Episode Transcript
[00:00:00] Okay, everybody, I'm going to spend about 25 minutes on the state of the business in HR and the workforce and we're doing a big webinar when I get back from the Middle east the week after next. Please join me in that webinar and you'll see more on this. But let me give you a preview here. And then early next year, we'll be producing our predictions report which will show you what's really going to happen in 2026. So the number one topic right now is the massive adoption of AI. Generative AI has gone mainstream. The Microsoft Copilot ChatGPT is now being used by 80 to 90% of managers. Look at some new research that came out from Wharton. Executives do believe they're getting a return out of this. Interestingly enough, the more senior people feel like they're getting a higher return than the junior people. And that's because the further you are from reality, the more optimistic you can be. 800 million people use ChatGPT every. Every week, something like 50 to 60 million are using the Copilot. The Gemini product is picking up speed, the Anthropic, and there will be others. Deepseek in China.
[00:01:10] And what are they doing with it? They're reading their emails, they're summarizing their meetings, they're creating documents or analyzing data. They're looking things up on the Internet. On the latter topic, as I talked about last week, there's still a lot of mistakes and the systems are proving to be imperfect. But that doesn't seem to matter because everybody's going to use them anyway. So we're in a world of experimentation, excitement and high expectations. And we're spending a lot of money on this stuff, which I'll talk about in a couple of minutes. I mean, I think about this constantly. All of the things we could reinvent with AI content generation, recruiting, learning, coaching, super tutors, sales, marketing. Pretty spectacular. In fact, the Galileo Learn is going to have a Super Tutor before the end of the year that's going to be launched. And you're not even going to need to do development planning anymore because the Super Tutor will keep track of who you are and develop a development plan for you based on your interest in your job. They'll get smarter over time as we add more content. So these new AI systems are not just productivity tools, but they replace a lot of old stuff, difficult to use applications, things we did by hand. And we're in the very beginnings of this. This is going to be a decade or more going up the Learning curve. And so I'll link you to the Wharton study and you can see how optimistic people are. Plus, budgets are going up. So there's enough successes now that companies are willing to spend a lot more money on AI, which is good for us because we have Galileo to support you guys. Number three, the AI infrastructure vendors are growing massively. They are taking over the stock market, they are taking over the capital markets. The money that is being spent on data centers, construction, power, power plants, chips is 2 to 3% of GDP in capital this year. It's more than a trillion dollars. And people are skeptical as to whether they're going to get a return on this. But obviously the vendors can't stop now. The largest consumer of electricity in Indiana is now a data center. It's larger than any other manufacturing plant. You've seen the big Meta, a data center that's being built in Kentucky that is bigger than Manhattan Island. We're going to be living in a world with lots of power plants, lots of data centers. Hopefully you won't have to live right next to one.
[00:03:20] They're going to be micronuclear power plants. In fact, I'm reminded of my career when I graduated from college in 1978. We were living through the oil embargo. And the reason I studied mechanical engineering and thermodynamics and energy was because of the energy crisis. We're back to that again, which is great, it's fun, it's exciting. And in fact, the statistics show that 20, more than 20% of the expected electrical demand over the next few years is going to be coming from these data centers. And then we have electric vehicles and all the other electrification things on. So that's a huge topic and it affects many of you in the energy industry, construction industry, semiconductor industry. We're starting to do work with several semiconductor companies on staffing and challenging problems in hiring and training. And you know, there's just a lot of shift in the economy towards the infrastructure and tools and technologies needed to support these massive AI adoption horizons rates. Number four, the evolution of companies from structured jobs to unstructured jobs. This is going to continue. It is something I've been writing about for decades. It's the post industrial age story we talked about two years ago. But when I first started to get to know HR as an analyst in the early 2000s and I sort of looked at how we had set up jobs and job titles and levels and structures and pay and all that, it did occur to me that this is relatively legacy stuff. Well, you know Go back and read the Frederick Taylor industrial model of work. And if you really read it, and it's not that long, it's worth reading it. I think most people should read it. It was designed for a factory where the average worker had very little skills or knowledge or education or brain power. He actually designed his work segmentation, his industrial engineering, to accommodate a worker that was as dumb as a brick. I forget how he put it, but it was a very insulting way. He described the difference between management and labor. And the reason there were job titles, job descriptions, job levels, which later became competency models, was so that the workers didn't have to think they did as they were told. And his model was about segmenting work into tasks so that we could scale up with highly under educated workers. And you know, for me as a young man, when I worked at McDonald's in high school, it was like that. I. They showed you how to run the french fry machine. You stood there and you made french fries all day. And I had shifts where I basically made french fries for four, five, six hours. And you got used to it. It wasn't very exciting, but it was fun. You got satisfaction out of the repetitive process, the people. And psychologically, it's comforting to have a structured job because you don't have to think and you don't have to worry about whether something's going to work or not because you just do your job and you get your pay. However, if you're a nurse, it's a little more complex. If you're a truck driver, there's decisions to make. If you're a delivery person, there's uncertainties.
[00:06:10] So these routine jobs really aren't routine and they're all subtle. And the more routine jobs get automated, the fewer of them we need. And more and more of us are in value creating situations. What we would like to have in a highly productive company is everybody's a value creator and everybody does job crafting. I mean, even accountants, I'm sure, spend a very significant amount of their time on routine stuff. But, you know, they don't want to do that. They want to help you run your business better or reduce expenses or improve your tax situation. So this super worker effect is going to touch all of us, not only because the AI does routine work for you, but because you will have access to information that will break down the hierarchy. Now, you know, the average productivity of a business has not gone up much in the last 40 or 50 years. And a lot of that is because of the hierarchical nature of our companies.
[00:07:08] The Bureaucracy, revenue per employee goes up, but actual labor productivity hasn't gone up much. And we're also going through this weird situation in the US at least, where we have very little antitrust regulation anymore. So everybody's working for bigger companies and the bigger companies are dominating the market. And when you're a big company, you don't have to be efficient because you just own your space and you just kind of stomp out your competition. But anyway, the AI is going to change that, because AI gives you information.
[00:07:39] In a hierarchy, managers hoard information. You, as a frontline worker, don't know things about the company that the people above you know. And that's done for power reasons. And some of it's done because it's hard to share the information.
[00:07:51] So the person in a particular job has limited information and their world is a little bit smaller than the person above them and the person above them and the person above them. So systemically, they don't think about their job very broadly because they didn't really have to or really couldn't. But if you're getting this information, you could do a lot of other things. Imagine you're a barista in a coffee shop. Well, you don't know unless you talk to your manager about the supply chain issues, quality issues, store profitability issues, customer patterns that your manager knows. You just do your work. But if you're bright or you went to business school or you're just interested in business, you would sit down and you might find this stuff out from your boss and you might say, wow, you know, there's some things I could be doing to help with these situations in my role. And you would have a larger context. And that's what the super worker effect is all about. We're all going to have the time and opportunity and information to have a larger context about our jobs. In some sense, we're all going to be entrepreneurs because we're also going to be able to use AI to build things. We're going to have better judgment. We're going to have to build better business skills because we're going to be involved in bigger decisions. If you didn't go to business school, if you don't know accounting, if you don't know what a P and L is, you've never managed a budget. Now you're going to be able to think about that. And I think we, a lot of people call it complex problem solving. It's more than that. It's business understanding. And AI is going to give us the information to do that. That is my sense of this empowerment process. We're going to flatten organizations, we're going to have faster access to information at the front line. And a lot of the creative ideas that are going to come in the AI transformations that are happening are going to come from the front line.
[00:09:33] Now another part of this transformation of the structure of companies is the tool set. I was with the CTO of Workday last week and he and I were getting to know each other and one of the things we were talking about was this technology we're now getting our hands on is technology to build stuff for you as individuals, not vendors. I think in a sense the spreadsheet is such a good analogy. AI is going to be your spreadsheet. You're going to build things with it. I remember when I was a young engineer, first went to work for IBM and I first got my hands on an IBM PC and we had this thing called Multiplan, which was the predecessor to Excel. I spent hours with it. I took the computer, I took one of the lap the luggables home and I just played with it. And my friend of mine from college and I just built spreadsheets and learned how to use it. And I thought, wow, I can, you know, we can build anything with this thing. It was almost like a video game. And that's what AI is going to be like. So we're going to have a lot of creativity, empowerment, organizational flattening, entrepreneurial instincts are going to be supported by this, either building videos or audios or documents or process. I talked about the group we ran into in Japan that's doing inventory by taking photos and they built that at the front line. They didn't go to it. And so part of this, this transformation of jobs is the transformation of work, the transformation of the empowerment of individuals and then the change in the role of managers. And let me talk a little bit about that because the super manager work came out last week. I think in 2026. You need to look at your management model and ask yourself, what do you want managers to do? Where do you want them to spend their time? We have a two by two that I'm going to talk about in the webinar when I come back from the Middle East. And you know, there's two things managers do. They execute and they innovate. If all your managers do is execute, they're not innovating. We're going to have to do some of both. You're going to have to give people the freedom to experiment. You're going to have to help people learn new tools. You're going to have to get your hands dirty with this stuff. Manager models are going to change. I talked with HSBC about this last week. We talked to SAP about it. Other companies, we're going to be facilitating the AI transformations at the manager level. Not from the top, not from the chief AI officer or anybody like that. And you look at any company that is a fallen giant. Nike, Boeing, Intel, Cisco, whoever you want to study. The reason they have lost their mojo, so to speak, is because they got involved in financial re engineering or trying to boost their stock price. They went through mergers instead of internal development and they stopped creating new things inside the company. The bureaucracy slowed them down. Decisions were not decentralized enough, the organization became unproductive and people were unable to speak up. And you know, that's always going to be a management challenge in large companies. But this AI stuff is going to break these models more and more and more.
[00:12:27] You know, sometimes they just want to show up for work and do their jobs and come home and that's that. And at some point in your life, you have periods of time where you don't want to build a bunch of new things. You just want to do your job because you've got issues at home, kids, whatever it may be. But most of us are very creative. We would like to add more value, we'd like to do job crafting, we'd like to build something. And AI is the opportunity to do that. I think you just look at YouTube, you just look at TikTok, you just look at any creator platform and you can see how, look at Substack. I mean the creator instincts are out there. Everybody wants to build something and now white collar workers can do this at any point in your career and your job. And that's going to be a big differentiator of companies too. And there's a lot of cultural issues about this. If you read about the dynamic organization, you're going to have to build people's skills in AI. And you know, the Wharton study that just came out showed that the eight or nine hundred people who took that survey basically said that this is about skills development, not skills education.
[00:13:28] You learn about AI by using it, not by taking courses on it. And even, you know, it's interesting that that report also shows that 80 to 90% of, at least in HR and other domains, people are saying we, we should spend more money on AI. So they're already seeing a return on this and that affects you as an individual too. And I'll talk in a couple of minutes. Okay, Next topic is sort of the economy.
[00:13:51] Now, you know, I don't like to talk about politics much on these podcasts, but we're living through a very weird period of time in the US at least, and I think most of you sense this where the economy actually is stuttering. We aren't creating a lot of new jobs. We have the barrier, the trade barriers being erected by Trump. We've had a long business cycle since the pandemic. There really haven't been any corrections in the stock market. The top seven or eight to 10 stocks dominate 50% of the S&P 500 valuation.
[00:14:25] It's very bubble like. So those of you with CFOs that you talk to are probably a little concerned. And then there's this issue of autocracy and politics and the argumentation between the Democrats and the Republicans, and it's resulting in a lot of stress on the shoulders of workers and employees. You know, if you work in the federal government, you're not happy right now because you're not getting paid. And even these initiatives that came out of the Trump administration to eliminate DEI and do away with all the DEI jobs are destructive because they take away the language we have for talking about inclusion and fairness and equity. We can't talk about that stuff anymore. Nobody wants to hear it. But those are real issues in companies. When people don't feel included, when people don't feel psychologically safe, when women are not promoted, when black people are eliminated from jobs, when there's anti Semitism, fear of multiple gender issues, you know, people check out, they don't work very hard, they leave. They may not tell you, but they're not giving you their best. One of the companies we spend a lot of time with is l'. Oreal. L' Oreal is just amazing company. And because they're in the beauty business, their customer needs are very diverse. People with different skin colors, ages, types of hair, all sorts of other demographic and physical differences all want to be beautiful. So they are inclusive by nature, but they're nervous about talking about it because of the political environment we're in. So economics and politics are going to be a big topic in 2026. I think we're going to have a correction of some kind. It could be big. We're in a bit of a stock market bubble. But I'm not going to tell you what's going to happen because I'm not sure either. But this is going to be a factor in the year ahead. In the meantime, There seems to be a lot of budgets on AI. And because of these uncertainties in the economy, many, many people think AI is a cost cutting tool. It's not. It's really a transformation and reinvention tool to get closer to your customers and build better scale and better customer experiences and better products. But you're going to be dealing with this. I'll talk about that in a couple of minutes. So that's a big topic for 2026, and I'll talk more about it when we get on the webinar next week. Okay, next topic is hr. So I am actually excited about what's going on in HR because we're really going to be reinventing this whole domain we live in. Let's face it, we are an expense center. We are a cost of the company, payroll, administration, hiring and so forth. Or you're a value creator. You have a choice of thinking about yourself as a cost or a value creator. Now, I'm sure most of you would like to be a value creator. You'd like to facilitate skills development, growth, innovation, flexibility, employee engagement, job design for positive output, and so forth. And that's the reason people get into hr. But a lot of people who aren't in HR don't see it that way. I still read all the time articles about people, you know who don't understand the complexity of HR.
[00:17:34] You know, there are 94 capabilities in our capability model. What we do is not simple. But most people who aren't in HR don't appreciate it or understand it. So we're going to be in a situation where you're going to be asked to use AI to cut costs and reduce headcount. And honestly, I wouldn't be surprised if HR departments are 1/3 smaller or maybe half as big in terms of headcount in two or three years because of the automation that we can do. But that doesn't mean you're going away. That doesn't mean you're losing your job. Because if you're in the value creation business, that should free you up to do other things or work in the business outside of hr. You know, we did a study last year, this year actually, on talent acquisition and 75% of TA leaders believe that their recruiting function is a fulfillment center, not a strategy or consultative function.
[00:18:24] So that's true in L and D, that's true in business partner roles. That's true in service centers. If people aren't served well, they don't have time for advice because they just want to get their questions answered. So now we're going to be asked, and every single Chro has been asking for this. How do I transform HR around AI? And we're working on a blueprint for this. It'll be out early next year. Some of it is eliminating administration and paperwork, some of it's process management.
[00:18:51] But it's also reinventing talent acquisition, reinventing learning and development, reinventing the customer, the employee experience, rather, reinventing the digital business partner so that maybe we don't need business partners to do administrative stuff. And we now know how to do this. We've watched IBM do it, we've watched other companies do it. And we're going to teach you how to do it, and we'll be there to help you do this. Because if we don't move HR into a value creation process, you're just going to get cut. If you imagine an HR function spending maybe 2 to 3% of payroll, it's more like 1 1/2%. But if you add L and D and other costs, it's higher. And you take that money and you cut half of the administration out. Well, that doesn't mean you reduce the expense. It means you spend the rest of the money that you just saved on consulting, on education, on training, on leadership development, on job design, on productivity. That's where we're going. So a lot of you in Europe kept asking me questions about is AI going to eliminate our jobs? Are we going to need recruiters? Maybe not, but that's okay. You'll be able to do other things. There's many, many things to do other than what we're doing today. And you got to manage the AI systems, too. There's quite a bit of interesting work there. But also consulting with the business and adding value in other ways. So that's going to be a big topic next year. I'm going to talk about that in the webinar also. And I think the way I think about our blueprint that we're working on is it's not a blueprint for cost reduction. It's a blueprint for both growth and transformation and innovation. That's where we need to be spending our time. But you don't have time to do that if you're just trying to get data and process payroll and deal with employee relations issues and teach managers how to do basic stuff. So that's where we're going. We're going into value creation. And get your seatbelt on, because that's going to be the biggest initiative for us to show you how to do this. The final Thing I want to touch on before I wrap up, because I've been talking for a little while, is where we go with the skills of HR professionals. The thing that will trip you up as an HR professional is not knowing what you don't know. And for me, you know, having done this for so long and working as more of an analyst than a practitioner, I see things every day.
[00:21:10] Every single day, I discover something and I want to scream from the mountaintop and say, my gosh, you guys, you got to know about this.
[00:21:18] And that is what this profession is like. We are in a profession that combines psychology, business, technology, management, leadership structure, operations, education, a vast number of complex domains to help our businesses improve.
[00:21:37] And so, you know, the other final thing I'll just touch on in this webcast, this podcast, is you have to educate yourself. It amazes me how much press there is about IT skills and technology skills. And nobody writes about the skills of HR because for some reason, everybody thinks they're an expert on management and hr. Well, you know, that's not true. The work that we do is very subtle. It's not as easy as it looks. It's easy for an executive to wing it. But your job is to develop expertise and credibility so that your leaders do ask you for help. I was with the chro of a large bank last week who's new to hr. She's new to hr. She came in and she's really amazing because she's asking questions about everything. Why do we do it this way and why do we do this? Tell me why we're doing this. And what she's doing is, through that process, encouraging the people around her in HR and other areas to think about their work and explain it and redesign it. Because what we do is so amorphous and so human centered. There is no right and wrong to anything in hr. I mean, I'm an engineer, and I'm actually more almost like a scientist than an engineer. And I think it's okay to question everything in the world of AI. And so I'll leave you with that. That Galileo learn and Galileo are your lifeline to learning and staying up to date. Every day we put new information in there that will help you stay up to date every single day. We're publishing and producing information every day, new data. And I know you're going to go to conferences and you're going to come to our conference next June and you're going to learn things from the Internet and read books and magazines and all that stuff. You have to stay up to date on this. We are in the steepest learning curve of business that I remember in a long time. You know, when the AI stuff first hit and I had to learn about large language models and neural networks and watch a bunch of YouTubes, I was a little intimidated myself. But I feel like we've come down the learning curve over here because we're doing a lot of this. You have to do the same thing. So that's going to be one of the big initiatives in 2026, and you're going to have LLMs, and you're going to have AI in your glasses and in your clothes and on your computers and built into your phones. So your big initiative for 2026 is to upskill yourself. I think I will stop there and we'll talk more about this on the webinar next week. Those of you that have invited, come to the webinar. I'm going to go through this in a little more detail, show you some graphical images, and then stay tuned for our predictions. It'll come out late in the year and lots and lots of specifics for you to think about in 2026. Talk to you guys soon. Bye for now.
