AI and the Workplace: Here’s the latest from Josh Bersin, the guy who knows it best

Josh Bersin:

“I’m going to spend about 55 minutes telling you about how AI is going to revolutionize HR and HR technology, and you will probably be amazed at how much is going on. I’m going to talk a little bit about the market and how it’s changing. And then, at the end, I’m going to do something I actually never do. I’m going to highlight 10 or 15 vendors that I think are what I call trailblazers, and the reason I’m doing that is to give you examples of what I think AI is capable of doing in the context of what these particularly innovative companies are doing. And then, after this is over, if you go to the app and you refresh it, you will see a page to download a report we’re just releasing today and tomorrow on the economy and AI that you can read yourself.

IF YOU ALL REMEMBER this chart from the last couple of years, this is a very big market. It’s very complex. Apparently, there’s 500 vendors at this conference. Every month there’s another 50 vendors being created. It’s very difficult for you guys… By the way, here’s the topics I’m going to go through. One of the things that we deal with is what do we buy, why are we buying it, and what are we trying to do? And what we always do with clients, and certainly I encourage you to do this before you run around and buy something, make sure you know what problem you’re trying to solve. I mean, what is the business problem, not what is the technical problem? So, let me start with that, and I want to give you a sense of why AI is going to be really important to your company whether you like it or not or you’re afraid of it or not.

We’ve now been through, since 2008, almost a 15-year economic cycle. I don’t remember in my career ever going through a 15-year period without a real recession. Obviously, we had the pandemic, but you can see the pandemic didn’t have a huge impact on company profits over the long term, and during that same period of time, the unemployment rate has been going down, down, and down. And that is a very significant piece of data because what it basically shows is that the economy has completely changed.

THE SYMPTOM OF THAT is that CEOs are all waking up in the morning thinking about people. They’re thinking about change. They’re thinking about transformation. They’re thinking about what industry they’re in. They’re thinking about what technology platforms they have. Even iconic, they’re just talking back here about Disney with some of the most highly esteemed brands in the country, and Starbucks, are worried about reinventing themselves because of the change of the political climate or the economic climate or the technology climate, and 61% of CEOs now say that we need to spend more time on transformation and less time on execution. So, we’re in an era of accelerating change, accelerating technology, and stress, and I can’t underestimate this problem of workplace stress.

“HR is now a C-level issue”

I’m in my late 60s, so I’ve been working since the 70s, and I’ve been through stressful periods of my life. I’ve never seen data that month after month after month shows how much agony employees are going through and it’s now manifesting itself in employees saying, “I’m not going to take it anymore. I’m going to go on strike.” And in the last maybe three months, I think there have been five or six major labor relations upheavals in the United States, including the President of the United States standing on a picket line, and that is forcing executives to think about employees first, not necessarily customers, stakeholders, shareholders, and so forth.

So, what you guys do in HR is now a C-level issue. I came to this conference 25 years ago or 20 some odd years ago when I first came, and we talked about talent management and pre-hire to retire and onboarding and all that stuff, and it was great. It was all HR stuff. This is all very C-level business stuff that we’re dealing with and it’s going to get worse, and the reason it’s going to get worse, and you can read about this in the white paper, is we’re not having many children. You’ve probably seen this research. Young people have put off getting married. They’ve put off having children, having fewer children, and the overall size of the labor market in most developed economies is going to flatten and shrink.

THIS HAS ALREADY HAPPENED in Germany. It’s already happened in Japan. It’s starting to happen in the UK. It’s going to happen in the other Northern European countries over the next decade. So we’re all going to have to do more with fewer people and what that means relative to AI, we are entering an economic period where we have to learn how to run a company with fewer people generating higher levels of productivity, having more flexibility in their jobs, having more empowerment, more skills than we had in the Industrial Age. In other words, every employee, including you guys in HR, are going to be super powered workers, and that is why AI is important.

One more piece of information before I get into the tech market — if you look historically at economics measured as GDP per worker, per the number of workers in the country… And they do this research all the time. It’s all over… The World Bank actually does a lot of these studies. You see what happens is during the Agrarian Age it was more or less flat. In the Industrial Age, it started to go up. And then, we invented computers. It went up again. Now, it’s going up again, and we’re reaching a point right now with AI where this accelerated rate of productivity is going to be the only way you’re going to be able to grow your company, and I guarantee you, your CEO is trying to figure out where’s our next growth vector? This is where it is. So, if we can’t adopt and take advantage of this AI and all the work we do, our companies aren’t going to be able to meet their goals.

That’s what’s going on economically, and you can download that white paper and read about it. We call it the Post-Industrial Economy. And I think it’s important to think about it because before you run around and buy a bunch of tools, what we tend to do with clients is we go through workshops discussing which part of your company needs the most help in this area of growth, productivity, skills, and so forth.

Okay. Let’s talk about the tech market. Now. I put together this chart three years ago, and yesterday, one of you guys who works for a big airline came up to me and said that this was the most important thing I had ever taught them because they went back to their organization and said, “Let’s get rid of half the tools we have.” But basically what happens in technology, and you know this and this happens in your house, is you buy something and you never get rid of it, and you end up with a kitchen drawer problem. How did all this stuff get in here? I don’t know. I don’t even know what we use it for, but I’m afraid to throw anything away because somebody might eventually use it. That’s what’s been going on in HR tech because we’ve had a proliferation of tools more and more and more. I think it’s on that chart. If you look at the data from Okta, which is the identity management firm, the number of corporate applications is going up and up and up, the quantity, not the volume, the number of them.

“HR tech is a great investment”

In our area, it’s been great because while the talent tools and the talent intelligence tools and recruiting tools and learning tools and so forth are proliferating, the core HR platforms are going too, and I don’t remember ever in my career as an analyst seeing the core HR business grow at such a rate. I won’t mention all these companies’ names because you know a lot of them, but because of that 15-year growth cycle in the economy, there are a lot of new businesses that need HR, and every time a new business is formed, they need a tech stack of tools, so they go out there and buy it, and those companies have performed very well.

In fact, I like showing this chart. I like to put it together every couple of months, that actually HR tech is a great investment. If you look at the well-run HR technology companies, Workday, ADP, SAP, and so forth, they have outperformed the S&P 500 because of this shift to a greater and greater percentage of the economy driven by human capital parts of companies. So, this is a very healthy space. I would say the investors kind of pull back. For the last year, they’re starting to come right back in again. There’s lots of money coming into the market, and as a result of that, some of the really big players are changing.

The one I want to highlight in particular is Microsoft. Most of you remember maybe two or three years ago, there was no Microsoft at this conference ever. We went up to Microsoft a couple of years ago and talked to them about the corporate learning stuff and they were kind of getting interested in it, and all of a sudden, they jumped into the market with Teams and Viva, and guess what? Viva is now the number one platform for employee experience. We can have an argument with ServiceNow about that later, but 35 million people have licensed Viva in less than two years. You find another product that went from zero to 35 million users in two years, I don’t think you’re going to find one. And today or yesterday, Microsoft announced a feature of Viva called Skills for Viva, so all of that skill stuff that’s out there on the trade show that you’re looking at is going to be embedded into the Microsoft toolset.

WHEN THE MARKET GETS BIG and healthy like this, the big players spend more money, and that of course changes the way it works. Now, I’m a big fan of Microsoft because I’m old enough that I used to use PCs back when they had green screens, and I actually think this stuff is very, very modern now and it’s been upgraded, and of course they have OpenAI and all those kinds of great things, but it’s going to change and that means that some of the smaller vendors are consolidating. As a matter of fact, if you look at the data on consolidation, there have been a lot of acquisitions in the last couple of months. Modern Hire was acquired by HireVue. You saw the ads from them out there. This is a kind of a hairy market. For those of you that are vendors and work in smaller companies, you got to be wary of what’s going on because the big elephants are now stomping around looking for their space in this and they tend to be very inquisitive as things grow.

Now, let me talk a little bit about AI, and I’m going to give you some things that’ll teach you about AI in a minute. Where did this come from? Just very briefly, AI’s been around for 55 to 60 years. I’ve told this story to many of you. When I was at IBM selling computers to the University of California, I used to go to the computer science department in Berkeley and used to try to get them to buy IBM computers. They wanted nothing to do with us. And there was this group in the corner. They didn’t have any shoes. They never took a shower. I don’t think they ever combed their hair. They were the AI guys, and they were working on these weird computers on how to do language and vision and stuff, and they were kind of the black sheep of the computer science department at that time.

Finally, “we got AI to work”

Well, what they were basically doing is building better and better and better mathematics to analyze data and information, interpret words and characters and images, and so forth, and while they were doing that, the computers were getting faster and faster and faster, until all of a sudden last year, with the advent of the GPT and the transformer, which basically is a mathematical sort of model, we got AI to work. So, this is a technology that has been enabled by these highly powered vector-based computers that are now available from companies like NVIDIA.

THE BIG DIFFERENCE BETWEEN AI and the traditional models of computing is actually very simple. In a normal computer pre-AI, you program it. You tell it what to do. You design the screens. You turn it on, and people use it, and while they’re using it, the data builds up and you have the transactional database. AI is virtually the opposite. In an AI system, you start with the data. You don’t necessarily know what all the data is telling you, and you build a model based on some characteristics or prediction or some classification you’re trying to create, and the software looks through the data and interprets it, and that’s what GPT does. That’s what these generative AI tools, that’s what these talent intelligence tools do. So, AI companies are data companies, not a software company. They obviously have to build software, but they have to manage and understand and really make sense of vast amounts of data. So, every vendor that says they’re an AI company may or may not be actually an AI company, and I’ll explain how I mean by that in a minute.

One of the things that AI enables in HR, and to me this is really in a sense the nirvana of AI, is we’re sitting on one of the most important data sets that any company has, all of the data about your people, but it’s really complicated data. We don’t know when somebody was hired, whether their degree matters, their skills, their tenure, their performance, their personality, right? I mean, there’s been scientists and I/O psychologists and assessment companies who’ve been trying to figure out what this people data is all about. Well, if you put all that data into a neural net, which is now called talent intelligence, you could actually make a lot of sense out of it, and that’s one of the biggest applications of AI is these talent intelligence systems, which I’ll talk about in a minute.

Generally speaking though, what’s going on in the market today, this is discussed in the white paper you’re going to get access to, is three things. The first is of course, adding generative AI to an existing product, and you’ll see in a minute, most of the vendors are doing this. They’re adding maybe generation of a job description, generation of a course outline, generation of an assessment, generation of some piece of content that would normally be done by hand in a more intelligent way, based on the data that’s in the system. So, the job description that’s generated in an AI platform should know information about your company and the other jobs, and be able to generate something that’s actually very consistent with the other generative job descriptions that are being taking place in your company.

“A great AI company is a data company”

The second is, of course, taking this big transactional data set in a Workday or an Oracle or an SAP and making it smarter using machine learning, mining it, predicting it, predicting what course you should probably take, predicting what career you might want to have, and that’s what I call first generation. And then, the second generation are the vendors that started from scratch. They built a neural net. They built a massive database of candidates and employees and other people and salary data, and they turn that on for you for some application, typically for recruiting, sometimes for career management, and I’ll talk a little bit about what those companies do.

AS YOU GO OUT AND LOOK at these different vendors, you’re going to see all three of these mixed together all called AI companies, but the big difference is that a great AI company is a data company. They get a lot of data. They know what the data means. They spend a lot of time making sense of the data. They don’t just use the data in your company. They use the data in your company matched against other data, so that the data in your company can be classified and used in a more and more intelligent way. And I think a year from now when we come back to this conference, there’s going to be a lot more big data AI companies than there are today.

Second thing I learned about AI is these chatbots, conversational interfaces. We’re going to talk a lot about that in the next couple of minutes. Obviously, based on the success of Siri and all of the conversational tools on our phones, it would be much easier to talk to or type a question into a computer, than try to navigate the screen and figure out what buttons to push, so let’s just build a chatbot, right? That should be pretty easy. Well, it’s not. It’s actually pretty complicated because these really sophisticated chatbots, the one that’s the most sophisticated in HR is Paradox, which I’ll talk about in a couple of minutes, actually have to do a whole bunch of things.

They have to be able to generate content to answer questions. They have to know where the content is. They have to know what corpus of knowledge to use, and that data has to be accurate and secure, so that if somebody doesn’t ask a question of the chatbot and get access to data I’m not supposed to see, then they need to know what to do with that answer because when I get the answer, I’m going to want to know, well, what do I do with this information next? Maybe I want to log my vacation time or change my desk location or whatever it may be. And then, I need to integrate it with the core system.

“Not a magic answer to every vendor”

Last week, I was actually at Vegas for the SAP conference. They introduced this product called Joule, which is a front-end chatbot that basically has access to all of the transactions and all of the ERP systems within SAP. It’s actually sort of a miraculous tool. I’ll show you a picture of it in a minute. So, these things are really significant and I think you’re going to be building these in your own company. The vendors are going to be doing it for you and you’re going to be building it in your company. We have built one of these for our research. One of these days, I’m going to show it to you guys. We’ve been showing it to clients and it’s remarkable what you can do, but basically there’s an IT project behind it to get all this stuff set up.

The third thing I would say about AI is AI is not a magic answer to every vendor. Just because you have AI doesn’t mean you’re going to suddenly win out over everybody else. AI is a difficult complex enterprise level technology implementation, so just because the company says, “We’re an AI-first company,” I would take it with a grain of salt. Everybody has access to AI technology. Everybody has access to the APIs. Everybody has access to the intelligence. Yes, the AI engineers are hard to hire, but honestly, there’s a lot of them being developed all the time, so I think this is going to become a core part of the computing infrastructure from every vendor. There are many, many applications of this, and I’m going to go through this now for the next couple of minutes.

I have now spent maybe three or four months talking to companies about their applications and their use cases of AI, and last night, I was talking to a client who told me they did a hackathon inside their company, inside HR alone, and they came up with 170 applications of AI in their global HR department among their HR people. So, we’re in the very early days of some really, really interesting things that are going to change the nature of the HR technology market.

NOW, WHERE DOES THIS FIT? Let me just spend a minute on sort of the overall architecture. If you go back maybe a decade or so, most of the HR tools, whether it be talent management systems, learning management, integrated talent management, applicant tracking, and so forth, were 90% or 95% transactional, that first box on the left I showed you. And over time, we get interested in employee experience and we had to deal with well-being and jobs that were more mobile and talent marketplaces. So, we sort of built this layer of software in green here that I call talent intelligence. That was really early days trying to figure out how to do some of these non-transactional things in a more intelligent way. And then, last year or two, it got bigger, so now, if you look at Eightfold, if you look at Phenom, if you look at Gloat, if you look at Beamery, if you look at a lot of these advanced recruiting or mobility tools, they’re basically AI systems. So, that talent intelligence part of the stack got bigger, not replacing core HCM system, but adding a lot of value on top of it.

“The next thing that’s going to happen …”

Well, the next thing that’s going to happen is AI is going to suddenly be everywhere. We’re going to have AI at the employee experience layer. We’re going to have AI at the transaction layer. We’re going to have AI in the talent intelligence layer, and we’re going to have AI in the analytics of data layer. I’m going to show you what that means. So, this is really in some sense, one of the most disruptive tech changes that I’ve seen. Obviously, when mobile came along, mobile affected everything. Obviously, when the cloud came along, the cloud affected everything. But now we’re affecting the actual application use case of everything you do in HR. Every screen, every panel, every interaction you have can be informed and improved and made more intelligent by AI.

It’s affecting all the vendors, and I know a lot of you guys out here that are vendors, the vendors are learning just as fast as everybody else. The funny thing about this space is the core technology providers, OpenAI, Google, Microsoft, Amazon, they’re not even halfway done building the stuff they were using, so we’re in the middle of using and building tools on a platform base that is changing almost every day. So, this is a very dynamic space, and whatever vendor you do business with, I guarantee you they are working on this constantly just to build and to keep up with where the market is going.

ONE MORE QUICK THING on that, and then I’m going to the different parts of the market. If you want to learn more about this and you just want to do a little bit of education, this is a free course we just put together. You can take it on your phone. It takes about five minutes a day, and I guarantee you in about a week, you will learn a lot of stuff about AI. We’ll just make this available to you and you can take advantage of it and sort of keep up on this stuff.

All right. Let’s talk about core HR. Interestingly enough, two weeks ago, Workday Rising announced Workday AI. Last week, SAP announced Business AI. The big guys are getting there very, very fast. Let me talk about them very, very quickly. SuccessFactors who is a very, very interesting historically really important company in this space, they actually are the largest HCM vendor in terms of number of users. They may or may not be largest in revenue, but they’re largest in terms of footprint. Last week, introduced Joule. I talked briefly about that. They introduced generative AI in their recruiting, and in their learning and in their career. They introduced their Talent Intelligence Hub, so they actually have an AI engine to help you find a job or a career, and a really cool thing called their Capability… I forget what they call it. Capability Center for building skills and validated skills. So, very, very different set of offerings from SuccessFactors. I think they’re actually doing very, very well.

Workday announced a lot of similar technologies named Workday AI. Workday’s strategy is to build AI into their core platform, and by the way, as is all the other vendors, but to Workday, that is a big deal because they have a very, very integrated core system. They manifest it in a new tool called growth plans where you can actually generate growth plans for employees based on history and based on other opportunities inside of the company, which is a big area, of course. And they are working on a chatbot, and they showed a quick demo of something they’re working there.

“50% of the calls  … are about skills”

Everybody knows Workday isn’t easy to use for end users, so they’re very focused on that too. Oracle is doing the same thing. Oracle announced a whole bunch of generative AI features, and apparently from what I can tell, Oracle is working with this company called Cohere on their LLM, so Oracle has lots of investment in this area too. So, you’re going to see this in the core platforms.

WHAT ABOUT SKILLS? Now, I think 50% of the calls we get from you guys these days are about skills. Let me talk a little bit about skills. Skills is essentially an AI problem, and the reason that everybody’s interested in skills is not because we need a lot of skills. We’ve always needed a lot of skills. I think that was true in 1978 when I got out of college, but what’s different is that people are changing jobs and roles at a rate of speed they never did before. We need to move people around faster into new positions or new opportunities, so we need to know what their skills are, so we can get them upskilled or reskilled and move them from place to place. So, there’s change in the way organizations work and what we call The Dynamic Organization.

By the way, next week, we’re going to do a big press release on a piece of research we call The Dynamic Organization that describes what this is all about. It means we need to know what the skills of people are. We need to know the skills for hiring. We need to know the skills for career. We need to know the skills for the pay, whether they’re ready for leadership, whether they might be in the wrong job or they can move to an adjacent role. And there’s been this concept, and I’m going to say maybe some controversial things here, that if we just build a global skills database, everything’s going to be fine. And I would venture to say of all of the companies we’ve talked to, very, very few have successfully done this. This is the theory. The theory is we’re going to take all these skills systems, all those vendors out there, and we’re going to stick it all in this thing, whether it be Workday Skills Cloud or something else, and once it’s all in one place, we’ll all be able to use it.

By the way, it’s not just the corporate learning skills and the recruiting skills and the talent marketplace skills and the pay. It’s also the talent intelligence skills generated from that, and the employee experience skills because by the way, if you’ve been paying attention to ServiceNow, they bought a skills company and they’re putting skills into the front end too. So, now we’ve got four or five sources of this. Oh, by the way, there’s a compliance program, so we need to put those in there, and then there’s a new certification program. We need to put that in there. This is a big hairy problem, and despite the fact that many, many vendors play in this, and I will just show you who those vendors are, this is not easy to do. Not only because the problem is complex and you need sort of a translation layer like Lightcast to try to make sense of it all, but every company’s different.

If you take two oil companies, if you take two retailers, you take two healthcare companies, they don’t have the same skills databases. I mean, they have similar skills certainly in their operational area, but we just finished a whole bunch of global workforce intelligence research, for those who came to the session last night, and actually there’s very big huge differences in the skills between a high performing company and a medium to low performing company. So, you’re going to have to deal with this as an ongoing care and feeding process for your company.

“This is a never-ending thing”

One of the most interesting interviews I had about skills with a large defense contractor, who competes with a large multi-billion dollar government contracts, and she said, what they do… This is the chief learning officer. She said, “What we do is every year, we sit down with all of our top engineers and we sit down for a week, and we talk about all of the new technologies that are entering the defense industry and what we need to do to stay ahead, so when that big project or contract comes out from defense, we’re prepared for it, and we build a skills database and we hire and we train people to get ready for these new technologies year after year after year.” She said, “It’s not a one-time project. This is a never-ending thing.” And that’s what’s really going on in skills.

Now, of course, AI has a lot to do with this and it’s become so exciting that every vendor has decided to jump into it, so whichever tool you buy out there, they will tell you that they have a skills engine included, and that of course makes your life even more complicated. Which one is the source? Which one is the slave? Which one is the target? How do we build a hub to connect all these things together? Do we even need to connect them together? I’m not sure if we need to. Maybe we do. Maybe we don’t. I’m not going to try to answer that today, but the basic story is that there are different types of skills technologies. Some are focused on skills relative to people. Some are focused on skills relative to jobs and roles, and some are focused on skills relative to content. And they all are there to do different things, to be used in different ways.

WHAT WE TRY TO ADVISE CLIENTS, and we do this in our workshops, is before you run around and try to build this big skills architecture as a tech team, focus on the problem. What problem do you want to solve first? Is it an underperforming group? At Procter & Gamble, it was the supply chain during the pandemic. They didn’t need to build the skills database for all of Procter & Gamble. They need to figure out how to optimize the supply chain performance. In Starbucks, it’s the store managers. So, I would suggest for those of you that are sort of baffled by all this skills technology, before you go out there and buy a whole bunch of tools, work with your leadership team and we’ll be happy to help you, to focus on the most important problem first, and you’ll realize that as you go from domain to domain to domain, the skills technology becomes more and more useful.

Now, the second area I want to talk about is employee experience. Employee experience is perhaps the tail wagging the dog in HR. Obviously, everybody’s worried about the core HCM system and the data and the talent management platforms, but as you now know, and I’ve talked about this for a few years, if the employees can’t use this stuff, it doesn’t matter how much you like it. It’s not going to succeed. So, now we’re in a world where the success or failure of every product you buy is how easy is it for people to use? How do they use it in the flow of work? How does it help them get their job done or how can they minimize the amount of time they have to spend using it if it’s something they only use periodically? That affects the user interface. That affects the AI front end to it. That affects where it manifests itself in the system. Does it come in through Teams or Slack? Is it in a portal? Is it a stand-alone system I have to log into?

THIS IS A BIG DEAL and I know this has been going on for several years. The big issue on employee experience is there are a whole bunch of new vendors working on this. There are now very fast-growing vendors. These are some of the ones that you probably know of that have built layers of software that sit on top of these enterprise applications, with interfaces for communications, for surveys, for transactions to make it easier and easier to find these back ends. And if you look at the way something like Google Works… By the way, when you go to the Google search engine or the Bard screen, you don’t know that there’s 50 things going on behind the scenes. That’s all invisible to you. You just type a search and you get an answer. That’s what these companies are doing is they’re really building kind of panes of glass that will sit on top of your user experience.

“3-4 times the market cap of Workday”

The reason I bring this up is a lot of times the tendency is to say, “Well, if we replace this hodgepodge of back-end systems with Workday or Oracle or SAP, everything will get easier for our users.” Hmm, it might. It might not. Maybe you should start at the top first. So, this has become a very, very hot market. To give you a sense of how hot it is, the company here that has spent the most money building a toolset for employee experience is ServiceNow. ServiceNow has three to four times the market cap of Workday. This is the financial performance. I know I took a little blip there, but look at the stock performance of ServiceNow. This is where a lot of the growth of this industry is going to come from, and once generative AI and chatbots are really industrialized, we’re going to be sticking those things on top of a lot of this complex back-end software and you won’t have to worry about the user interface of every single system you buy. So, that’s a big area for HR, plus of course the issue of well-being.

I’m not going to spend a lot of time on well-being, but interestingly enough, if you go back to that research I talked about in the very beginning about burnout, stress by putting unions and so forth, many of those issues have to do with stress and workload. We think by the way that the four-day workweek is coming. We have an analyst by the name of Julia Bersin, by the way, who is doing a study on the four-day workweek, and you’re going to read more about this from us in a couple of weeks because what I talked about earlier is super-powered high performing roles that we’re going to have with AI is going to enable people to get more work done with less time. So, a lot of these technologies are really there to facilitate what I believe is a transition to a much different way of working that we’re going through right now in most of our companies.

By the way, the other company that’s all over this is Microsoft. I talked about Viva in the very beginning and Viva Skills, which I think is going to be very disruptive. There’s also copilots for Viva. Not only has Viva as Microsoft invested in all of this platform infrastructure, which you can use, but there are now AI tools on top of it, copilots for goal-setting, copilots for surveys, copilots for learning, copilots for communications and so forth. So, there will be a lot of new ex applications that will be changed by AI. By the way, these charts that have these blue squares, I’m going to make them available at the end. We’ll send you guys a link on how to download this, and you can go through this later and show it to your teams and think about what role some of these different AI tools might play in your company.

Okay. Next topic is recruiting. Recruiting is the most experienced AI domain in HR because in a sense, what recruiting firms have been trying to do for a long, long time is capture all sorts of complex information about candidates, their personality, their skills, their fit, their experience, and figure out if that information is relevant to the job, the company, the culture, the management, the team or so forth that we’re trying to hire for. So, AI really has been around in the recruiting industry for a long time. In fact, really the beginning of the skills stuff that we now see in a lot of the learning and other tools was in recruiting. LinkedIn, for example, did sort of behind the scenes skills analysis for many, many years. So, now it’s gone mainstream, and all of the big recruiting tools, whether they’d be sourcing, candidate relationship management, ATSs, are adding AI more and more and more.

Last week at the LinkedIn Talent Connect conference, they unveiled a generative AI on top of LinkedIn Learning and on top of LinkedIn Recruiter. So, now if you’re a recruiter and you’re trying to find a software engineer in Eastern Europe who knows this, this, this and this, you don’t have to go read a book on Boolean logic to try to figure out and type that query. You can say, “I want a software engineer,” and you can literally write it in English, and it will generate the query for you and find that information out of database. That’s the kind of thing that’s coming in AI and I think you’ll see all of the recruiting vendors doing this.

“A focus on AI … (in) the candidate experience”

One of the vendors in AI that I know very well said to me, “In a sense, the most sophisticated AI in HR is in the recruiting domain because recruiting has multiple levels of problem. Is this person potentially a fit for our organization? Will this person pass the interview candidate? Will this person fit the particular job role? Will this person have the particular technical skills for the projects we’re going to do?” Those are four different AI models that are basically running behind the scenes to give you the right candidates when you do recruiting. So, very exciting stuff going on.

THERE’S ALSO BEEN A LOT OF FOCUS on AI in the front end, the candidate experience part of recruiting. I want to highlight Paradox. I’ll talk about them in a minute. I’ll talk about the HireVue acquisition, which is all about building, taking intelligence in a selection and assessment, and bringing it forward to candidates. And then, a company that most of you probably forgot about called SHL, that’s been through kind of the security’s life getting acquired by CEB and spinning back off, is now coming back as one of the largest pre-hire assessment companies in the market. So, this is a very exciting phase, and I think most of you are probably spending a lot of time on that, and I think in recruiting, there will be tremendous transformations that’ll take place during my AI.

By the way, one more thing on recruiting, we did a big study on this last year and the year before, and what we found is that we’re not eliminating the human part of recruiting. No matter how hard you try and whether you think AI is going to do the right job of recruiting, the recruiter still has a critical role not only in getting to know the candidate and matching the candidate against the role and the team, but in deciding if maybe this is an internal hire, maybe this should be an internal candidate versus an external candidate, working with the hiring manager on being more of a talent advisor about the type of person they need to hire. So, the role of the recruiter is going to be upskilled significantly into that superhuman type of role that I mentioned earlier, because some of these more difficult transactional parts of recruiting are going to get automated.

Second area, number eight… I can’t believe I’m at number eight already. Is the talent marketplace. Let me just take a minute on this. I want to give a lot of credit to Gloat and Fuel50 who really kind of pioneered this. As you know, in a job market where there’s a 3.8% unemployment rate and it stays low and it gets lower and lower and lower, like I talked about earlier, you have to recruit internally. You cannot grow. You cannot evolve. You cannot necessarily transform your company without moving people around. And there’s all sorts of cultural reasons why that’s difficult, but technologically, that is getting easier and easier and easier. And what the talent marketplace does is it uses AI to match people to internal opportunities, and it doesn’t wait for somebody to look for a job. It actually looks at information about an internal candidate and recommends opportunities for a role, a project, or perhaps a mentor to do that.

It really uses the same dynamics of Airbnb versus Marriott, and that is if you look at the jobs in your company as a marketplace, not a top-down directed, boss decide everything that happens, and you let people look for jobs, you actually can generate a much higher value company than you can if you wait for the management team to make all these decisions. This is essentially the essence of The Dynamic Organization research we’re launching next week, is that you want to empower your company to be agile and to act agile, not do agile projects, but to operate in an agile way. That’s why the talent marketplace is strategic. The talent marketplace, it’s actually not just an HR tool. It’s really a very strategic way to change the operating model of your company. These are the companies that have significant products in it, and by the way, most of the vendors are adding these kinds of capabilities. This is an AI-powered system that uses a lot of the same technology that’s in the sourcing tools from the talent intelligence vendors.

WHAT ABOUT CAREERS AND LEARNING? Now, I’ve been doing learning stuff since 1998, something like that. We are in another new world for learning, and I think the learning industry kind of needed a shot in the arm. There’s a lot of learning management systems, learning experience products, learning experience platforms, content companies, other forms of micro-learning and so forth. Now, we can take all of that information and all of this content and all these assessments and interactivities and videos and things that we created in learning, and we can apply it using AI to the growth opportunities that people want, to the in the flow of work opportunities people need, and simply to answer questions. For example, in our copilot, we have put most of our content into there. You can ask the copilot a question and it will answer a question from a video or a podcast or our research without forcing you to go in and read the source content, and you can do that now more or less off the shelf in your learning environment.

“Object-based learning”

So, it’s going to be very, very significant and I think of all of the domains of HR where AI is going to have a big impact, the L&D is going to be massive. All the way to the degree of people saying, “Well, maybe I don’t need to take this course. Can I just ask a question and maybe it’ll just take me to the chapter or the paragraph or the piece of the video that I need, and then I’ll just go back to my job and worry about the course some other time?” That’s actually what we used to call… Cisco, called it… I forgot. There was a word for it. Object-based learning. We’re actually going to be able to do that. We’re actually really going to be able to do learning in the flow of work.

I talked about LinkedIn. If you want to see a good example of this, LinkedIn basically introduced this last week for LinkedIn Learning. You can now go to LinkedIn Learning. You can ask a question in the soft skills from the library. It’ll find the answer to the question and it’ll show you which course it came from. That’s just the beginning. They haven’t even applied it to some of the more technical skills yet.

One of the reasons the learning and development market is so messy is because there’s so many applications of learning. Sales training is different from leadership development, which is different from customer training, which is different from onboarding and so forth. So, the vendor market has really sort of fragmented itself into different categories. Eventually, I suppose, there could be one vendor that does all of this, but I don’t think I’ve ever found an L&D department that doesn’t have 10 tools, 15 vendors, 20 content providers and so forth. So, despite the fact that there are many, many new products in the market, it’s still a very complex market. The content industry itself is changing.

I WAKE UP SOMETIMES in the middle of the night thinking about our business, thinking to myself, “Well, maybe all the content we’ve built is obsolete because if people can just go out and search the whole thing, maybe we don’t need to build these fancy PDFs and all these beautiful images and things you guys like to read.” That’s what’s going on in the content industry is content providers are just beginning to realize that they can build content for AI using the power of AI in a very, very different way, and that goes for soft skills, hard skills, professional content, compliance content, and so forth.

The coaching market is going to be impacted by AI. For the last three or four years, there’s been a huge growth in online coaching, AI based matching to coaches. Coaching platforms like BetterUp has done really, really well because we needed it. We could democratize the coaching to much more people. I would not be surprised in a year or two if your coach might be an AI. It might be a bot. I know if you remember these coaches that were around many, many years ago, they were sort of psychological coaches that were built by academics, that is now coming to the market as well. So, these vendors are all going to be taking advantage of this and I think they’ll be disruptive also.

The final thing of course is just this big mess. I mean there is just a lot of learning technology, too many tools, too many different systems, too many different content development and content aggregation systems and learning experience platforms. So, I think we’re going to see a much simpler experience when we lay AI on top of this, and I’ll talk a little bit about the vendors in particular, a minute. One more or two more categories, and then I want to go through the trailblazers for you guys. Okay. Go back to the beginning again. Tight labor market, high turnover, employees under stress, jobs changing, organizations trying to become more dynamic.

“Suddenly … this gold mine of information”

Guess where all the information is you need to know about what to do? Just ask your employees. They will tell you. As you’ve heard me say many times, the most valuable source of information you have about how to make your company better is in the minds of your employees. They know. They know what’s working. They know what’s not working. They know why the customer did or didn’t buy what they bought, but they can’t tell you unless you ask them. So, we need to open up this aperture of listening.

THE LISTENING INDUSTRY IS OLD. It started in probably in the 1920s and 1930s with Frederick Taylor and other I/O psychologists asking people questions, doing annual surveys, doing opinion surveys, and so forth. We’re now at the point where we can use AI for this. We can do surveys in near real time. We can get passive listening like Perceptyx has done and other vendors. We can analyze sources of data from different inputs from employees, video data. Medallia actually has video-based information and audio-based information they can capture from employees.

This is a big opportunity because in your employee experience strategy, which is somewhere buried in your HR department and sometimes the listening guides are over in people analytics, you suddenly have this gold mine of information you can use to make better decisions about the company, about the HR strategy, about the pay, the rewards, and so forth, and the benefits. And these vendors are all dealing with it too, so if you think it’s been disruptive for core HR, for recruiting, for learning, these guys have the same level of disruption going on as well, and I’ll show you some examples of that. And they can do more intelligent analysis, more intelligent reporting, more intelligent diving in.

One of the things we were just talking back here in the back, one of our people in the company’s getting her MBA, and she’s talking about how excited she is using SaaS and Tableau, and I said, I’m thinking to myself, “You’re not going to need any of that stuff because pretty soon, you’re going to ask a chatbot a question and it’s going to go out there. It’s going to run the analysis to give you back the answer.” And I’ll show you a new tool from Visier that does that. So, this area of accumulating information, making sense of it, and then bringing it to you as an analyst or to your line leaders is going to be really revolutionized by AI.

By the way, I have decided to call it systemic analytics because as we’re talking about systemic HR and connecting the pieces of HR together, the same thing’s true here. The reason people analytics and employee listing has been so hard is because the data’s sprinkled all over the place. Some of the data is in the LMS. Some of the data’s in the surveys. Some of the data’s over in some other system. You have to hire a PhD in data science to bring it all together, and then a year later, you get the answer to the question you asked a year ago, and that hasn’t been particularly satisfying for people. It’s interesting to me that of all the people in HR I talk to that seem to have a hard time hanging onto their jobs, the people analytics people move around a lot because people get frustrated with how hard it is to do this.

I THINK THAT’S GOING TO GO AWAY. I think if you look at the way some of these AI systems work, we’re going to be able to pull massive amounts of heterogeneous data together. The AI can make sense of it. I mean, you can play around with ChatGPT or Bard and you’ll see how easy it is, and that problem will get much, much simpler. So, there’s going to be a massive change in the listening and people analytics market, and I think that that area of analytics is going to be coupled to this area of talent intelligence. So, you’ll be able to say, “Here’s the reason we have retention issues. Here’s the reason we have performance issues. And by the way, let’s look at that data relative to the outside market too and see what we can do to benchmark ourselves against other companies in our industry to improve.” So, this is going to be really, really fun and very, very, for geeks like me, it’s going to be really, really an interesting area of HR.

“Trailblazing examples of how AI is going to transform HR”

Okay. We’ve got six minutes left. I told you guys I was going to go kind of fast. What I’d like to do now is I have the privilege of talking to hundreds of vendors. Most of them give us an hour or two in-depth briefing of their products, and we get to know what they’re doing as best we can. And what I’ve noticed in the last six months or a year as well, everybody is of course trying to do AI in different ways. There are some really amazing examples, so what I’m going to do is I’m going to give you 10 or 15 examples. I’m not recommending that you buy things from these companies. I’m not endorsing them, but I’m just telling you that I think these are trailblazing examples of how AI is going to transform HR. So, think about this as education, not promotion of these vendors, even though with some of the vendors, you’re going to be very excited.

The first one is Eightfold. Now, you guys know we built our whole global workforce intelligence research on Eightfold. Eightfold is one of the pioneers in talent intelligence. When I met Ashutosh 5, 6, 7 years ago, I couldn’t understand what they were doing. It made no sense to me. Now, it’s come along that we’re all basically saying, “We need a talent intelligence system that can infer skills and identify job opportunities, that can look at inconsistent roles, that can do job design architecture and so forth.” So, I give Eightfold credit for really pioneering that. And if you want to go see what they do, you’ll be amazed. It is all based on AI-based talent intelligence technology.

The second is Paradox. Now, Paradox is also a fascinating company. Paradox started life I think 10 years ago, maybe longer, trying to make the candidate experiences easier. I want to apply for a job. I want to know when are the hours of this job. How much does it pay? Do you have this kind of benefit? Lots of questions and back and forth, and they built a conversational interface. They, over the years, made it better and better and better, and eventually built out an entire conversational ATS. And you look at the companies that are using Paradox, and they are doing massive amounts of recruiting, whether it be high volume or high value recruiting, using this conversational interface.

THE REASON I THINK YOU SHOULD look at it is they have actually innovated a lot of the user experience in the chat conversational paradigm that other vendors have not figured out how to do yet because they had so much time to focus on this one domain. The other lesson I would give you here is that every chatbot has to be, to some degree, designed for the use case or the domain that it serves. I don’t think there will ever be a universal chatbot that does everything you want to do in HR. Maybe I’m wrong, but Paradox is a really, really good example of that.

The third one is Gloat. Gloat is not at the conference. They decided not to come, but these guys are also an AI engine that built their AI originally for talent matching. They were going to use it for recruiting. They immediately found through the applications of some vendor or some client work they did at Unilever that it was going to be used for internal mobility. They renamed the product InnerMobility, and then eventually came up with the concept of the talent marketplace, which other vendors like Fuel50 were already doing, and built a really state-of-the-art system for internal mobility. Again, if you have a chance to see it, I think you’ll just see what the opportunities are to use AI for career, internal mobility, mentoring and so forth.

The fourth is Visier. Visier is a fascinating company. Visier probably isn’t as well known as they should be. This is an analytics company that built this really massively scalable analytics platform that can sit on top of virtually any HR platform you have. It connects to all the HR data you have, and then you generate reports for your end users. But who wants to want to report? I don’t really want to run reports. I just want to ask it a question and get an answer. Well, this new product Vee does that. You can literally ask it a question like, “Why do I have high turnover in this department? What is the compa-ratio of the employees in this domain? Who are the 10 people that were hired in the last month? Who are the 10 people that just left last month?” Any question you want to ask, it can dig around inside of the metadata management of Visier, and it’ll give you the answer. So, I think you should take a look at this because it’ll give you an example of what an analytics conversation interface looks like.

I TALKED ABOUT MICROSOFT VIVA earlier. I think Microsoft probably has a pretty big booth here. I really think you need to look at Viva, not because I’m a Microsoft fan necessarily, but because what they’ve done, because they’re so attuned to the end user experience, let’s face it, Microsoft’s been worrying about desktop applications a lot longer than most of the other people in HR that they’ve virtually built, in some sense, learning, talent marketplace, career, skills assessment in the Viva platform, and I think it’s pioneering in the sense that they’ve done this all from the front end down, as opposed from the back end up. So, I suggest you take a look at them.

“Pioneering innovator in talent intelligence”

Strivr Labs. Strivr Labs just have to be a company I’m very, very fond of. These guys basically invented the idea of VR. It’s now widely used in banks, insurance companies, retailers, manufacturing companies, telecommunications companies. It’s funny. Last year, before AI or the year before that, we were talking about the Metaverse. I don’t know where that went. I guess it’ll come back later, but these guys… It’s still out there, you guys. It’s coming back, don’t worry. These guys are pioneers there. I would suggest you talk to them.

SeekOut. Now, SeekOut is what I would consider to be a fast follower, pioneering innovator in talent intelligence. These are folks… I’m sure you’ll meet them. A lot of the management team is here. Ex-Microsoft, senior AI executives, software executives that took all the work that companies have been doing for maybe a decade in recruiting and sourcing, and applied the latest and greatest real-time runtime binding, skills analysis for recruiting, talent mobility, career, and so forth. So, I suggest you look at them. They have some really interesting applications of AI that I think you’ll find incredibly useful in sourcing and other forms of talent mobility.

I GOT TO GIVE SAP CREDIT. I’ve been working with SAP for a long, long time. When they bought SuccessFactors back in 2000… I don’t remember if it was ’08 or ’09 or whatever it was. It was a mess. I mean, they had the HCM on-premise. They were trying to build stuff in the cloud. They were trying to do their new database technology. They had SuccessFactors. They have literally reinvented this whole suite. They’re probably the furthest ahead in the actual implementation of AI in HCM. So, if you’re looking around at core systems, I think you should go look at Joule, take a look at SuccessFactors. They are really certainly to me right now, a model to watch.

Sana, this is a company we’re working with personally on some of the stuff we’re doing. This is a really interesting company headquartered in the Stockholm that has built a LLM-based learning platform. This is a ground up, work all over, start from scratch learning platform based on an AI course. It’s a second generation AI platform. They’re not at the conference I don’t think, but I would imagine you’ll see a lot more about them in the next couple of years, and we’re doing some unique stuff with them in our copilot.

Aris, fascinating company. If you take that course I mentioned to you earlier, the mobile AI learning course, and I’ll show you the URL in a minute one more time, it’s built on Aris. Aris does microlearning using AI and delivers it through your phone. We gave Aris a research report that we did on AI and their AI read our AI report and generated a course and put it on the phone. Now, I think there was a little bit of handwork behind the scenes, but not too much, so this is a very important application to me because we all want to learn on the flow of work. I just want to look on my phone, do a little… I used Duolingo. If you ever used Duolingo, it’s basically Duolingo for everything and training you ever want to do. So, very important company.

“These guys just don’t stop”

Cornerstone. The reason I want to highlight Cornerstone is these guys have one of the most difficult sort of business problems of anybody. They own some of the world’s biggest, most legacy complex learning management platforms. They have a massive content library. They build their own content. They have built an AI infrastructure around all this that now as of the last couple of months, they can tell you in your company, if you happen to use Cornerstone, the utilization of content, who’s using it, the amount of the value of it, and all the analysis of your content versus all of the other companies like you in your industry. Very interesting application of AI.

Textio is another one. AI before it’s time. If you’ve ever used this tool, this is a human LLM. This is an LLM that will show you visually, if you’re typing a job description or you are doing a performance review and you are biased, it will tell you you’re biased. How does it know you’re biased? It’s looking at hundreds of thousands of other job descriptions and the effectiveness of them using AI to make your life easier. Again, that’s the big data analysis kind of problem before.

This company, Bob, they have a big booth out there. HiBob, another example of a core HR system. The Instagram of HR, they like to call it. By the way, we happen to use this tool. It’s really very, very cool. It’s a roundup reinvention of a core HR system designed for managers, employees, not just for HR. Rippling, another redesign, start from scratch, rebuild the core HR system, build it around an employee database, allow you to build provisioning, expense management, all sorts of other tools on top of it. Another, to me, advanced platform that you should look at. LinkedIn I talked about earlier.

And then, of course ServiceNow and I’ll just take one minute on ServiceNow. ServiceNow is one of the most impressive software companies I’ve ever run across. These guys just don’t stop. I mean they have built the world’s leading service delivery system for IT. They now have I think 8,000 or 9,000 or 10,000 customers using their HR service delivery, employee experience platform. They’ve added skills to the platform and generative AI. Another example of somebody I think you can learn a lot from.

THAT’S THE BASICS. Let me just take one minute and wrap up and I’ll let you get out of here. This is a significant change in the market. It does not obsolete anything that you have. It doesn’t necessarily replace anything that you have, but it’s enormously disruptive because the use case in the behavior of an AI system is so much more intelligent and so much more productive, than a traditional transaction application, that I think it’s the key to you delivering solutions to your employees, to your managers, to your leaders, and to yourselves that will really revolutionize the productivity we need in this post-industrial economy.

Thank you so much for giving me an hour to give you this information today, and I encourage you to go through this course if you’d like to learn more. Thanks a lot.