Good Morning World! Time for some AI.

Good morning, LinkedIn friends. Value First Nation, welcome to another episode of Value First AI Daily, your collaborative intelligence report. It is Wednesday, March 11th, 2026. George, Nico, how we doing, fellas?

Doing very well. Doing, doing real good today, actually. How about you, George?

Doing good. It's Wednesday. I got one more day and then I'm on vacation with the wife, uh, to go celebrate our 25th anniversary. So doing good, doing good.

Nice, nice.

Congratulations indeed. Uh, we'll miss you for sure. Um, uh, I'm doing great as well. Uh, big thanks to Nico for finally breaking the seal on what sponsorship could look like for all of the media that we do. Our official first, first sponsor of any show, Hub Helper Harry, your friendly guide to everything HubSpot. I'll drop a link in the YouTube comments, but appreciate you, Nico, for both the app, and, you know, uh, getting a spot on the show.

Very nice.

Uh, for today's topic, um, I actually woke up, uh, and caught Marketing Against the Grain. They did like a little 15-minute thing on, uh, reviewing, reviewing this, uh, the labor market impacts of AI. Um, I think I had only heard about it on, on, uh, on some podcast episodes. Uh, so watching it today and seeing this, this diagram basically really caught my attention, and I thought it'd be worth chatting about with you fellas. Um, long story short, what we're seeing here is in the blue we've got theoretical capability, uh, of AI based on occupational category, right? So management, business and finance, computer and math, architecture and engineering followed around. Uh, so in theory, AI capability is almost at 100%, uh, for some of these. Now I'm not sure, maybe it's in the rest of the article, what like 80% is versus 60%. Um, but the stark thing to look at is observed usage in red here. Yep. Right. And this is what people are actually using AI for in these domains, um, or how much they're using it for these domains, which obviously we, we've talked in, on, and around this topic for a long time, but saw it today and talk about opportunity, folks. If you're— this gap here, right? And when I say things like AI is already smart enough or good enough in so many use cases, like this is the kind of thing I'm talking about. And that means the challenge is a human, is a human one, like human capability, human understanding, human ability to change, adapt, and organizationally integrate it into the work. So I'd love to hear your thoughts on seeing this diagram and what you've been seeing out there as, as this dropped, uh, last week, I think 5 days ago.

Uh, for me, it, it is pretty accurate. The— it's, it's telltale, and it's very unfortunate. Like, the shape of it is very unfortunate. Um, And that's mainly because the actual use cases are all monetary driven. They're not like, they're not care-driven per se, right? Um, but what I find like as the silver lining to this is the amount of opportunity that is still like massive. So like every just, I don't know, square millimeter between the red and the blue and the edge of that blue represents how much runway you have. And if it's not highlighted in blue, it hasn't been explored yet, in my opinion. Someone hasn't looked at the practical application because I'm I'm telling you, it's there in those areas that are marked in white that have not been highlighted in blue. I have talked to people about practical application of AI in those areas. It's definitely possible. It's definitely there. Just nobody's doing it yet, but they will be. So like the, the whole expansion on economy, expansion on, uh, jobs, expansion on like what we're going to be doing like as a whole, like that's To me, that's what I'm looking at. I'm looking at like the very beginnings of this explosive movement of both like tech and economy.

So my brain goes a couple different directions. One, I don't know the way this is laid out what 1.8 point whatever represents honestly. Like, I can make some assumptions. No, no, no, scroll, scroll back down. Now we're talking about this graphic you're showing. Uh, the second thing that my brain goes to is observed by who. The third thing that my brain goes to is Theoretical. Oh well, who made it up then? The other thing that is blowing my mind about this chart is I'm guessing marketing is in business and finance. Yeah, sales has its own category. That's interesting. Where, where the heck am I at in this chart? I guess in some clump somewhere. So like, I look at this and I go, and like these aren't actual numbers. And by the way, then my brain kicks into something really not even maybe but sort of relevant, because Nico's like, in the white space, I'm— it's there. So I look at grounds maintenance, and I think last week about a story that— no, yesterday— that Chris told about it was raining and the sprinklers were on. Well, grounds maintenance— couldn't AI tell that it was raining and couldn't it shut the sprinklers off? Yet in grounds maintenance, it's zero. Like, so this— I don't— like, I will not lose no sleep if I don't look or think about this chart after today's episode. That's my thoughts.

Fair. Um, I think the, the primary effort by Anthropic here, and I think like Dario has been pretty consistent on trying to get the word out about any and all risk, like no matter how high or not high it is, um, like new measure and early evidence, right? Is the key and like starting somewhere to create just a framework to start understanding. Definitely, as I hear, as I heard, you know, Kieran and Kip talk about it on their episode, as I inherently know what we've been talking about in terms of like how to help people understand it's not about like you should not be asking— leaders should not be asking the question how AI works. They should be asking the question how will AI work with the humans in our organization. That is the gap. No matter how big or accurate these numbers are, we all know there's a clear gap between usage and capability. Um, I agree, George, like Having office and admin and sales over here. And then like, like, it's just again, we're reminded of how dysfunctional the natural structure of how people look at just business in general. Like, just how the hell is it over there? How is it over there?

Yeah, so here's what's coming to mind, okay? Like business is a team sport. AI, I think, can be a team sport, but I think right now everybody's playing like pinball. It's like individual usage to the highest level in which that one human can do. And then it's a team of humans playing pinball in a game room together. Like, you know what I'm saying? So like, it's, it's not a football game yet. It's not like AI doesn't quite feel like a team sport. And, and to kick back to this theoretical thing, like, if you go just to the definition of theoretical, right? Concerned with or involving the theory of a subject— subject today, AI— or area of study rather than its practical application. The message that I would say out of today is like businesses, business leaders, employees, humans in life need to find the practical applications and start to use it. I don't need to theorize how I could I just need to think and/or dream and do. And so honestly, I look at this red and I look at this blue and it slightly just kind of like pisses me off because it's not the story that I want to pay attention to. The story that I want to pay attention to is, is it possible? If you can dream it, you can do it. If you are a sprinkler company and you're tired of then build it.

Like, I mean, it's definitely true. That's, that's the way I, I look at it as well. I don't really see a whole lot of, you know, there's— I don't know, I'll say this much. I was telling my wife the other day it's really tough living in multiple timeframes at the same time. You know, we talk about like now, we talk about like what's, you know, what's coming. I try to think about 3 months from now and I call 3 months from now like immediate or impending impact. 6 months from now is right around the corner for me. And like a year from now is, you know, don't know, right? Like that's, that's, there's like a big, big old question mark, right? So I look at stuff, I look at graphs like this, I think about, excuse me, I think about the impact on job market. Things Dario has said in relation to, uh, job market, like especially white-collar job market. You know, it's, it is exactly what you're saying, uh, Chris. You know, it's, it, it's a matter of humans. And I remember very early on when my brother asked me like, hey, so with all this advent coming and with all this possibility and, you know, 50% job loss in white collar and all this kind of stuff. What's to prevent all of that from happening? And I said, the only thing that keeps any of this at bay is people. Either your boss who at, you know, your job who doesn't want to implement or doesn't want to replace or doesn't want to whatever, or it's government. That steps in and puts in a policy or puts in a regulation or does what they, they need to do. But, you know, the evolution is going to happen one way or another. The speed is— it's going to eclipse whether we want it to or not. It's just a matter of like, are we going to be able to not necessarily cope with it? I think, are we going to be able to help everybody to get to this next place that we need to be, right? With— because look, we had so much time with phones, we had so much time with, uh, email, we had so much time with computers, right? Not a whole lot of time with this. Like, we're already 3 years in and people are really just losing their minds. I, I watched a story this morning about college kids blaming AI for like everything already. We're not even that far in, and I'm, I'm listening to college kids say like AI is the, the source of all their woes. I'm not saying that this is like nationwide. I'm just saying like saw a couple videos and they're saying that it's, you know, that's the reason they can't get jobs because, uh, businesses aren't hiring. And I— that I, I see. I've been following that for a few months now. And I can only guesstimate that yes, it's very difficult to graduate college now and get a job, especially any type of job that requires you to use a computer. So I know it's definitely happening, but from, you know, there's always that balance from destruction breeds creation. So if you can't find a job, then I think that You know, just make one.

Yeah, yeah. I mean, that's easy for us to say, but I do agree with you. I feel like you can make a job. But, but here's the thing, my brain is going like 100 miles an hour, and I, I honestly, I, I'm not trying to be that guy, but I feel myself being that guy this morning. I could just tell the energy. Look, you said evolution. I don't know if that's the right word, maybe innovation, but being left behind in what's innovating around us. You also said something that basically broke my mind, but that's because I think I have a relatively strange relationship with this thing called time. Because at, you know, 18 and a half, like having a near-death experience, I just think about it differently. And that is, you're like, tomorrow, next week, you know, 6 months, you don't know, bro. Tomorrow, you don't know. I could walk out my house, walk down my driveway, a car could go off the road, it could be over. Like, there's this thing that people are trying to do called control, and this is maybe one of the most impossible things to control that we've ever dealt with in the history of technology and mankind. I got very specific there for a reason, because there are some other things, but technology and man and control. This is very difficult to control, okay? And so like this mindset of like, well, in 6 months— no, well, today. Like, if you are not, uh, you know, carpe diem, if you're not seizing the day, then you're falling behind, plain and simple. And here's the thing that also kills me about this conversation is we humans are really bad at like future. I'm gonna eat these 12 donuts today because in 2 weeks I don't care if I gain 20 pounds. I'm not thinking about it. This college, uh, conversation of people not getting able to get entry jobs, it's true. Like, I've seen multiple times where even talking to one of my family members, AKA one of my brothers, well, we can keep the seasoned people on with AI and let these people go because they're not really up up to like what they should be doing anyway. Those seasoned people die. They expire. Like, so what happens when all the seasoned people expire and then you didn't have the new force that you were growing up? Where are you at then, Mr. Business Lady or Mr. Businessman, when all season has expired and there's no spice in your spice racks to keep the business going? I don't know, maybe you're hosed, screwed, or in trouble. Again, not trying to be that guy, but we're not paying attention at the wheel.

Yeah, and, uh, to your earlier point, like, we have to find a way to help people give themselves permission to dream, right? Like, you have to be able to dream here, to— like, inside business, app, and personal, wherever. Right? Like dream in ways you have not been allowed to before. Like somebody else telling you, no, that's not your lane. Stay in your lane. Right? And tie that to like all the businesses trying to sell you stuff and build, build the solution. Right? And we don't think into the future very well. Right? So what? Has happened. And this is where it's like, have we learned nothing from, from poor adoption rates and, and messy CRMs and lack of digital transformation? And that we're just gonna try to rerun it with AI? Like, and this is what drives me crazy with, with HubSpot, right? As I come over and I look at this channel, right? And kind of what they're getting at, like the opportunities Like always come down to, oh, here's this very specific use case that this, this, this case study over here had a ton of success. They got a bunch of leads and they went up 10,000%. Their resolution rates went up 40% because they implemented Customer Agent. Now you can do that. Well, guess what doesn't work very well? Finding one use case, getting a quick win. And then somehow it just disseminates into the rest of the organization. And as I download the adoption playbook, right, I find one thing at the end that I'm like, all right, I can get behind that, right? Mark Robards, we have huge functional boundaries between sales and finance, between product and customer support, between marketing and sales. Why? Because we're limited as humans. So we had to have these functional silos, but when we're in an agentic world, those go away. Theoretically, they go away. Practically, can a business remove them, right? And that's the point here. Like, this first bullet is not quick win for a reason. Right? And the, like, transformation instead of optimization, right? That's how I think this happens. It's not the slow boat to somewhere else, right? It's moving way too fast. And that's why it's up to the leaders to actually, like, they Nobody else can do this for the organization. Like, you can— after this happens, you can give it to like an AI orchestrator or some chief AI officer to, to then like make sure you're gonna leverage the hell out of and make sure you're successful with AI. But before that, if you don't have your leaders like building and activating in some kind of way there's no way to understand the urgency and the opportunity at the same time. Some, like maybe the brightest of CEOs and leaders that can see everything and know how to move people, can do that. But most are not like that in my experience. They really built an awesome product or they sold a great vision. Right, right. They are not well versed in the, in the world of, you know, moving, uh, like change management and process management and— right. But what's cool is you can take those people and take them through this process and then like they get it. Somebody at some point has to say, okay, we are transforming our operating system. As a business. And if we don't find it, like, if, if we need to find use cases that are tangible, then every team needs one of those. It can't be customer success, all right, go do customer agent, and then, uh, oh wow, tickets closing fast, okay, sales, like, go for it, like, go ahead, like, go, go ahead and start, start using, uh, using AI to get your job done better, like based on this customer success use case. Um, so again, we're back to mindset is everything. And as long as these silos exist, as long as the, the concept of stay in your lane— like, stay in your lane is basically antithesis to dreaming, like dreaming of what's possible, like in a business. And if you haven't created the space for that, which is why individuals like us, individual entrepreneurs, like they don't have, they have one lane. It's like, go as fast as we can to solve the problem that we want to solve in this moment. And now AI is making that more fun and easier than ever. And I think it just doesn't have to be so hard when applying it to the organization, as long as you, you just have to come at it from these. Again, we have to like everything we've known about business, which has been based around silos, marketing and sales, because humans could They needed some management. They needed some structure. Well, now we got— we got AI.

Oh, I need you to listen up close. Screw a lane, build a superhighway. Like, screw a lane. Like, what are you talking about? Like, quit thinking so small. Like, you need to think big. Like, Okay, I'm just gonna not say what's on my mind because I will offend too many human beings if I continue down this road. No, actually, I will say it. Can you quit trying to find case studies and just effing become one? That's it.

Oh, uh, 100% agree. Um, and we'll leave it there. We'll be back tomorrow, uh, with another Value First AI Daily. Uh, remember to check out hubhelperharry.com. Uh, have some fun getting some help with HubSpot, and, uh, we'll see everybody, uh, next time. Have a great Wednesday.

Peace out.