Big AI Announcements From Workday, SuccessFactors, and LinkedIn

September 30, 2023 00:19:26
Big AI Announcements From Workday, SuccessFactors, and LinkedIn
The Josh Bersin Company
Big AI Announcements From Workday, SuccessFactors, and LinkedIn

Sep 30 2023 | 00:19:26

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Show Notes

This week and next we're going to see some big news from the three biggest companies in HR Technology. In this podcast I explain what Workday announced last week and give you a sneak preview (nothing confidential) about what's coming from SAP and LinkedIn.

The message is pretty clear: Gen AI is not only here but it's about to add massive value to these systems. There are some threats to come, but generally thinking you'll see how creative and solution-oriented these offerings are. (Definitely nothing to be afraid of.) I also discuss what Gen AI means to you and your IT department, and give you a preview of the three big research studies coming out soon: The Dynamic Organization, Systemic HR, and Irresistible Leadership. See you all at the upcoming conferences.

Additional Resources

Understanding AI in HR: Research Study

The Role Of Generative AI In HR Is Now Becoming Clear

People Analytics Evolved: Systemic Analytics Powered by AI

The HR Tech Workshop, Certificate Program By The Josh Bersin Academy

View Full Transcript

Episode Transcript

[00:00:07] Hello everyone. This week we're entering one of the most active periods of time in the HR Tech space because of the two big conferences coming up, the US HR Technology Conference and then the Paris Unleash conference. And in preparation for that, I want to talk about three big announcements. This week. Was workday rising. In which they introduced many, many things relative to AI that I think you're going to care about next week you're going to hear from Success Factors, I'm going to talk about some things they've already announced and what's going on there. And then on Tuesday is LinkedIn, Talent Connect and you're going to see a flurry of AI announcements from them. And what you're going to see in all three cases is real world value add solutions, features, capabilities that are going to change the paradigm of what they do. And I mean that seriously. The paradigm of these semi transactional systems. For the most part they're transactional systems is going to change because of AI in a very, very positive and productive way. And we are going to be introducing at the HR Tech conference our research on the post industrial economy. And you're going to see, if you don't already know this, that these AI capabilities are going to be more or less mandatory for the economy going forward. So let me talk about the three companies now. First of all, workday. Workday is a very, very successful company, approaching 9 billion or so of revenue grew at 19% or so recurring revenue last quarter. The approximately 10,000 customers, something like 65 million users. They are the sort of ERP of the future as certainly their brand. They don't think about themselves as an ERP, they think about themselves as a platform company, which they are. And Neil Bashuri, who's now the chairman and he's the co president, but he's assumed going to be only the chairman, is going to move back into much more of a role of technology in future. And they are very, very aware of the platform shift that is taking place. And so what they introduced was a whole series of generative AI features, generating job descriptions, comparing contracts against invoices, creating growth plans for individuals. You can read about them in my blog. They're very, very interesting. They're not really groundbreaking, but they are important and they're going to add a lot of value in some sense. They are also capabilities that you could do yourself if you cut and pasted content from Workday into Chat GPT. But the difference is that when you do it within the platform, the large language model underlying the platform has data about your company that Chat GPT doesn't have and it's safe. So presumably if you created a job description in Workday or Success Factors or Oracle or any other platform, including LinkedIn, which I'm going to talk about in a minute, it would know a lot of things about the other jobs in your company. The levels the skills and so forth and should create, if it's well designed, a job description that's very, very relevant and consistent with the rest of the things going on inside your company. And that's really the magic here. It isn't the fact that it can generate words, it's the fact that it can use vast amounts of data to generate the words in a very relevant way to your user or your company. And that's the challenge, of course, for these vendors, is to make sure that data system works and that they're effectively leveraging these data elements inside of their own platform. The third thing they introduced was a capability that I've been talking to Jeff Galfuso about is this idea of an Ask Workday chatbot and that is not available yet, but it's a massive, massive opportunity, of course, because Workday is hard to use. It's got lots of screens, it's got lots of panels, and most people don't know how to use all the capabilities of it unless they live in it. So if you could just ask Workday how's hiring going, move this employee from this city to this city, give this employee a raise, et cetera, and it could come back to you and say, well, what percentage raise are you considering? Here's the percentage raises for the other people in that job, et cetera, et cetera. It's going to be massive and that has not been finished yet. They're really just working on it, but you can expect that probably over the next year. Second big series of announcements is from SAP. Now SAP has sort of got a different culture from Workday. They are also a platform company, but they're really a much bigger company and much more industry oriented. They have a much larger user base than Workday, by the way. There's many more users using success vectors than Workday, although the number of clients is probably somewhat similar. And so what they've done is several things. They're also introducing similar generative AI features, but there's more. They have done two other things. The first is they introduced a product called Juul, J-O-U-L-E-I particularly love that name because I'm a mechanical engineer and a Juul is a unit of energy, like a watt. So I think it's kind of cool, although a lot of people probably think it's kind of stupid. But anyway, I think it's very cool. And what Juul promises to do, and we'll all see it next week, is do what the Ask Workday product or feature is thinking about doing. You can ask it questions about any part of your organization's operations through all the SAP products. Not just success factors, the other modules of SAP. And it will bring back information, it will invoke transactions, it will step you through a process and so forth. And my understanding is that they've been working on this for quite some time with the help of IBM to use the generative capabilities of their own LLM and some of IBM's technology to put this together. And I think SAP customers are going to adore this. I'm sure there will be pieces of it that don't quite work yet. But this is another reinvention in a sense of how these ERP, human capital systems work. They are also introducing a relationship they have with Microsoft working on Copilots to support the Microsoft Copilot which comes embedded in Windows Eleven and in teams and in Viva. So since Success Factors and SAP actually is the underlying infrastructure at Microsoft, of course Microsoft wants to do this because they'll not only be able to sell it, but they'll be able to use it. And so there'll be generative capabilities in the Microsoft infrastructure that will probably connect directly to success factors and other though, you know, there are some products in Microsoft that compete with SAP. They're building some of their own HCM and ERP stuff. Anyway, lots of, lots of things there for SAP customers. The third one that's coming and I don't want to preannounce it, but it will be available to you as of Tuesday is LinkedIn. LinkedIn of course, you know, has 600 million or more users and most large corporations that I know use LinkedIn for recruiting. They use a product called LinkedIn Recruiter. Many of you use LinkedIn Learning and then it of course has features for internal mobility and succession and skills analysis and so forth. You're going to see them add some pretty cool generative AI features to the Recruiter product and to learning. And I think the learning features are going to be essentially emblematic of all of the learning platforms going forward. And let me just talk generally about it since this is an unannounced yet. But if you think about the problem we have in corporate training and learning and this is not a small market. This is a 300 and 3340 billion dollars market. This is everything from onboarding to compliance training to technical training to leadership training to It training to safety training to dei training on and on and on. Most companies have, I would say virtually every company has tons of content. Videos, articles, stories, interactivities, assessments, long courses, simulation courses, et cetera. In our academy alone we probably have close to a thousand resources and learning objects in the JVA. And of course the designers of those systems try to build a user experience on top of it so that you can click on a button and find what you need and consume the content that you want. Of course we don't want to consume things in long periods of time anymore. We want small pieces. So we want a five minute chunk. We don't want a 1 hour course. We don't have time for that. Show me the five minutes I need right now and I'll come back later and look at the rest of the course. Well, that's really, really hard to do with traditional search technology. It's never really been very possible. Now it is because what the generative AI tools do and we are doing this in ours, by the way, is they literally index or analyze all of the content. They can go through video and audio and text and understand it. They put it into the neural network, and they allow you to ask questions in English. And it will either answer the question from the content as if you were talking to the instructor, and this absolutely works because we've done it in our system. And then it will take you to the point of the course that you're interested in. And if the system is architected, well, it will open that for you. So imagine you're a software engineer and you're having problem with some data structure. And you ask it a question like, how do I do? Blah, blah, blah. I don't know what the right word would be. And it goes in and says, the answer is here. Here's the general approach you take. Let me show you the video of how the instructor would explain it to you. By the way, that applies to soft skills. That applies to management. Give you another example. I'm about to go into a performance appraisal with an employee who has been coming in late, who's been difficult to work with, who's been behind on their goals. How should I start that conversation? How should I conduct that conversation? What are the things I should say? What are the things I shouldn't say? Frankly, I'm not very good at that myself. I'd love to read a few paragraphs on that and listen to a leadership expert talk a little bit about it before I go into that meeting, even if I have been trained in this in the past. So there's a lot of applications for this, to say nothing of compliance documentation that's buried in some cabinet that nobody even knows where it is anymore. Operations tips on how to run the oil drag or drive the truck that could be now accessed over a phone. Because once these generative AI systems exist, we don't need to type into them. We can talk to them, and they should be able to talk back to us. So now we really can access this large corpus of content through the generative AI in a much, much higher value way. I've always felt from all the L and D work we've done over the years, that probably 80% of the LND content that you guys have all built and bought probably sits there. And rarely, if ever, gets used. It may have been used in the first year of its life. And then it just sits there, right? And you have to find it and edit it, and rarely do you ever get rid of it. And so it's just cluttering up the experience for everybody else. So that's a massive, massive change in this market. It threatens the LXPs because the LXPs were essentially designed to solve this. This is going to go around them or supplement them. And it also allows you to understand what content you have. And let me get to that point next, because this to me is maybe one of the biggest ROIs of AI that I've experienced and I believe is out there. So you take a company like ours where we have thousand research studies, 500 case studies, statistical data on this, that, and the other thing. In HR, we have a bunch of videos, a bunch of courses, et cetera, and somebody asks us a question about how do we do performance management in a retail organization that has this, this and this going on? Well, if they don't get to the right person, no one knows what we know as a group. No one person does. I might know a lot of it, but certainly not all of it. Well, the AI does. The AI does collectively know everything that the Josh Burson company knows. Now, it's not going to be as explanation oriented. It may not be able to provide consulting, but it's pretty doggone close. And in our particular case, our system that we haven't introduced to customers yet can generate implementation plans. It can compare this versus that. It can give you best practices. It can give you examples very, very easily. We didn't have to do a lot of Tweaking to get it to do that. And just think about the corpus of knowledge you have in your sales organization, in your sales training, in your product marketing, in your operations areas, in your supply chain, in your customer service, in your finance organization, on and on and on. That information is there. It's sitting around in lots and lots of places and documents and courses and stuff that's going to all get unlocked. And so maybe eventually there will be vendors that do this, but you'll probably do a lot of it yourself. And so you'll be making your mind up. Do we buy or build these kinds of systems? I think the big vendors, the three that I mentioned, SAP, Workday, and LinkedIn, are mostly working on their own stuff. They're going to make their own systems more generative, but they're adding APIs. Workday introduced an AI partner program. I'm not sure there's a lot of deep integration yet, but there will be they'll expose more and more of the workday interfaces to third parties. And so you're going to have lots of options to do this yourself. Now the other thing, of course, I want to mention on AI, which I'm going to talk about at the conference, is this may look easy, but it's actually kind of tricky. And the reason is, in any one of these applications, whether it be the three vendors I mentioned earlier or the stuff you do yourself, you have to decide what information do you want to source for this thing? [00:14:05] Where is the quality information and where is the out of date information we don't want to put in there, who will have access to what parts of the information. There's security rules, of course. Not everybody gets to see salary information. Not everybody gets to see compliance of this or that. It all has to be segmented by users. So there's user profiling to do, there's security, there's tracking and an analytics because these systems are unpredictable. We don't know what questions people are going to ask and you want to watch what they're asking so you can tweak it and tune it to better answer the questions of your users. And then you're going to want to add data to it based on the needs of your employees. [00:14:49] Every analytics project I've ever done, by the time I finished it, I found myself saying, wow, now that I understand the dimensions or dynamics of this particular thing, I wonder what the relationship is between this and that. Well, I don't have time to go and try to build a bunch of cross correlations and probably wouldn't even know how to do it, to be honest. But you can do that with degenerative AI. I happen to use Bard a lot and I'm very frequently asking Bard questions like, would you compare the financial performance of Exxon versus Chevron workday versus Oracle versus SAP, et cetera, in my domain? And it's pretty doggone good at it, but I assume that the data is reasonably good because it's coming from the public sources inside your company. It has to be good. So you're going to have essentially an It project here because this is the same process you go through to build a data warehouse, a new employee portal, whatever the employee related system you have the user profiling, the security, the quality of data, the metadata, and then the future planning of how this thing is going to evolve. So as mystical and magic and confusing and maybe scary as this is, it's going to come down to basic It change management strategy and user interface design. The user interface design is also very interesting to me. Most of these systems kind of look the same. There's a little blue or sort of starry little icon that generate sort of the motif of generative AI. You type into it and then it scrolls through and gives you answers and little cards and boxes and pages come up to explain what you've know. That's great for now. I think it's going to get much better. I think we're going to be building these things for our phones. I think they will be embedded into the phones. If you notice the announcement from OpenAI and Johnny Ive trying to think about building a whole new phone based on AI, I mean, imagine if your phone had the large language model in it and the phone could do the work. And the phone was designed with this interface so you could talk to the phone with voice and the phone could do a lot of this for you. I'm sure that's what these guys are planning on doing. So there's going to be a lot of changes in the way these systems work. Anyway, I just wanted to give you sort of where we are. The next two and a half, three weeks are going to be very exciting. There's going to be lots of announcements the next three weeks. For those of you coming to Vegas, I will be there. We're going to have almost half our company will be there, so there'll be a lot of us there for you guys to talk to. A lot of us are also coming to the Paris Conference, the Unleash event, and then we'll be introducing this research on the post pandemic economy. The other thing I want to highlight from our standpoint is we're working on three massive research studies that are coming out in the fall. The first is called the dynamic organization. It's a year or more longer study we've done on how organizations become adaptable and dynamic, what are their people practices and the talent and leadership practices that drive changeable industry leading companies. This comes from both our HR research and our global workforce intelligence research in various industries. You're going to really want to read that. The second is the systemic HR work that we've been working on for almost two years that will be introduced at the LinkedIn Conference. And we'll be introducing more and more of that next year. And you'll see that that impacts a lot of interesting things about your career and your HR organization and your operating model. And the third is our new research on irresistible leadership, which is a never ending topic, of course, but we actually have interviewed 30 or 35 senior leadership executives or HR people and done a lot of surveys here. And you're going to see there's some actual things that have changed in the leadership market and the drivers of great leadership. So we're not just here to kind of tell you what's going on. We're here to help you deal with it and learn how to adapt to all these changes. Anyway, have a great weekend and I hope to see a lot of you at these conferences over the next couple of weeks. Thank you.

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