases that were started way before anyone knew what ChatGPT was.
And by the way, they were probably also using AI.
They just weren't bragging about it or putting it in marketing speak.
But the onus on those companies now is they also have to have a marketing message around AI.
(10:04):
So they are investing in agents that they name, give like cute names to Their agent who helps you.
It's like Clippy.
It's like the new version of Clippy.
And so there's like almost like these marketing wars between large incumbent companies that have huge customer bases and have had to adopt an AI message versus the AI.
(10:29):
The actual only AI companies that aren't doing anything else but AI and are saying, well, were started two years ago and so we're, we've built everything using the most state of the art that you could possibly have.
Speaker 2 (10:45):
Yeah.
Speaker 3 (10:45):
And, and it's all, and a lot of it is marketing.
Right.
Obviously.
Speaker 2 (10:49):
I think we also, you know, a lot of individuals out there are, you know, they see like C.H.
robinson, they came out here recently about their massive AI push and you know, they reorganized a bunch of stuff and you know, you see it.
But then I feel like a lot of people fail to realize that some of the, you know, like you were saying, like these large corporations and kind of like what they're doing with this.
(11:13):
But like, I think what a lot of people are failing to realize is a lot of these companies have been working on this already for five years now, like six years.
They've been working on this for a long time.
And then we're seeing the announcements come out about a company like C.H.
robinson and just to be abundantly clear, I'm not ripping on Robinson here at all for this, but they see that and then they see all of this AI companies popping up in the industry and they're like, oh, C.H.
(11:36):
robinson must be using all of these tools.
I haven't done a ton of in depth research, but I'm assuming Robinson bought their own or built their own and then they've been in there kind of breaking that down because they are getting ahead.
And, and this is where it's like, I feel like a lot of companies who are at a smaller scale, Eric, they need to model what like a company like Robinson out there is doing where, you know, I, I think there's going to be a lot of stuff that comes out where a lot of people are going to lean heavy on.
(12:05):
Oh, AI is replacing all of our jobs.
But, but I don't think it's going to be that way in a couple of years where it's going to balance it out and I'm going to take it where like Robinson and a lot of the big companies are not going to get the benefit of the doubt because they're going to probably slash 30%.
Right.
Just a, just a guesstimate.
And the smaller companies though who adopt it like, I'll use my company as an example.
(12:29):
Our plan is to adopt as much tech as possible so we can remain as lean as possible for as long as possible, hire the right amount of people, pair that up with uncapped commissions, because again, I will quote again for the thousandth time, my companies will never cap their commissions because I want to pack a larger punch in the market and be able to bring and level the playing field.
(12:50):
And that's where I see a lot of small companies.
You can literally level the playing field with the right technology.
But I feel like with what will come out in the coming years, a lot of these large organizations are not going to get the benefit of the doubt.
They're going to be told, you're putting profits over people, you're firing all these individuals.
I think that the meritocracy that is the economy of the United States is going to really come into full effect here.
(13:16):
And I feel like if you're that great of an employee, you're going to be just fine no matter what.
Speaker 3 (13:22):
Yeah, I'm, I would agree with, especially that last point, right?
Like, you have to figure out what your unique value to companies, the company you work for, just the general market.
Right.
Like, that is, it's really, it's.
It's always been important, but it's never been more important in light of like, if you just assume there's a certain amount of like, repetitive tasks that everybody has to do, like for a manager or someone in like an executive role, you do a ton of administrative stuff that honestly sometimes feels like a total waste of time.
(13:55):
Or like, you sort of wonder, like, why is my company paying me to do like, fill out forms?
Right.
Like, that could be taken off your plate.
Right.
So, okay, so it's interesting.
Robinson is a great example of a company that has, I mean, they're doing great relative to where they were two years ago, and they've gone really hard in on the messaging, on, we're automating this.
(14:19):
I think they had a smart message around.
We are the biggest, we have the biggest number of transactions.
Thereby we have the best ability to train a model to do what we do.
Because nobody has a data set as big as ours.
And if we internally make that data, the data as accurate and clean as possible, then the model should learn from the, like, a very clean internal data set.
(14:46):
That's a great message to go into the market with.
Yeah, there's other companies and yes, I agree.
I mean, I haven't talked to them in depth.
But I know they develop a lot of stuff internally.
They've obviously had a TMS and a managed trans kind of facility internally that they've built.
So I don't think they use a lot of outside help with this.
(15:07):
Then look at Echo.
Echo has, doesn't put out press releases about the use of AI.
They don't set up chats with me and Bill Cassidy about use of AI.
But I know the guy, he's speaking at our event in a few weeks who is in responsible for sort of like corralling what's in the outside market and making it useful for Echo.
(15:34):
And they try a lot of different things.
They're using off the shelf stuff.
So there's different approaches to this both in terms of what you use and also how you market it.
So it's very dangerous to go, oh, the company that's making the most noise is the one that's the most innovative.
It's also dangerous to say that the one that's being super quiet isn't doing anything or is the most innovative because they're being quiet.
(16:01):
Like you just can't make these assumptions.
You have to kind of just peer under the hood and most companies don't let you do that.
So it's very difficult.
Like if you think about it from the company, you know, whether you're a shipper or you're a carrier and you're interacting with these companies that are all of a sudden like wanting to transform how they do, how transform themselves operationally, it's super hard.
(16:24):
You just have to get in there and like work with them and know, oh my God, this is amazing.
Like this thing pings my system instantly, 24 hours a day.
Instead of me having to call Pam and getting, you know, getting her to give me a piece of data.
Right.
Alternatively, they may be you, they may be saying that they have amazing AI and the AI sucks and it's terrible and it's just giving you wrong answers or it's like it just keeps pinging and it doesn't get through.
(16:53):
Like the other day, I'll give you a great example, I was in this small town in Illinois last week and were trying to make a reservation for a restaurant in Davenport, Iowa.
We were about an hour away and the only way to make the reservation was through Google's AI.
(17:17):
So Google AI goes, we're gonna call the restaurant right now and make the reservation for you.
Can't get through to the, can't get through to the restaurant.
We will try again in 15 minutes.
And I kept getting texts three, four times.
Couldn't get through.
I just picked up the phone and called the restaurant and they picked up and I made the reservation.
Right.
So, like, this stuff is not infallible.
It.
Yeah, it doesn't always work.
Speaker 2 (17:39):
No.
And, and that's the thing though, man, is I feel like there's a. I feel like a lot of individuals are kind of like with everything in our society right now, they read a headline, they formulate an entire opinion on it, and they don't actually do any independent research or try on their own to go out there and do it.
Like, we've been utilizing ChatGPT and Grok and then a couple other AI tools for our content.
(18:04):
Not to, like, write it out, but to help us edit it, to help me come up with brainstorming.
Yeah, brainstorming.
That's really what it is, right?
Because it's like, I look at it as I put out on average of 20 to 23 podcasts every single month on a variety of topics, but there is a lot of overlap out there in what topics are top of mind in the industry right now.
(18:27):
I can't use the same episode title for every single AI episode that I do.
Right?
And for me, it's like, that's what I love utilizing these tools for, is to get in there and mess around a little bit.
And I'm like, oh, shit.
I like the way that topic is structured and then that topic is structured.
I'm going to combine it right now and I'm going to create my own.
(18:47):
And it is just a way for me to help spark my creative juices.
And I think most people are going to look at this as like, they're just going to ask it a question and be done with it.
Like, dude, I have, like, I kind of feel like a psychopath.
Like, I have actual conversations with it to be like, no, I need you to do this.
Speaker 3 (19:04):
There's been guys who've gone, like, have had like, mental breakdowns doing this.
So you gotta make sure someone's in the, like, in my room to make sure you're not going crazy.
Speaker 2 (19:17):
You know, to me.
But it's like, I, I look at it is as like I'm training it myself.
And, and that's also another, like, discussion that I've had is like, maybe I just buy my own off the shelf AI bot and then just train it myself and just do it that way.
And you know, Build it out like that.
And I feel like there's going to be an opportunity out there with it.
(19:40):
But I think, like there's going to be two groups of people out here, Eric.
They're going to be the over automation and then the no automation on the majorities.
And there's going to be a sliver of people who actually take the old school methodology with automation and then accelerate it with.
Yeah, and I think like, they're going to be the ones that grow.
(20:01):
And again, this is just a very bold prediction.
I think if you look at the top 50 freight brokers out there right now in the next five years, it could be filled with companies that nobody had ever heard of before that went from a $10 million operation to a $400 million operation in a matter of months because they just did the right thing and made the right calls.
Speaker 3 (20:26):
So the other thing to be like, really careful about when you talk about AI is like most people's.
Most people's conception of AI is what they've experienced directly.
So.
ChatGPT.
Yeah, co pilot.
We have, at S P where I work, we have an internal one that we use that is like.
(20:51):
So I, I mentioned I was at a conference earlier this week and literally I put up.
The first thing I did is I put up a picture of a tree and it's like, if you think of this tree is AI, like the whole totality of AI and there's a branch that does this.
And then off of this big branch, there's like three branches that stick down.
(21:14):
That's AI.
Like, and what we're talking about, what most people's experience with AI is like one small branch off of a big branch and it's not even off the main trunk.
Like the main.
What AI has been developed over the last 70 years is the main trunk of the tree and all these big branches.
(21:36):
You know, things like fuzzy logic and deep learning and stuff way beyond my brain power.
And LLM is like an offshoot of one of those that just people have gotten familiar with.
It's.
It's their window into AI, but it's totally.
It's not the totality of AI for sure.
Speaker 2 (21:59):
Do you think people are underestimating the power of AI and do you think, and I'm asking you this because you live in D.C. do you think there will be some form of federal regulation on it?
Because it's a lot more powerful than people think at this current juncture?
Speaker 3 (22:22):
I Think it's pretty powerful right now.
I think it's.
I think actually probably more than regulation.
The thing that is preventing it from, like, from it being.
Reaching the ceiling of its power is like, is culture, is our.
Most people still don't.
Most people use it in a very, like, superficial way.
(22:45):
They don't use.
They use it to replace Google Search.
Speaker 2 (22:48):
Yeah.
Speaker 3 (22:49):
Or they use it to replace some conversation that they have with a person like you were talking about before.
They aren't using it to, like, set two, three, four levels of depth.
And mostly either because they're scared of change or they literally have no idea what to do with this tool.
(23:12):
It's like, it's.
It's sort of like if you handed me the keys to a.
Like a.
Like the space shuttle.
Speaker 2 (23:17):
Yeah.
Speaker 3 (23:18):
What.
How do I even get started with this thing?
You know, like, so it's incredibly powerful and were probably underestimating the power of it.
But also, like, it's only powerful to the extent that we let it be powerful.
And right now we're not letting it be powerful.
(23:39):
Not because we are less because we're scared of it, but more because we just don't even know how to let it be powerful yet.
Speaker 2 (23:46):
Yeah.
Speaker 3 (23:47):
And now in terms of regulation, I don't know.
It's very unclear to me what government can and should do to limit this.
Like, how do you stop.
How do you stop someone working on a computer in their house developing something that eventually lets out Pandora's or opens Pandora's box?
(24:12):
Like, I don't know how you regulate that.
Honestly, there's literally no constraints on coding.
So I think it's more like we have to be way more educated as a society about how to interact with this stuff and how to maintain our.
What makes us human.
(24:33):
And so I.
One example I give all the time is, like, I don't know what your calculator was in school, but, like, when I was in high school, Casio, everyone had.
Well, everyone had a TI81 graphing calculator because you needed that for.
I Forget what algebra 2 or whatever it was.
Speaker 2 (24:52):
I wasn't in advanced math, Eric, so we can just curb that is what I. I wasn't.
Speaker 3 (24:56):
I'm not a mathematician.
Even, like, the basic kids got.
Were told to get these.
These things because it was.
It didn't make sense for you to break a protractor out and a compass and like, for sure, you know, you.
You can do this all digitally.
Right.
I mean, there's a.
There's a.
A manner of thinking that like, this stuff should.
(25:19):
Takes stuff off the human, the plate of the human brain that we're not necessarily best equipped to do.
Right.
And so if you take that perspective, you still have to decide what.
We still need to decide what it is we're really good at.
(25:40):
Like creative thinking, moral type stuff.
Like, it's not clear that machines will ever have the ability to do those things to the level that humans do.
So empathy, you know, things like that.
Like, those are the things that we need to cling to as we start to hand more and more off of this.
(26:01):
Because we will, because it will look, it will be very clear how easy it is to hand things off to systems.
Speaker 2 (26:07):
Yeah, no, and that's where I feel like it's going to be a, you know, kind of like a big bullwhip.
I think, like, it's going to go really far in one direction.
And I feel like, again, I don't know if this will happen, but I just feel like in time humans are going to realize like, hey, I think we did too much and we want to go back to just being humans again.
(26:30):
I don't know, man.
I just don't know if you can erase thousands of years of tribalism that we are as people.
Speaker 3 (26:38):
Can I say something that I feel like I've noticed people talking about more is the rush to AI.
Everything is.
Because most people feel completely overloaded in their lives, work, personal, everything we get, we take in too much information, we get too many emails, we have too many, like, authorities sending us mails to do this and that.
(27:02):
We have to fill out too many forms.
Everything is so frigging complicated.
And it seems very appealing to have someone take some of that load off our plate.
So I agree.
I think there's going to be a backlash where it's like, we need humans to be doing things, but it needs to be a reasonable amount of things that they do in a day.
(27:24):
And it can't be that we're just like trying to emulate supercomputers and just juggling a million different things all the time.
Speaker 2 (27:31):
I think the most powerful thing a lot of people can do right now is literally just shut their phone off.
Speaker 3 (27:37):
For like, for sure.
Speaker 2 (27:40):
And, and it's like, I won't go down.
I, I could have been like, oh, Eric, welcome to the dark side of tinfoil hats.
We can go on about that, about with big government and everything, but we won't go there on this show today.
But I, you know, I look at it is, you know, you do need to give yourself a break from social media and all of this stuff, because I feel like people get a little too wrapped up into it, right?
(28:04):
Like, they get a little too wrapped up and needing to have an opinion on everything.
And it's like, dude, for me, it's like, I. I literally just take the stance of, like, I'm just not going to comment on anything.
I don't even reply to, like, most comments and stuff that I see or posts out there that I see.
I just don't do it because I'm like, dude, this doesn't affect my life, like, what somebody else is going through.
(28:27):
And when I say somebody else, you guys, like, 99% of the people you see online are not your friend.
Right?
Like, they're just fucking people on the Internet.
Yeah.
And I'm like, I don't feel the need to comment on some of that stuff.
And I feel like so many people get so wrapped up in.
In everything that's going on.
This is just another layer of getting wrapped up into stuff that I feel like the most powerful piece of advice I can give the majority of people.
(28:51):
Shut your phone off for like an hour.
Speaker 3 (28:54):
All right?
Go look.
Go look at a mountain or, you know, get some sun on your face.
Speaker 2 (28:59):
And then another thing, too, man.
Like, I think a lot of people will also come to the realization we're not as different as the Internet makes it seem.
You know, like, when it boils down to it, we're not.
Speaker 3 (29:08):
You go like, one of the benefits.
I get to go to conferences all the time and, like, you go to conferences and I.
It's like, I.
Sometimes I think I catch myself going.
I look around and I'm like, I bet if were all sitting behind computers, everyone would be, like, antagonizing each other about some stupid detail.
But here we are in person and we're like, you know, having coffee and chit chatting and like, oh, that's interesting.
(29:32):
And, you know, it's totally.
You're totally right.
Speaker 2 (29:35):
Yeah, I. I just look at it as is.
Like, yeah, you know, there's, you know, and especially, like, with.
With where we're at with AI and technology and everything and, you know.
Yes, Ryan Schreiber, this entire episode has been about you, actually, the entire time.
So if you go back, listen to it, and then share it out a bunch, then you can show everybody how we only talked about Ryan Schreiber.
Speaker 3 (29:55):
This started with.
We started with.
On this day.
Ryan Triber was born on.
On week one.
He did this on week.
Speaker 2 (30:05):
Dude, I just like I, I look at it is, you know, there's a lot to be seen.
There's going to be a lot of great tools that are going to come about this.
And, you know, I feel like you do have to give it a little bit more time on how you're going to utilize it inside of your organization.
There's going to be a lot of great tools that are.
Have yet to be developed, that are about to be developed.
(30:26):
And you know, I look at it is as, you know, a good gauge and a good place to start is like, what are your customers asking of you?
Are your customers coming to you and asking for any of these tools?
Because that's one thing.
You know, again, like, I actually move freight.
I don't work with the largest shippers in North America, but the shippers that I do work with have a lot of volume.
I, I don't have a big push from them about, hey, you need to do this.
(30:50):
You need to have this tech and this tech.
Speaker 3 (30:53):
they're not like, Chris, I need you to optimize my workflows.
Speaker 2 (30:58):
That, yeah, that conversation doesn't happen.
I'm not saying it doesn't happen out there, but from my experience, and again, I feel like with a lot of companies, you know, if you don't know where to start, maybe gauge on what your customers are asking of you and your capabilities.
And you know, I, I think like a lot of organizations out there, Eric, a really good tracking system and some really good load updates would serve them very well out there in the market.
(31:26):
Because if I'm talking to any prospects, which I, you know, I do, I cold call every single day.
That's kind of the big sticking point with a lot of them is it's like we just need to know what's going on with our freight and.
And that's it, right?
So, yes, there's some organizations that are a lot more complex, but I feel like the majority of them out there might not be as complex as you think.
It might not have the.
(31:46):
As big of requirements as you think.
Speaker 3 (31:49):
Yeah, that's fair.
Speaker 2 (31:51):
Eric.
I appreciate your time, man.
How does anybody.
You guys got your conference coming up here and I know these fly by every single time.
Even though were late, we already blew past 30 minutes.
Like inland.
All that stuff's coming out there, man.
Drop that in there for people.
Speaker 3 (32:04):
So yeah, we're.
Our Inland Distribution conference, or Inland25 is September 29 through October 1 in downtown Chicago.
We have an awesome program this year.
Attendance is looking great, even despite.
Despite the market.
And, yeah, Joc.com is a place to read stories.
(32:26):
I'm on LinkedIn.
I'm also still, to my.
You know, to.
To your point earlier, probably to my detriment, I'm still on Twitter.
But, you know, I. I have a high pain tolerance, I guess.
Speaker 2 (32:38):
So, dude, I. I try and stay off of Twitter as much as possible.
I stream.
I. I do.
I stream this show on Twitter just because, like, there's a.
There's a big community, there's an audience there.
Yeah, but I'm like, man, that's.
That's one of those social media platforms that I'm on for about eight seconds, and I want to, like, drive my car into oncoming traffic.
(32:59):
I'm like, this cannot be.
Your post last night summarized it perfectly.
This cannot be where we're at as a society.
Speaker 3 (33:07):
You know, it's funny, I, like, I don't quote Joe Rogan a lot, but he had a bit of a, like, way before he became big, where he talked about, like, whether humans were getting dumber generation by generation.
Because I forget the reason he said, but I have to go back and find this.
But I am like, man, I think he actually was right about this.
He's like.
He's like, the Egyptians 2,000 years ago built the pyramids without, like, any machinery.
(33:31):
And like, now we seem like they have a dumber handle on basic facts than they did, so.
Speaker 2 (33:39):
It's so damn true, man.
Eric, thank you so much for your time.
That's going to be it for today, ladies and gentlemen, as always, if you guys got value in what you heard, subscribe to the show.
You guys.
And if you're feeling really ambitious after this one, rank the show on itunes and Spotify.
Because if you see value, your network's going to see it as well.
I appreciate you guys.
I love you guys, and we'll be talking to you soon.
Speaker 1 (34:05):
Came back with a bank window down yelling now money anything hey, oh got the foot on the gas pedal to the metal when I'm getting to the back hey Got the foot on the gas pedal to the metal when the lane moving fast hey Let them all cross if they hate then let them hate them make a bigger boss hey.
Came back with a bank window down yelling now money anything hey oh got the foot on the gas pedal to the metal when I'm getting to the back hey Got the foot on the gas pedal to the metal when the lane moving fast hey Let them all cross if they hate then let them hate them Make a bigger balls hey.
Speaker 2 (00:26):
What is up, ladies and gentlemen?
We are back.
We are live.
It is the Freight Coach podcast, the top podcast in transportation, coming to you guys every single weekday, 8:30am Pacific, 10:30 Central, to break down some industry headlines.
But most importantly, you guys provide some actual insight into what we can do with all this information.
If this is your first time tuning in, welcome.
This is the real side of freight, ladies and gentlemen.
(00:47):
And I do say that before every single show.
And what I mean by that is I only speak with transportation professionals because at the end of the day, you guys, I want to talk to the right individuals who have done what you're looking to do or who are currently doing what you're trying to achieve, so you can take that information, apply it, utilize it, and see a meaningful difference in your business and your life.
Happy Friday, everybody.
And you know, we're going to jump in.
(01:07):
Sorry we're a couple of minutes late.
It's ironic that every time I talk about technology on the show, mine seemingly doesn't like to work on schedule and on par and everything.
So we're going to jump right in.
I got my good friend Eric Johnson back on the show.
Speaker 1 (01:21):
Thank you.
Speaker 2 (01:21):
To break down all things freight tech.
So, Eric, thank you for taking the time to join me today.
Speaker 3 (01:26):
All good, Chris.
It's, you know, it's like the curse, right?
Like whenever.
Whenever a technology company decides, sets up a meeting, like a month in advance.
Like, hey, we can't wait to show you this platform.
And they do the demo and it doesn't work, you know, so it's like, it's just the way these things go.
Speaker 2 (01:42):
Oh, man, this, you know, man, it's funny because it's.
It's so true.
And I'm like I was telling you, I'm the only one who, like, comes in here in my studio.
Nobody else touches this stuff.
I don't know how it works fine 99% of the time.
And then just all of a sudden, and I didn't do anything different, Eric.
(02:03):
I just kept hitting the power button and then back, boom, it miraculously turned on.
Speaker 3 (02:08):
You know, I think we have to come to terms with, like, the.
The tools we use have minds of their own.
They're they're mercurial, they have moods.
Like, some days they work great, some days they don't.
So yeah, it's not as uniform and like unemotional as we think it is.
Speaker 2 (02:27):
Dude, I wish it was that easy though, you know, where you can just show up.
Everything worked out all right.
We never had to worry about anything.
It would, you know, it would be pretty amazing if that was the case.
But.
So, dude, what's new, man?
You know, I always love having you come on the show because you're out there at the forefront of all things freight technology.
You're talking to a bunch of different companies and you know, I, I jokingly stay on the show every day there's five new AI companies that pop up inside of this industry and they're all here to revolutionize everything.
(02:58):
And you know, don't get me wrong, I'm a massive fan of AI and tech and everything that's out there.
But you know, it's kind of like what is going on?
Like, how much, you know, like, is this like the dot com bubble of, you know, the early 2000s?
Speaker 3 (03:13):
That's a great place to start.
I mean, I think we even have a more recent precedent is the blockchain bubble, you know, from 2018, I think.
Right.
I think that's the thing is I get most people asking me, is this like blockchain again all over again where like everybody cared about it and then all of a sudden it's like, well, it doesn't really work or it's too expensive or so there's so much to talk about on this.
(03:42):
I mean, just this week we've.
I'm actually posting a story on Joc.com this afternoon about it.
We had two massive fundraisings for two of those companies.
Augment, Happy Robot, both kind of logistics, mostly broker oriented AI automation type companies.
(04:04):
I think they both collectively raised like 120, 130 million, something like that between the two of them.
So we are sort of again in this like boom where AI has kind of captured the fascination of investors.
And it certainly is, it's certainly having an impact on the brokerage space.
(04:27):
Like there's hardly a broker I talk to who is not trying these things or have tried a bunch of them or using a bunch of them.
Right.
Like they are using them.
And it makes sense if you think about it from the perspective of if you're a broker and you don't own trucks and you don't own cargo you're the ability for you to be successful, especially against your peers, is to just be as operationally cost competitive as possible.
(04:57):
Right?
Speaker 2 (04:57):
Yeah.
Speaker 3 (04:58):
And if these tools have the promise of like doing a task faster or for 24 hours a day instead of eight, not getting distracted or you know, frankly just doing things that like humans don't have the capacity to do as quickly as these systems do, you're sort of fooling yourself if you just completely ignore it.
(05:23):
Right.
So it totally makes sense that this has kind of captured the attention of especially the 3pl space.
There was some interesting.
I was at a conference earlier this week talking about AI actually and one of the other presenters brought up this study that recently came out.
I think it was, can't remember if it was a consultant or MIT that did it.
(05:45):
Anyway, they said 95% of AI projects enterprise from enterprises are not.
There's no ROI on them yet because, you know, it's more like we feel like we need to do something and so we're doing something, but it's not turning into ROI yet.
Speaker 2 (06:04):
I think a lot of people, Eric.
And again, I always, like, I don't want to say like I always blame marketing, but I feel like the push is oh, you just have to implement AI and it's going to take off and it's going to automatically start working.
And I think like the messaging failure out there, at least as a consumer that I have experienced is like, no, with LLM large language models, like you have to train it's extremely smart and it can do a lot of great things but like you have to work with it a lot more in depth.
(06:35):
And I feel like the message is out there.
And again, maybe it's just me, but like I haven't really seen any of these AI companies directly come out and be like, hey, this is where it's at right now.
You have to do this to get it up to that level of efficiencies that you're wanting.
(06:57):
And I feel like, you know, you can kind of blame Grok or Chat GPT because it's like you can go in there and use that like it's Google and essentially it creates a bunch of stuff for you in the matter of seconds.
But the as the purchaser of it.
Yeah, and you also have to look at it as, it's like, no, if you want these AI tools inside of logistics to work for you have to be working with it to get it to that point.
(07:21):
Like if you are as good as you think you are in this industry, you got to train that bot to work 24 7, 365 the way that you want it to.
Because I feel like that out of the box, initial implementation people are going to, I, I feel like a lot of resistance is going to come out here in the coming months, Eric, where people are like, oh, AI is a fad, it's a joke.
Nothing inside afraid is going to work.
Speaker 3 (07:43):
So I mean, I think you're totally right that there's a danger that the things that have kind of happened with past software hype cycles is people get excited about it doesn't work as well as they thought it was going to or as well as it was sold.
They get disillusioned and instead of like going back to the drawing board and trying again, they sort of just like, nah, let's just go back to what we did before.
(08:09):
I mean that's definitely a possibility.
Oh, there's so many different aspects to this.
You're right that some of the marketing is to blame.
I think also some of the demand from companies is to blame.
Like there's a lot I hear all the time, like you read in any sort of corporate type magazine, like the demand at the corporate level to figure out how to use AI is off the charts.
(08:35):
Like they want this badly because if we're being totally frank, it helps them not have to hire people or it helps them reduce their headcount.
Like let's not beat around the bush.
The goal from corporate America is more, be more efficient, higher margin.
That's, that's what it boils down to.
And so if you combine the demand with the marketing that the demand wants to hear, it definitely can create some like it set you up essentially for a promise that was not kept.
(09:11):
Right now the interesting thing with the marketing thing that's going on, especially inside of freight right now is you have companies that are like AI, born AI, like they came, they started, their product was essentially let's use AI to solve this problem or to connect these two data sets or to automate this workflow.
(09:39):
There's other companies, there's a million other companies that were, that existed and have huge customer bases that were started way before anyone knew what ChatGPT was.
And by the way, they were probably also using AI.
They just weren't bragging about it or putting it in marketing speak.
But the onus on those companies now is they also have to have a marketing message around AI.
(10:04):
So they are investing in agents that they name, give like cute names to Their agent who helps you.
It's like Clippy.
It's like the new version of Clippy.
And so there's like almost like these marketing wars between large incumbent companies that have huge customer bases and have had to adopt an AI message versus the AI.
(10:29):
The actual only AI companies that aren't doing anything else but AI and are saying, well, were started two years ago and so we're, we've built everything using the most state of the art that you could possibly have.
Speaker 2 (10:45):
Yeah.
Speaker 3 (10:45):
And, and it's all, and a lot of it is marketing.
Right.
Obviously.
Speaker 2 (10:49):
I think we also, you know, a lot of individuals out there are, you know, they see like C.H.
robinson, they came out here recently about their massive AI push and you know, they reorganized a bunch of stuff and you know, you see it.
But then I feel like a lot of people fail to realize that some of the, you know, like you were saying, like these large corporations and kind of like what they're doing with this.
(11:13):
But like, I think what a lot of people are failing to realize is a lot of these companies have been working on this already for five years now, like six years.
They've been working on this for a long time.
And then we're seeing the announcements come out about a company like C.H.
robinson and just to be abundantly clear, I'm not ripping on Robinson here at all for this, but they see that and then they see all of this AI companies popping up in the industry and they're like, oh, C.H.
(11:36):
robinson must be using all of these tools.
I haven't done a ton of in depth research, but I'm assuming Robinson bought their own or built their own and then they've been in there kind of breaking that down because they are getting ahead.
And, and this is where it's like, I feel like a lot of companies who are at a smaller scale, Eric, they need to model what like a company like Robinson out there is doing where, you know, I, I think there's going to be a lot of stuff that comes out where a lot of people are going to lean heavy on.
(12:05):
Oh, AI is replacing all of our jobs.
But, but I don't think it's going to be that way in a couple of years where it's going to balance it out and I'm going to take it where like Robinson and a lot of the big companies are not going to get the benefit of the doubt because they're going to probably slash 30%.
Right.
Just a, just a guesstimate.
And the smaller companies though who adopt it like, I'll use my company as an example.
(12:29):
Our plan is to adopt as much tech as possible so we can remain as lean as possible for as long as possible, hire the right amount of people, pair that up with uncapped commissions, because again, I will quote again for the thousandth time, my companies will never cap their commissions because I want to pack a larger punch in the market and be able to bring and level the playing field.
(12:50):
And that's where I see a lot of small companies.
You can literally level the playing field with the right technology.
But I feel like with what will come out in the coming years, a lot of these large organizations are not going to get the benefit of the doubt.
They're going to be told, you're putting profits over people, you're firing all these individuals.
I think that the meritocracy that is the economy of the United States is going to really come into full effect here.
(13:16):
And I feel like if you're that great of an employee, you're going to be just fine no matter what.
Speaker 3 (13:22):
Yeah, I'm, I would agree with, especially that last point, right?
Like, you have to figure out what your unique value to companies, the company you work for, just the general market.
Right.
Like, that is, it's really, it's.
It's always been important, but it's never been more important in light of like, if you just assume there's a certain amount of like, repetitive tasks that everybody has to do, like for a manager or someone in like an executive role, you do a ton of administrative stuff that honestly sometimes feels like a total waste of time.
(13:55):
Or like, you sort of wonder, like, why is my company paying me to do like, fill out forms?
Right.
Like, that could be taken off your plate.
Right.
So, okay, so it's interesting.
Robinson is a great example of a company that has, I mean, they're doing great relative to where they were two years ago, and they've gone really hard in on the messaging, on, we're automating this.
(14:19):
I think they had a smart message around.
We are the biggest, we have the biggest number of transactions.
Thereby we have the best ability to train a model to do what we do.
Because nobody has a data set as big as ours.
And if we internally make that data, the data as accurate and clean as possible, then the model should learn from the, like, a very clean internal data set.
(14:46):
That's a great message to go into the market with.
Yeah, there's other companies and yes, I agree.
I mean, I haven't talked to them in depth.
But I know they develop a lot of stuff internally.
They've obviously had a TMS and a managed trans kind of facility internally that they've built.
So I don't think they use a lot of outside help with this.
(15:07):
Then look at Echo.
Echo has, doesn't put out press releases about the use of AI.
They don't set up chats with me and Bill Cassidy about use of AI.
But I know the guy, he's speaking at our event in a few weeks who is in responsible for sort of like corralling what's in the outside market and making it useful for Echo.
(15:34):
And they try a lot of different things.
They're using off the shelf stuff.
So there's different approaches to this both in terms of what you use and also how you market it.
So it's very dangerous to go, oh, the company that's making the most noise is the one that's the most innovative.
It's also dangerous to say that the one that's being super quiet isn't doing anything or is the most innovative because they're being quiet.
(16:01):
Like you just can't make these assumptions.
You have to kind of just peer under the hood and most companies don't let you do that.
So it's very difficult.
Like if you think about it from the company, you know, whether you're a shipper or you're a carrier and you're interacting with these companies that are all of a sudden like wanting to transform how they do, how transform themselves operationally, it's super hard.
(16:24):
You just have to get in there and like work with them and know, oh my God, this is amazing.
Like this thing pings my system instantly, 24 hours a day.
Instead of me having to call Pam and getting, you know, getting her to give me a piece of data.
Right.
Alternatively, they may be you, they may be saying that they have amazing AI and the AI sucks and it's terrible and it's just giving you wrong answers or it's like it just keeps pinging and it doesn't get through.
(16:53):
Like the other day, I'll give you a great example, I was in this small town in Illinois last week and were trying to make a reservation for a restaurant in Davenport, Iowa.
We were about an hour away and the only way to make the reservation was through Google's AI.
(17:17):
So Google AI goes, we're gonna call the restaurant right now and make the reservation for you.
Can't get through to the, can't get through to the restaurant.
We will try again in 15 minutes.
And I kept getting texts three, four times.
Couldn't get through.
I just picked up the phone and called the restaurant and they picked up and I made the reservation.
Right.
So, like, this stuff is not infallible.
It.
Yeah, it doesn't always work.
Speaker 2 (17:39):
No.
And, and that's the thing though, man, is I feel like there's a. I feel like a lot of individuals are kind of like with everything in our society right now, they read a headline, they formulate an entire opinion on it, and they don't actually do any independent research or try on their own to go out there and do it.
Like, we've been utilizing ChatGPT and Grok and then a couple other AI tools for our content.
(18:04):
Not to, like, write it out, but to help us edit it, to help me come up with brainstorming.
Yeah, brainstorming.
That's really what it is, right?
Because it's like, I look at it as I put out on average of 20 to 23 podcasts every single month on a variety of topics, but there is a lot of overlap out there in what topics are top of mind in the industry right now.
(18:27):
I can't use the same episode title for every single AI episode that I do.
Right?
And for me, it's like, that's what I love utilizing these tools for, is to get in there and mess around a little bit.
And I'm like, oh, shit.
I like the way that topic is structured and then that topic is structured.
I'm going to combine it right now and I'm going to create my own.
(18:47):
And it is just a way for me to help spark my creative juices.
And I think most people are going to look at this as like, they're just going to ask it a question and be done with it.
Like, dude, I have, like, I kind of feel like a psychopath.
Like, I have actual conversations with it to be like, no, I need you to do this.
Speaker 3 (19:04):
There's been guys who've gone, like, have had like, mental breakdowns doing this.
So you gotta make sure someone's in the, like, in my room to make sure you're not going crazy.
Speaker 2 (19:17):
You know, to me.
But it's like, I, I look at it is as like I'm training it myself.
And, and that's also another, like, discussion that I've had is like, maybe I just buy my own off the shelf AI bot and then just train it myself and just do it that way.
And you know, Build it out like that.
And I feel like there's going to be an opportunity out there with it.
(19:40):
But I think, like there's going to be two groups of people out here, Eric.
They're going to be the over automation and then the no automation on the majorities.
And there's going to be a sliver of people who actually take the old school methodology with automation and then accelerate it with.
Yeah, and I think like, they're going to be the ones that grow.
(20:01):
And again, this is just a very bold prediction.
I think if you look at the top 50 freight brokers out there right now in the next five years, it could be filled with companies that nobody had ever heard of before that went from a $10 million operation to a $400 million operation in a matter of months because they just did the right thing and made the right calls.
Speaker 3 (20:26):
So the other thing to be like, really careful about when you talk about AI is like most people's.
Most people's conception of AI is what they've experienced directly.
So.
ChatGPT.
Yeah, co pilot.
We have, at S P where I work, we have an internal one that we use that is like.
(20:51):
So I, I mentioned I was at a conference earlier this week and literally I put up.
The first thing I did is I put up a picture of a tree and it's like, if you think of this tree is AI, like the whole totality of AI and there's a branch that does this.
And then off of this big branch, there's like three branches that stick down.
(21:14):
That's AI.
Like, and what we're talking about, what most people's experience with AI is like one small branch off of a big branch and it's not even off the main trunk.
Like the main.
What AI has been developed over the last 70 years is the main trunk of the tree and all these big branches.
(21:36):
You know, things like fuzzy logic and deep learning and stuff way beyond my brain power.
And LLM is like an offshoot of one of those that just people have gotten familiar with.
It's.
It's their window into AI, but it's totally.
It's not the totality of AI for sure.
Speaker 2 (21:59):
Do you think people are underestimating the power of AI and do you think, and I'm asking you this because you live in D.C. do you think there will be some form of federal regulation on it?
Because it's a lot more powerful than people think at this current juncture?
Speaker 3 (22:22):
I Think it's pretty powerful right now.
I think it's.
I think actually probably more than regulation.
The thing that is preventing it from, like, from it being.
Reaching the ceiling of its power is like, is culture, is our.
Most people still don't.
Most people use it in a very, like, superficial way.
(22:45):
They don't use.
They use it to replace Google Search.
Speaker 2 (22:48):
Yeah.
Speaker 3 (22:49):
Or they use it to replace some conversation that they have with a person like you were talking about before.
They aren't using it to, like, set two, three, four levels of depth.
And mostly either because they're scared of change or they literally have no idea what to do with this tool.
(23:12):
It's like, it's.
It's sort of like if you handed me the keys to a.
Like a.
Like the space shuttle.
Speaker 2 (23:17):
Yeah.
Speaker 3 (23:18):
What.
How do I even get started with this thing?
You know, like, so it's incredibly powerful and were probably underestimating the power of it.
But also, like, it's only powerful to the extent that we let it be powerful.
And right now we're not letting it be powerful.
(23:39):
Not because we are less because we're scared of it, but more because we just don't even know how to let it be powerful yet.
Speaker 2 (23:46):
Yeah.
Speaker 3 (23:47):
And now in terms of regulation, I don't know.
It's very unclear to me what government can and should do to limit this.
Like, how do you stop.
How do you stop someone working on a computer in their house developing something that eventually lets out Pandora's or opens Pandora's box?
(24:12):
Like, I don't know how you regulate that.
Honestly, there's literally no constraints on coding.
So I think it's more like we have to be way more educated as a society about how to interact with this stuff and how to maintain our.
What makes us human.
(24:33):
And so I.
One example I give all the time is, like, I don't know what your calculator was in school, but, like, when I was in high school, Casio, everyone had.
Well, everyone had a TI81 graphing calculator because you needed that for.
I Forget what algebra 2 or whatever it was.
Speaker 2 (24:52):
I wasn't in advanced math, Eric, so we can just curb that is what I. I wasn't.
Speaker 3 (24:56):
I'm not a mathematician.
Even, like, the basic kids got.
Were told to get these.
These things because it was.
It didn't make sense for you to break a protractor out and a compass and like, for sure, you know, you.
You can do this all digitally.
Right.
I mean, there's a.
There's a.
A manner of thinking that like, this stuff should.
(25:19):
Takes stuff off the human, the plate of the human brain that we're not necessarily best equipped to do.
Right.
And so if you take that perspective, you still have to decide what.
We still need to decide what it is we're really good at.
(25:40):
Like creative thinking, moral type stuff.
Like, it's not clear that machines will ever have the ability to do those things to the level that humans do.
So empathy, you know, things like that.
Like, those are the things that we need to cling to as we start to hand more and more off of this.
(26:01):
Because we will, because it will look, it will be very clear how easy it is to hand things off to systems.
Speaker 2 (26:07):
Yeah, no, and that's where I feel like it's going to be a, you know, kind of like a big bullwhip.
I think, like, it's going to go really far in one direction.
And I feel like, again, I don't know if this will happen, but I just feel like in time humans are going to realize like, hey, I think we did too much and we want to go back to just being humans again.
(26:30):
I don't know, man.
I just don't know if you can erase thousands of years of tribalism that we are as people.
Speaker 3 (26:38):
Can I say something that I feel like I've noticed people talking about more is the rush to AI.
Everything is.
Because most people feel completely overloaded in their lives, work, personal, everything we get, we take in too much information, we get too many emails, we have too many, like, authorities sending us mails to do this and that.
(27:02):
We have to fill out too many forms.
Everything is so frigging complicated.
And it seems very appealing to have someone take some of that load off our plate.
So I agree.
I think there's going to be a backlash where it's like, we need humans to be doing things, but it needs to be a reasonable amount of things that they do in a day.
(27:24):
And it can't be that we're just like trying to emulate supercomputers and just juggling a million different things all the time.
Speaker 2 (27:31):
I think the most powerful thing a lot of people can do right now is literally just shut their phone off.
Speaker 3 (27:37):
For like, for sure.
Speaker 2 (27:40):
And, and it's like, I won't go down.
I, I could have been like, oh, Eric, welcome to the dark side of tinfoil hats.
We can go on about that, about with big government and everything, but we won't go there on this show today.
But I, you know, I look at it is, you know, you do need to give yourself a break from social media and all of this stuff, because I feel like people get a little too wrapped up into it, right?
(28:04):
Like, they get a little too wrapped up and needing to have an opinion on everything.
And it's like, dude, for me, it's like, I. I literally just take the stance of, like, I'm just not going to comment on anything.
I don't even reply to, like, most comments and stuff that I see or posts out there that I see.
I just don't do it because I'm like, dude, this doesn't affect my life, like, what somebody else is going through.
(28:27):
And when I say somebody else, you guys, like, 99% of the people you see online are not your friend.
Right?
Like, they're just fucking people on the Internet.
Yeah.
And I'm like, I don't feel the need to comment on some of that stuff.
And I feel like so many people get so wrapped up in.
In everything that's going on.
This is just another layer of getting wrapped up into stuff that I feel like the most powerful piece of advice I can give the majority of people.
(28:51):
Shut your phone off for like an hour.
Speaker 3 (28:54):
All right?
Go look.
Go look at a mountain or, you know, get some sun on your face.
Speaker 2 (28:59):
And then another thing, too, man.
Like, I think a lot of people will also come to the realization we're not as different as the Internet makes it seem.
You know, like, when it boils down to it, we're not.
Speaker 3 (29:08):
You go like, one of the benefits.
I get to go to conferences all the time and, like, you go to conferences and I.
It's like, I.
Sometimes I think I catch myself going.
I look around and I'm like, I bet if were all sitting behind computers, everyone would be, like, antagonizing each other about some stupid detail.
But here we are in person and we're like, you know, having coffee and chit chatting and like, oh, that's interesting.
(29:32):
And, you know, it's totally.
You're totally right.
Speaker 2 (29:35):
Yeah, I. I just look at it as is.
Like, yeah, you know, there's, you know, and especially, like, with.
With where we're at with AI and technology and everything and, you know.
Yes, Ryan Schreiber, this entire episode has been about you, actually, the entire time.
So if you go back, listen to it, and then share it out a bunch, then you can show everybody how we only talked about Ryan Schreiber.
Speaker 3 (29:55):
This started with.
We started with.
On this day.
Ryan Triber was born on.
On week one.
He did this on week.
Speaker 2 (30:05):
Dude, I just like I, I look at it is, you know, there's a lot to be seen.
There's going to be a lot of great tools that are going to come about this.
And, you know, I feel like you do have to give it a little bit more time on how you're going to utilize it inside of your organization.
There's going to be a lot of great tools that are.
Have yet to be developed, that are about to be developed.
(30:26):
And you know, I look at it is as, you know, a good gauge and a good place to start is like, what are your customers asking of you?
Are your customers coming to you and asking for any of these tools?
Because that's one thing.
You know, again, like, I actually move freight.
I don't work with the largest shippers in North America, but the shippers that I do work with have a lot of volume.
I, I don't have a big push from them about, hey, you need to do this.
(30:50):
You need to have this tech and this tech.
Speaker 3 (30:53):
they're not like, Chris, I need you to optimize my workflows.
Speaker 2 (30:58):
That, yeah, that conversation doesn't happen.
I'm not saying it doesn't happen out there, but from my experience, and again, I feel like with a lot of companies, you know, if you don't know where to start, maybe gauge on what your customers are asking of you and your capabilities.
And you know, I, I think like a lot of organizations out there, Eric, a really good tracking system and some really good load updates would serve them very well out there in the market.
(31:26):
Because if I'm talking to any prospects, which I, you know, I do, I cold call every single day.
That's kind of the big sticking point with a lot of them is it's like we just need to know what's going on with our freight and.
And that's it, right?
So, yes, there's some organizations that are a lot more complex, but I feel like the majority of them out there might not be as complex as you think.
It might not have the.
(31:46):
As big of requirements as you think.
Speaker 3 (31:49):
Yeah, that's fair.
Speaker 2 (31:51):
Eric.
I appreciate your time, man.
How does anybody.
You guys got your conference coming up here and I know these fly by every single time.
Even though were late, we already blew past 30 minutes.
Like inland.
All that stuff's coming out there, man.
Drop that in there for people.
Speaker 3 (32:04):
So yeah, we're.
Our Inland Distribution conference, or Inland25 is September 29 through October 1 in downtown Chicago.
We have an awesome program this year.
Attendance is looking great, even despite.
Despite the market.
And, yeah, Joc.com is a place to read stories.
(32:26):
I'm on LinkedIn.
I'm also still, to my.
You know, to.
To your point earlier, probably to my detriment, I'm still on Twitter.
But, you know, I. I have a high pain tolerance, I guess.
Speaker 2 (32:38):
So, dude, I. I try and stay off of Twitter as much as possible.
I stream.
I. I do.
I stream this show on Twitter just because, like, there's a.
There's a big community, there's an audience there.
Yeah, but I'm like, man, that's.
That's one of those social media platforms that I'm on for about eight seconds, and I want to, like, drive my car into oncoming traffic.
(32:59):
I'm like, this cannot be.
Your post last night summarized it perfectly.
This cannot be where we're at as a society.
Speaker 3 (33:07):
You know, it's funny, I, like, I don't quote Joe Rogan a lot, but he had a bit of a, like, way before he became big, where he talked about, like, whether humans were getting dumber generation by generation.
Because I forget the reason he said, but I have to go back and find this.
But I am like, man, I think he actually was right about this.
He's like.
He's like, the Egyptians 2,000 years ago built the pyramids without, like, any machinery.
(33:31):
And like, now we seem like they have a dumber handle on basic facts than they did, so.
Speaker 2 (33:39):
It's so damn true, man.
Eric, thank you so much for your time.
That's going to be it for today, ladies and gentlemen, as always, if you guys got value in what you heard, subscribe to the show.
You guys.
And if you're feeling really ambitious after this one, rank the show on itunes and Spotify.
Because if you see value, your network's going to see it as well.
I appreciate you guys.
I love you guys, and we'll be talking to you soon.
Speaker 1 (34:05):
Came back with a bank window down yelling now money anything hey, oh got the foot on the gas pedal to the metal when I'm getting to the back hey Got the foot on the gas pedal to the metal when the lane moving fast hey Let them all cross if they hate then let them hate them make a bigger boss hey.
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