Workforce dynamics in an AI-assisted world

0:28Welcome to the practical. behind-the-scenes content, and AI insights. You can learn more at practicalai.fm. Now, on to the show.

0:48Welcome to another episode of the Practical AI podcast. In this fully connected episode where It's just Chris and I will dig a little bit into the latest news related to AI, hopefully share a few of our opinions and maybe some little nuggets that will help you level up your machine learning or AI game. I'm Daniel Whitenack. I'm CEO at Prediction Guard, and I'm joined as always by my co-host, Chris Benson, who is a principal AI research engineer at Lockheed Martin. How are you doing, Chris? I am doing splendid today, Daniel. How's it going with you? It's going great. It's been a productive week.

1:30We've had a customer visit and lots of interesting development stuff. And last week, we did a workshop. So lots of hearing all the different kind of archetypal use cases that people are working on. Lots of interesting questions. I think we're also in a hiring phase right now, which means I am thinking a lot about kind of what positions to hire in, especially in light of all the AI stuff that is happening and everyone talking about, oh, maybe you should consider AI could do this task before you hire someone in to do that. Are those discussions happening in your circles as well? Oh, they are. And I hear that a lot of people are asking me about questions like this, you know, increasingly.

2:26And it's funny that you bring that up. I was doing another podcast as a guest. And some of those questions came up in that podcast asking about kind of how we saw that. I think things are getting so fast. You know, we've gone through several years of big LLM experience and now the agentic world followed rapidly by a physical world. And people are really like paying attention to how their lives are starting to be impacted by this with with jobs being right at the top of that list. And, you know, concerns on what it is and what should I do and will I be replaced? And it's a mixture of excitement and fear out there.

3:03I know that you can't share things necessarily from your immediate actual day-to-day job always, but let's say Chris Benson in a fictitious world and you were, well, I guess you also have the nonprofit side of what you're doing. But as you're thinking about, as you would be thinking about in this context, like the world we live in now, knowing not the promise of what AI might do next year, but just based on capabilities now, the tools that you're seeing out there, and you are building maybe a small team for a new company. What do you think is kind of on the, you know, maybe positions or things that might be on on AI, which may have traditionally been a full time or a part time hire?

3:55What is your thought? Yeah, the sense I'm getting from my interactions with people and what I'm observing is still using AI mostly as a tool to empower people, though that might mean that there are fewer people in a given function than there might have been before. And, you know, like there's some really obvious examples that we've all seen, like like marketing material and using AI to to generate that and stuff. And so, you know, I think I'm not seeing AI like completely replace lots of positions right now. There's probably some here and there. But I think I think that companies are looking for efficiencies.

4:37and, you know, if a marketing department could be two people with AI tools instead of five people in a company, I think that's a really common approach that you're seeing right now, you know, today and over the last couple of years in terms. And I think there are many, many instances of that, you know, that small efficiencies, small functions that are being, you know, are task level things that are being offloaded, but which by doing that reduces total headcount, you know, to some degree. And I guess there's things that maybe people can do faster. So to your point, there's maybe fewer of a particular type of position that is needed.

5:20Maybe it's marketing or even development or other things. I also find it interesting that there may be things that people could do that in a certain position that they couldn't maybe do before and might have to hire like an outside agency or services organization to do, which is an intriguing part of this. So just thinking of, you know, advertising, PR, market research, Those, of course, are things that you mentioned, but also there's kind of like prototyping new software things, you know, proof of concept that maybe you would have to engage an external consulting firm or software dev shop, right?

6:13to do before that maybe you, even with fewer years of development experience or less exposure, could knock out internally? What's your thought on that kind of interplay with service providers and how I guess this world may impact the service provider side of things? So yeah, with service providers, I think it's an interesting story. I don't bring it up very often in our episodes. But before I was in the defense world, I spent a dozen years in the digital marketing world and, you know, as a CTO or other technical positions and stuff. And I think that it's really tough with these new AI tools to be in that industry at this point, because there's so much capability.

7:00You know, we've commented many times that, you know, once upon a time, we would say AI would take care of all the grunge work and leaving humans for the creative work. But we've actually kind of seen the opposite in some cases. And I think the the creative aspect of some service industries like that, you know, compared to AI tools, which may or may not be able to do it at the same level, but they might be able to do it good enough. You know, we you know, in software development, we often talk about good enough. And you mentioned prototyping a moment ago. And I think with the notion of vibe coding, making at least simple coding efforts for things like prototyping accessible to people who normally historically would not have been able to do that is also a bit of a game changer.

7:45And that means that that's another area where hiring externally or hiring that function into your organization is also reducing because you don't need that necessarily just to get a prototype. And, you know, it may be different for writing production systems. And even then, AI tools, as we know, have had an impact, though I think the impact on that can be debated on whether it's positive or negative and depending on who you talk to. But these tools are definitely changing many industries right now. And they may not be completely knocking out an industry, but they are impacting it in terms of its viability from a revenue standpoint and such.

8:27So, yeah, we're I mean, it's it's a concern. And I think most people start off thinking, well, most people that are kind of, you know, AI cognizant on a day to day basis, start off thinking, what tools do I have available with these new AI services and the models that I might host ourselves at our company? Can I do now that maybe I couldn't have done before? And how can that change my cost structure? Yeah, I I'm really intrigued by this service provider side of things, actually, because on the one side, there's maybe traditional things that people would have gone out and hired an agency to do.

9:04So maybe that's a new website for your business, right? Or a simple website for your business or some type of marketing assets, or maybe a prototype of a project, like a SaaS product or I don't know, a bunch of different things. Those things seem to be good targets for kind of the either vibe coding or kind of wrapper type platforms around certain AI systems. So, you know, for the very first, I think the very first one of our websites that we made for Prediction Guard, I just use one of those sites where it's like, create your website with a prompt, You just go in and prompt the thing like, I want a website for this thing.

9:50And it kind of generates it and you move around a couple of things and there you go. So I think that those types of things, the sort of non-AI things that are generated by AI are very much maybe those are, there's less of a need to go out and hire an agency or a services company for those things. At the same time, I do think it's interesting that if you look at building AI things for your company, so let's say you are a mid or large size company and you want to create this AI tool for your company, right? But the talent is so scarce for that sort of thing that really, I mean, if you look at things as a whole, OpenAI or companies like that are definitely not the companies making the most money off of AI.

10:48You know, OpenAI is losing a lot of money. The companies that are making a lot of money off of AI are Deloitte, Accenture, McKinsey, right? Those are the company it's absolutely raking it in off of AI, right? Because there's all of these companies that say like, well, we want to transform our company with AI. So you need sort of change management and you need to create these prototypes and maybe these AI tools that you're going to deploy across your company. You need to take care of the security privacy concerns. You need to have a strategy around it, a roadmap, like all of this stuff. And that is all very much tailored to what these services organizations do really well.

11:36And I think even smaller MSP type of companies that have a book of business and healthcare or other industries where the impact of AI is clear, they have a big win to have in this area too. So I find it really interesting on the services side where some things maybe are getting a little bit eaten up by AI, but the actual AI stuff, the AI transformation is actually very ripe for services organizations. It's interesting. It is. I mean, you know, I guess people are looking for guidance. They don't understand how. And there is, of course, this whole industry of consultants who are happy to tell you they have it all figured out.

12:25So, yes. And they may. And I'm sure that much of that they are very much helping people, but they are well positioned to do that. And that is kind of their business model. Right. Indeed, it is. I did a brief stint at Accenture as well. Uh, so I can, I can, I can attest to that. Yeah. Yeah. So maybe it is a bit of a mixed way. If you're an MSP out there, maybe you're, uh, you're, you're thinking that some things are going away, but there is maybe a big opportunity for you to go into this sort of set of offerings around AI services.

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14:03Well, Chris, we started talking a little bit about influence of agents and that sort of thing on workforce. There was a very interesting story that came out that intrigued me as related to this because basically everyone's saying, well, 60 % or 80 % or whoever's giving the percentage will say the majority of development work is now going to go to AI systems. systems. And it was very interesting because there was a story that came out. I mean, it was reported by multiple folks, I think. But this one I'm looking at is from Fortune. And the title is an AI-powered coding tool wiped out a software company's database, then apologized for a catastrophic failure on my part.

14:58And this was, I believe it was Replit that is the culprit here, which is a really amazing tool. And, you know, they have, I think there has been apologies and, you know, of course they're handling this in one way or another, but I'm sure this is not the only instance of this across these kinds of tools, but also it's a, it's maybe a bit of a wake up call for some people to, to understand that maybe these tools are moving at a little bit of a faster pace than what might be reasonable for companies to support just operationally and permissions wise and at scale, et cetera, et cetera. Any thoughts?

15:49My first thought was, you know, lack of guardrails, lack of consideration on that. And I don't know the details any more than you do, you know, other than what was in the article. And maybe part of my perspective is biased because of the industry I'm in. Being in defense, we're really, really cognizant of safety measures and guard rails and such like that in our industry, because obviously it can turn into a problem if you didn't have that. But I think other industries sometimes may need to stop and think. And I get that the marketplace is moving really fast and there are competitors that will eat your lunch quickly and you want to get to market with the best thing.

16:32But kind of at this point, you know, we're still fairly early stages in agentic AI. You know, a lot of frameworks are still under development. This is and so I think having a kind of it's a good thing to ask yourself what happens when things don't work out per your expectations. What are the guardrails for when things really go bad and maybe think kind of a little bit of maybe a little bit old-fashioned in terms of, you know, what can you do for data redundancy and backup and things to where if your AI experiment or effort does go off guardrails that you have a guarantee that you don't have real damage done in a large sense after that.

17:18Something that literally it has no permissions to. So there's probably some mitigating factors there that I'm not aware of. So I'm not trying to lay in on the company, but I would just urge people to think about worst case scenarios and maybe architect, spend a little time architecting for that. And then go do some cool stuff, but make sure you can fall back without blowing your company up. Good point. What do you think, one of the things I've been wondering around this is there's all of these tools coming out, you know, vibe coding tools, vibe marketing tools, vibe, you know, design tools, or even HR, hiring, recruiting, etc.

18:04Name any function. There's a way to do it with prompts or these sorts of tools now. Now, how do you think this influences the type of both education and professional development that people need to have coming into a job? Because obviously, there was maybe, and again, we only know what we know about this one instance of the database being dropped or that sort of thing. But I'm guessing that maybe and, you know, people can correct us on social media if I'm saying something wrong here. But I think in a scenario like this, regardless, there's probably some of this that's on the company using the tool.

18:57And like you say, the trust and the guardrails that are put in place around kind of how things are pushing to production and how they're iterating on their platform or code or that sort of thing. And there's part of it that's probably on the platform itself and how it's architected and failure modes and safeguards and that sort of thing. But part of it, I think, is, well, how should we train our new workforce such that they're ready to kind of team with AI systems in any role, one or the, you know, from not technical to non-technical roles? And how do people in existing roles that maybe didn't haven't spent their career using these tools, how do they kind of how should they professionally develop themselves to be proficient in this new space?

19:55Any thoughts? Yeah, it's something I think about quite a lot on several factors. There's there's my own career, you know, as we're as we're working through things and things are changing constantly. And I also have a 13-year-old daughter who's going into eighth grade. She'll be in high school soon and then into college. And we are living in an age of experimentation right now because these technologies are coming so fast that the nature of what it means to use it from one year to the next is very different. You know, 2023 to 2024 to this year have all been distinctive in terms of how these tools are able to affect our jobs.

20:37So I think the first thing is, I would say, kind of accept it, accept the change. And I see, you know, I see a lot of people who are highly technical developers, things like that, who probably should know better, kind of resisting and all that. And so I think the first thing is to say, this is happening and it's not going away. And then the second thing is on individual roles, on individual jobs, to try to imagine where things might go given the tools that you're seeing today. What do you think might change incrementally tomorrow? And what kind of trends are you seeing in your particular industry?

21:13And go ahead and get ahead of that curve. And I think that's really valuable. I think it's hard to do. So it's very easy for me to go make a recommendation like that. But seeing the future is not easy and being able to do that. So I think my recommendation is, given that this technology is only going to continue to grow and change things, accept that your job is changing, accept that the vision that you had yesterday is not going to be what happens tomorrow. And so try to track on what you're doing, embrace the tools and figure out what's changing your job. How can you make it a net positive instead of a net negative?

21:52And those are very generic, but I think it's a very job specific, you know, set of tasks that you have to do in terms of that. And I think that starts with education. It's one thing to be doing it on the job like we are in the middle of a career. But how do you train today's youth to to do that? They're really good with these technologies, but they're not the ones setting the curriculum. It's us older people that are setting the curriculum. And I don't think we're doing them any favors right now in school curriculums. They're definitely not set up for success yet. How far behind in general are we, do you think, on that front in terms of, let's just say, college grads coming out into the workforce in terms of what maybe, you know, take any field, accounting, marketing, communications, business, whatever it is, how far off do you think we are in terms of the realities of what day-to-day work might look like with these tools versus how that's being represented in the classroom?

23:01Any insights? Yeah, I think look to how people are doing it in a hobby sense. Because people who are interested in adopting these technologies. We've seen this for, I mean, this is not new. This is for many, many decades. Companies tend to adopt what their developers go home at night to their home and play with and are interested in because it's the cool thing to do. And I think you could expand that across a lot of different fields and industries. What do people do when they're doing it on their own time because there's this new thing out there? And if companies were smart, they'd pay attention to that.

23:38If universities were smart, they'd pay attention to that and track that fairly early, kind of what the maker space or the hobby space is doing and build curriculum around that. Because right now, I mean, as we sit here today, most schools, if students go in, the professors are trying to find ways to keep students from using models that are publicly available to do their homework and stuff. And when I hear, And every time I hear an academic say something like, how do I keep my students from using chat GPT to cheat on their homework? I'm like, well, you're teaching the wrong thing then, because that that that model is never going away.

24:16So if you're teaching something that that's causing you a problem, then you're doing your whole curriculum is off track. And I realize that may not be the, you know, a specific teacher's ability to change overall curriculum. But it's certainly university and school leadership, school system leadership that should be doing that. So there's a big correction that needs to happen in education that companies would be very smart if they could also track that very early and go ahead and make adjustments earlier rather than later. Yeah. And maybe part of the struggle here, which I may be just playing devil's advocate a little bit on the edge.

24:57Well, there's a lot of, I think, as everyone would recognize, there's only so fast that education can move just because of bureaucracy and other things. But just putting those things out of the, I mean, this is also true probably for companies where you look out around the landscape of AI tools that can affect my job. And you look at the snapshot today and then you look at the snapshot next week and it almost seems like it's totally different. There's so many things coming out and I can put in the investment to learn this thing. And then next week, it seems totally useless or could seem totally useless.

25:40How does one out there that's maybe listening to this navigate that kind of whirlwind of releases? So I don't plant an anchor in any one thing as a long-term bet. I think to win these days, I think you have to embrace that learning mindset. And it's very cliche to say that, but I think you have to do that in your day-to-day actions. I'm at an age, I'm 54 right now, closing in on 55. And a lot of my peers in terms of age have already just kind of given up. they've already decided what they think their worldview is and they've stopped and planted right there. And I think it's exactly the wrong thing to do.

26:26I think the world is changing fast and to continue to be successful and happy in such a world, you have to roll with the world on a day-to-day basis. And you may invest in something today based on what you think tomorrow looks like. And you may realize in a few months that that's not the way things are going and you should be ready to pivot again. And so there is a never ending series of pivots or, or adjustments that you need to be making on an ongoing basis for the rest of your life, all the way till the day your dying day. And if you ever quit doing that, you're putting yourself in a worse position.

27:03So that learning mindset is a, is an action based, uh, uh, activity. It's something that you're, you're literally doing all the time. And I think people who can do that will tend to be more successful and happier in what they do than people who just resist and resist and plant flags. So that would be at 54. That's what I think I've learned. Well, I definitely. So there's a whole element of this that really has nothing to do with AI, which is also kind of based in neuroscience. And, you know, I read a lot about like dementia and these sorts of things as, you know, the sort of that's occurred in my immediate family.

27:47And and that's one of the things that a lot of neuroscience neuroscientists talk about is that just act of always trying to learn a new thing is one of the best things that you can do that's tied towards, you know, not that it's a guarantee, but it's definitely positively correlated with good outcomes long-term in terms of preventing dementia or other sorts of brain type of conditions. So maybe that's a good sign regardless of whether it's AI or not. That's right. There's a mental health benefit to doing it and there's a career benefit. So just love learning and pick lots of different stuff to try out and some of it's little things like puzzles and some of it is learning a whole new thing that you've never touched before.

28:39Well, Chris, we talked a little bit, I guess, more generally about the impact of AI on the workforce and maybe professional development education. There's an interesting side of this too, which is the actual workforce that is developing the AI things. So, you know, AI, and I think, you know, we've kind of started to adopt this term, AI engineer, you know, I think in a lot of, a lot of things to Leighton Space and our friends over there, SWIX and others from the AI engineer summit and those types of things that have put this term out there. But whether it's AI engineer or data scientist or machine learning ops, or whatever it is, this sort of workforce that's actually supporting the build out of the AI, both infrastructure and application layer that is driving a lot of these transformative tools.

29:45I think we would all recognize, well, maybe our listeners would recognize, but certainly, and I hear this, I know this directly because I talk to our customers who many of which are trying to hire in this sort of talent into their companies. It's very difficult right now. There's a lot of positions available. It almost reminds me a lot of back in the day when people were trying to find the unicorn data scientists that sort of didn't exist, maybe back kind of 2011 to 2015 type of time period. Now it's like it's expanded because the impact of this technology is just so much more, but everybody's looking for AI engineers and talent that is related to kind of this wave of generative AI technologies and having trouble finding those.