Transcription
I was recently in New York talking with the Chief Information Officer of one of the state's agencies, and he clued me into an interesting way of thinking about the effect of AI on job roles. It's a subject a lot of people are concerned about these days, and for good reason. I've done videos previously on the question of whether AI will take or make jobs. Spoiler alert, the answer is a definite yes. And about a thing called Jevons Paradox. And how that can be seen to predict an actual increase in the need for people in the AI era, more on that later. But what are those jobs going to look like? Will we all be slaves to the AI machine, plugged in matrix style to some collective brain? Well, that might make for a great sci-fi, but the reality is far more appealing. In fact, if we do this right, we might actually find that AI has given us all a promotion of sorts. Stick around and I'll explain.
Let's start off by taking a look at traditional job roles. And we often think of these in terms of a pyramid, where we've got a lot of these kinds of roles that are entry-level. And these are where someone has got to just do stuff. People above assigned to someone down here, and then there's something that's got to be done. Sometimes it's not the most fun work to do, but it's work that has to get done. It's kind of the grunt work, and it ends up falling down to the folks who are doing this. And as we move up this pyramid, generally speaking, we end up with fewer and fewer people in these other roles. We move up to a more experienced role, where their responsibility is to own a major piece of work. Maybe they are looking at not just writing, maybe a programmer might write an individual module here. In this case, they're responsible for an entire section and the integration amongst those modules, just as one example. Then we move on up to senior level. And maybe even to the managers in this. And what they share in common is that they're looking to lead individuals. They're gonna lead people. So they're gonna oversee the work of the ones below and make sure it all comes together. Then we move up to a narrower and narrower portions of this pyramid. We have executives up here, all the way up to the C-suite, the CEO and so forth like that. And their responsibility is to basically lead the leaders. So they're looking across the entire organization. This is how we have traditionally looked at job roles, and they move from entry-level all the way up to the top.
Now let's see what happens if we take that pyramid and turn it into a diamond. So now what we're gonna do is we're gonna have fewer of what we considered the sort of traditional entry-level jobs. But hold on, there's good news in this. We're gonna have a significantly larger number of people in the experience category, and then as we move up, we'll have more in this sort of senior-level category, and then the management stuff and and so forth will continue with the execs and the C-level. So notice the relative size of this, and you can't hold me to this exactly because this is all approximation, but what has actually happened is, what happened to all the entry-level work? Well, in fact, AI is gonna be doing a lot of that for us. And that we expect, because we can see that AI can do a lot of those kinds of functions that in the past we really needed people to do, and now we don't need people to. So does that mean all those people just go away? No, smart organizations won't do it that way. They're gonna do something different. They're gonna take the entry-level positions here, and some of those will still need to be done by people. But a lot of those will essentially move into the kind of work that we used to consider an experienced-level person would do. Because this experienced-level of person will now have an AI team that they're commanding, and now they're owning a larger portion of the work. They can use the AI tools in order to accomplish what in the past, they would have needed an army of people to do. So these people have actually moved up on what was the pyramid. Same thing happens over here. Some of these experienced people can now move into what are more senior-looking jobs in terms of the way we look at job descriptions today versus what they're gonna look like in the future and so forth. So we're gonna have a lot more of this. This is essentially the promotion that I'm talking about. You got moved from one level of work, which in some of these cases down here wasn't very interesting, to a lot more challenging, a lot more interesting level work that's gonna happen here. And that's the promotion. And in fact, I'm going to suggest to you this is going to be even bigger, and we'll see why in a few minutes.
Now, what's going to need to happen, though, is I can't just take today's entry-level person and throw them into an experience-level position. What they're going to do, and it's going to be expected, is that the skills will need to change. We're going to need to upskill, improve what our skills look like. The things that used to be more executive-level functions, more decision-making functions, rather than just do, we're gonna need the even lower level within the pyramid, now the diamond, to accomplish. Also, we're going to need more experience. How do you get more experience at the entry-level? Internships. So be looking for those kinds of opportunities so that you can move into these kinds of positions. Also, we're going to see overall, I think the number of jobs for smart organizations will actually increase. That's why this diamond is actually a little larger than the pyramid was.
Okay, as I said, notice that the diamond that we have over here is actually larger than the pyramid. And why would that be the case? Why would we need more people if we've got AI doing a lot of this work? Well, let's go back to 1865 in the way back machine and see what a guy named William Jevons taught us. He found that back then steam engines were getting more and more efficient. And as their efficiency increased, a lot of people assumed we're not going to need as much coal, and therefore it would be bad for the coal business. We're not gonna need miners, we're gonna lay all of those people off. That's not, in fact, what occurred. What occurred then was as efficiency got up, it turned out that we could do more work with the amount of coal, and in fact, what that meant cost went down. Well, as cost goes down, well, then what else happens? What happens, as we know from economics, is that basically utilization or demand goes up. That's what, in fact, occurred. The demand on coal increased. In fact, the steam engines became more affordable. People could use them in more different cases, in more ways, and more people could have them. So therefore, we needed more coal. Now, in this analogy, you're not gonna like this part, but you're the coal. So we've got AI making us more efficient. So as AI makes us more efficient, the cost of doing the particular task will go down, and therefore, the demand on people who can do these kinds of things will actually increase. We're gonna actually do more things because we're gonna have more time. For instance, a smart company would look at this and say, you know what, I'm not gonna just leave my labor force the same or try to cut my way to the top because that doesn't work. I'm gonna do more innovation. I'm going to try to reach more clients because now I don't have to spend as much time doing this grunt-level work. I can let AI do that, and now I can use my people to do what they're best at. We can reach more clients. We can do more innovative projects. We can do more demand for the smart organizations that understand Jevons will actually go up as a result of AI. So I said you're getting a promotion. In other words, the kind of work, the quality of work, the nature of the work you're doing, will actually move up that pyramid into the diamond.
So what will those roles look like? Well, let's take a look. So for instance, I think as we move into using more and more AI that can do a lot of the just perform, just do this thing. Well, then that means we are more valuable in answering these questions. What is it that I need to do and why would I do it? For instance, what is the new area that we want to launch the business off into? What's the new project we want to work on? What's new capability that we would like to develop? In the past, we were limited, for instance, as a programmer. If you can program or can only produce so many lines of code per day, and that productivity figure limited what kinds of software products we could create. But if AI can create that a thousand times faster, well then I don't need to write as much of the code. I can spend more time thinking about what is it that we'd like to do and why would we like to do it? What's the purpose of this? What's going to meet the customer demand? What's going to anticipate what the customer wants before they even know it? And meet those needs and delight them in those ways. That's why we're gonna need more people that will be freed up to do more of the higher-level thinking. In other words, we'll be looking as people more at the big picture. We'll be doing more of these kind of architecture type of jobs rather than the hands-on kinds of jobs. We'll still need some hands-on, don't get me wrong, but less of it and more ability to move up that pyramid or up the diamond. And we're gonna be more involved in things like goal setting, telling the AI what we want it to do, and then supervising it. So we want to make sure that it does what we've wanted it to, and does it in the correct ways. What is a supervisor? What is a goal setter? Those are again, higher up on the diamond or the pyramid. These are more almost like management-level functions or certainly senior-level functions. And we're going to be handing a lot of these kinds of responsibilities off to what has traditionally been entry-level people, because the AI can do the grunt work instead of us.
Now, what kind of skills? We don't just automatically move into those roles. What are the skills that we're gonna need in order to accomplish that? Can't just take an entry-level person with no experience and just have them do that, or someone who's been doing one thing their entire life and they're not ready to change. So number one skill, flexibility. You have got to be able to be adaptable into this new environment. We don't know exactly where all of this is going to take us. The jobs of yesterday will certainly change. Some of them will continue. Some of them will change. Some of them will change in amazing ways, and then absolutely brand new jobs that none of us can anticipate right now are going to exist. The flexible ones as employees are gonna be the ones who are gonna win. The ones who're good at being lifelong learners. If you like learning, you're in the right time. You were born at the right moment because there's always something new to learn. And if you enjoy that, you will continue to be flexible and improve your skills because knowledge and what you know is gonna be super important in this. Another one that's really good to have is curiosity. You need to be curious. If you're not curious, you're gonna think about what the next big thing is. Those questions about what and why, those are curiosity questions. And curiosity is what will lead us into the next area. And the people that are the most curious are the ones who will be the ones taking the leads. You need to be creative. You need to enjoy creating and being able to do that sort of thing. Take your curiosity and turn it into a creative aspect. And then what I think is maybe the most important skill to have in the era of AI is you have to be a critical thinker. You have to be able to think about, again, what should we do? Why should we do it? Those are critical thinking questions. Just because we can do something doesn't mean we should do that something. So we need to think critically about the things we do and figure out what is it that our clients, what is it that our stakeholders really want, and leverage the AI and leverage our skills so that now we're in this new promoted state where we're looking at higher-level functions, we're gonna be doing those things. And we're going to need to be doing a lot of this. IBM is actually planning to hire two to three times as many entry-level people in 2026 as it did in the previous year, and that's with AI. If you're just looking to cut costs, that's not the kind of thing that you do. But if you're looking to grow, you're gonna need more people to innovate. We need more to reach more clients and do more things if that's what we're actually planning to do, and we are. Smart companies will be rewriting job descriptions to fit the new AI era, realizing that if they don't continue to develop talent, that pipeline will run dry.
Just to be clear, no, I can't get you a job. Do you really think they would let me make those decisions around here? No. But if you keep developing the skills I've discussed, AI will effectively promote you up the pyramid into the diamond. That's exactly what these fine folks are looking to do. They all survived my class at the university, so they can certainly make your organization better. And here's their message to you. CALL ME! All right, now you all have a final exam to study for. Get to work.