Episode Transcript
Speaker 1 00:00:10 Hello everyone. Today I wanna talk to you about the emerging massive AI market and what it's gonna mean to you as an HR professional. And much of this is going to be detailed as I prepare our presentations for the HR technology conference in Vegas and the Unleashed Conference in Paris. Now, there's interesting phenomenon that's going on in the world of ai. Not only are there billions of dollars of investment money going in, but if you look at the growth of Nvidia and some of the technology providers and the announcements that are coming out from Google this week, everybody is investing in the technology platform because AI isn't just mathematics, it is a technology platform. And so what we're gonna experience in HR is a proliferation of what we call generative AI applications. And what I talked about in the article I recently wrote in last week's podcast to some degree is that generative AI isn't a thing, it is a technology and you don't implement generative ai.
Speaker 1 00:01:21 You implement applications of generative AI in different business use cases. The onboarding, the recruiting, the candidate experience, the HR person, the HR business partner experience, the chat bot that helps the employee find their pay stubs, the scheduling application, the training application, the compliance application, et cetera. Generative AI is used to deliver those applications. So it isn't a solution in and of itself. And none of those applications really exist quite yet because the vendors haven't built them. And the reason they haven't built them is the technology stack is very, very immature. And I know this because we're going through this ourselves, that what's actually happening is a massive new technology stack is being developed and the vendors are positioning for ownership of that stack. Obviously Google is going to be announcing a whole bunch of large language models and development tools in part of Google Cloud.
Speaker 1 00:02:24 Amazon is investing heavily in a series of large language models and tools in a w s. Microsoft has partnered with open AI and offers all sorts of tools for developing applications. Oracle has decided to partner with this company called Cohere and is going to be offering the same sort of things and there will be others. And there's lots of mid-sized technology providers, including Anthropic and many others that are building up stacks of tools for application developers to build the things that you guys will eventually wanna buy. And because that part of the market is so immature, the end user applications are not here yet because the application developers don't know which platform to build on top of, and I again know this because we are going through ourselves and the analogy that I think is somewhat similar to try to make sense of it is in the early 1980s, 1990s when the relational database industry was new, there were hundreds of database companies building multidimensional databases, SQL databases for transactional processing, SQL databases for massive parallel processing for queries, SQL databases that were vertical SQL databases that were horizontal, uh, some that had object oriented front ends.
Speaker 1 00:03:52 And they were in applications, they were purchased by developers or by IT departments to build applications on top of. And it took, I don't know, 7, 8, 10 years before that market shook out and it became clear which application technologies people were gonna use. Microsoft eventually went in and and sorted Oracle and you know, won a very large percentage of this, but I B M was in IT and form X, lots of others and, and we built applications on top of those during that period of time. And some of the application providers picked the wrong platforms and they got in trouble. And there were a bunch of E R P vendors that standardized on relational database technologies that didn't make it. And those vendors had a very hard time surviving over the long run. So the interesting thing about this stack is that while you wanna buy an end solution that works, obviously that works well.
Speaker 1 00:04:49 What's going on under the covers actually makes a big difference because the ability for that vendor to support your needs over time will be limited on the fundamental technology services they get from their platform provider. And this is why Workday's announcement about their Gen AI strategy was so vague, they really didn't announce anything. They just kind of talked generally about their strategy. And I'm sure more will come out at Workday Rising. Coming up from the standpoint of what you do in hr, I think the most important thing to do is to experiment with these technologies and get to know them and talk to the vendors, go to the conferences, see what they have to try to figure out if any of them are mature enough and far enough down the track for you. So where does that leave you or us? As I will explain when I do the conference, there are some big, big use cases here that are going to drive this market.
Speaker 1 00:05:52 The first is the fundamental issue that in most companies we can't hire people fast enough or with enough technical or professional skills to grow the company as fast as we'd like to grow. So we need tools that will not only help us find candidates and hire people, but actually on the other side to help us to make people more productive. Because in the coming economy, which we call the post-industrial economy productivity and the ability for each person to do more is going to become fundamental to your success. We're gonna have a war for productivity and it's not gonna be a war for who works the NAR most number of hours and who has the best benefits and who has the best onboarding program. It's gonna be a war for who can deliver the best products and services to our customers with maybe not the least number of people, but the most optimal use of the people that you have.
Speaker 1 00:06:58 Now, we call that working at the top of your license or working at the top of your license means in healthcare is that if you're a nurse, you should be doing nursing. You shouldn't be scheduling people, you shouldn't be cleaning the floors, you shouldn't be working behind the desk trying to type data into the epic system. You should be doing nursing. And so what they do in nursing, in the healthcare industry, and there's many, many articles written about this top of license idea, is they are re-engineering work so that when you go into the hospital, you get great service from all sorts of different people, but when you need the doctor, he or she is there, but the doctor's not doing a lot of that non-essential work. He or she is letting somebody else do it. Unfortunately, in business, we didn't design our companies that way.
Speaker 1 00:07:49 We do have specialized jobs and we've tried to decompose work into specialized jobs, but in many cases we've built more of an industrial model where we have lots and lots of repetitive work being delegated to many, many people. But the really high value work is hard to find. Like if you think about the job of say a salesperson, the best salesperson on the planet that I've ever met, don't enter things into Salesforce all day. They're great with customers, they're great with understanding problems, they're great with communicating the value of your product and your service. They're great with negotiations, they're great with objection handling, they're great with executive relationship building. They don't sit around and put data into Salesforce and run reports and somebody else should do that. Uh, do you have a group that does that? Most people don't. Most people expect the salesperson to do all of that stuff.
Speaker 1 00:08:43 So there's, there's lots and lots and lots of opportunity for you to use this idea of working at the top of your license to make your company more productive. And by the way, that's what AI is really good at because what AI does is it democratizes information so that the person that needs the gritty details can get what they need and the person that wants the high level version of it can get what they need. And you don't have to sit down there and manually design all the content that everybody needs to do their job and try to figure out to train everybody to do it in an optimal manner, which by the way, changes every year anyway because the company keeps changing. So what we need these AI platforms to do is to deliver on this real productivity. Now. Now let me go back to the word for a minute.
Speaker 1 00:09:30 Again, productivity doesn't mean doing more stuff per hour. It means generating more revenue, creating more customer value per dollar of input. That may mean doing less work, but doing smarter work. It may mean spending more time with big customers and less time with small customers. It may mean adding value to the customers that are the most profitable and not adding value and not wasting time on the customers that are unprofitable. It may be manifested in much more strategic ways than this idea of the, of this sort of mouse in the wheel going faster and faster and faster. That's why we have to move past the industrial age to the post-industrial way of thinking. What is it about your company that you can spend time and money on that's gonna have a 10 x return? And each person, by the way, should be thinking this way as opposed to let's do more and more of the same thing because that's what everybody asks.
Speaker 1 00:10:31 And those are design issues that we have to do in org design. Those are design issues we have to do as an HR business partner. Those are design issues we have to do as an L and D consultant or as an OD consultant working with the business. And we can't do this alone. These are kinds of things that have to be done in concert with the business, but that's where AI is gonna help. And we really need to help the vendor market at this point clarify these problems so they don't give us stupid solutions. I've seen quite a few generative AI products over the last 60 days and most of them are kind of silly. I know they have the best of intentions to write emails to candidates or take a piece of content and format and then create a quiz and so forth. They're great.
Speaker 1 00:11:19 I mean they, they look great at first glance, but then I think to myself is how are we gonna industrialize these? How are we going to use them? How are we gonna scale them? How are we gonna configure them for each company's needs? How are they gonna be personalized for each user? The vendors haven't figured that out. So fast forward two years, we will have all this stuff, but we don't have it today. So that's where the AI market is. The interesting thing about it is I've probably haven't seen so much money go into one category for a long time, maybe since the beginning of the cloud market and the level of noise and the level interest from the vendor markets is really spectacular and also very interesting. And the level of confusion and lack of clarity from buyers is also sort of amazing. And so we have this gap between the knowledge in the heads of the core technology providers, the knowledge in the heads of the application providers are trying to build solutions, and the knowledge in your heads that none of us are all reading from the same page because it's very unclear how these pieces are gonna fit together.
Speaker 1 00:12:29 Um, I'm not saying I'm the world's expert at this either I'm, I'm probably a little more knowledgeable than most because I spend so much time on it and we're doing our own projects, so we're getting our hands wet directly. But it's clear to me that this is huge future in unavoidable, inevitable that these new tools are going to be replacing and disrupting a lot of the technologies we have, not overnight, but certainly over a period of few years. And that if you're not paying attention at some point, somebody and and a competitor to you will start out performing you and you won't really know why that is. The other issue that plays here is really three things. There's the org design that I've talked about before, there's the leadership role and then there's you in hr. Lemme talk about the other two. We talked about the org stuff last week and also this week leadership.
Speaker 1 00:13:23 So Janet Mertens who runs research for us is just finishing our big research on leadership. We've been working on this for more than a year. And what we've been discovering, and you're gonna hear about this at the conference briefly, is that in order to run a company that evolves and adapts to this post-industrial age uses AI constantly looks at the higher level views of productivity. You need leaders that are not only focused on execution, hitting the bottom nine, making our numbers, but leaders that are keenly aware of the human issues in the company. We call it human-centered leadership. And the analogy that used with Janet when we talked this through, and we haven't published all this yet, but it's coming, is that in the industrial age of leadership, and you go back to Jack Walsh or GE or Bill Gates or Steve Jobs, whoever your favorite leader was, the company had a pyramid of management priorities.
Speaker 1 00:14:19 Top of the pyramid was execution. Are we getting things done that we planned on getting done? Who's accountable for what? Are we hitting our numbers? Are these projects on track? If they're not, why are they not on track? And who's responsible for that stuff? And do we have the right people in the right roles to execute? Number two, are we innovating and growing? Are we moving into new directions? Are we transforming? Are the projects related to the next generation of products and services happening at the right level of speed and the right level of quality? And if not, why not? And what's holding us back? And level three, there's the people issues. Do we have too many people? Do we have too few people? Are we paying people too much? Are we paying people too little? Is our turnover too high? Is our turnover too low?
Speaker 1 00:15:10 Is our culture too execution oriented? Is it too innovation oriented? Is our customer service suffering because our people are not trained? Blah, blah blah, blah, blah. And and that was really sort of the third category of issues. And when those people issues became big, they rose up and they were discussed in the context of the first two. But the generally the leadership agenda, if you went to business school, if you read books on leadership, was execution first, growth and innovation second people third. We believe that has completely flipped. We believe in the new economy, the post-industrial economy, the number one leadership issue is people. And when the people agenda is on track, we grow, we innovate and we execute. We cannot execute without the people agenda because we are in the people business, we're in the IP business, we're in the service business, we're in the innovation business.
Speaker 1 00:16:05 And the C H R O is a 100% partner on the business strategy and must be involved in every major decision. If you think about what Helen Russell's been doing at Rivian, for example, Rivian ISS an amazing company by the way. You don't know much about them. When they decided to build the manufacturing plant in normal Illinois in a whole new way, it's a very different kind of plant because it's really an e e egalitarian workforce there. They don't have management and labor like the older car companies. She said, you know, she as the C H R had to go to Illinois and she had to look at the place and they had to think about all of the people issues of management and pay and work environment and physical location and hourly labor and really rethink all of that in order to build that plant.
Speaker 1 00:16:53 Now Rivian has yet to become the darling of Wall Street, but it's a pretty good company and is growing pretty fast. That company would not be what they are if they didn't have that people strategy. And I think Rivian will turn out to be a big superstar company in the future because of that. Many, many of the other examples where you've even Nvidia by the way, is this way Nvidia, everybody thinks it's an instant success. It's not. NVIDIA's been around for a long time and it's a people-centric company. You can argue about Apple being a tough place to work or not, but Apple understands how to motivate and incent people. That's the level of leadership we're gonna have in the future and not just understanding how AI works and what our opportunities in ai. The third area of course in this transformation to AI is us in hr.
Speaker 1 00:17:42 And we are gonna be introducing the A, the systemic HR research to you in October initially at the LinkedIn Tele Connect conference and then a few other places. And what we basically found is that there's a journey going on and some of you are getting there very, very slowly. Some of there are getting there very fast towards systemic hr. It's not an end, it's a direction, it's a journey. It's a series of steps that you have to take to running your part of the company and optimizing your part of the company to take advantage of these integrated tools like AI to bring HR teams together into more systemic groups to become consultative, to operate as product leaders, not just program managers. So we don't just launch HR programs and then throw them over the trans to the service center, but we stick with them and we iterate on them and we buy and build technologies around them so that our people practices are not only innovative and creative but also scalable.
Speaker 1 00:18:43 We cross train each other, we rotate people in and out of hr. We have great talent intelligence, we invest in data and we realize that our job in HR is not to keep people happy and to improve employee experience, but to optimize the company's investment and labor. And that in many cases, the R O I of what we do in HR is enormous because we are in a sense the specialists responsible for the craftsman work of making the human capital part of the company operate better and better at higher and higher levels of productivity. That's systemic HR and how to do, that's gonna be very clear to you when we show you what we've learned, we've learned a lot about this. So AI may feel like the sort of topic of the day at the moment, but it's all related. All of these things are related and the tech industry does as it always does.
Speaker 1 00:19:39 There's people trying to make a lot of money building a tool or a product or a platform that everybody wants to buy so they can sell it to somebody else or go public. But that market is so young right now. We can't predict who the big players are gonna be. So we as the practitioners responsible for making our companies more successful have to get to know this market in its formative stages. What we are doing, and we will do is we will continue to show you everything that we've learned. We get a chance to talk to many more vendors than you do. We get a chance to see perspectives you don't see. We get a chance to see data that you oftentimes don't see and we'll keep you up to speed. I'm really excited about these conferences. Not that I like going to conferences particularly, but because I think we're gonna see a state of the market come together in the fall. So that's it for today. And uh, check out our new courses in the J B a. The org design courses is going very, very well. There's still lots of room for more people to join and we look forward to talking to you in the next couple of months and seeing you on the road. Bye.
