


14 Aug 2026 · 17m · 6 chapters

The episode covers three topics: Workday’s potential move to go private, Mark Zuckerberg’s 6,500-word essay and the implications of Meta’s AI direction, and the evolution of the HR AI tool Galileo plus new research on frontline work. On Workday, the host argues AI strategy is strong (SANA, Paradox acquisitions) and that private-equity owner Silver Lake could accelerate it; he cites Workday’s lower price-to-sales versus AI peers as upside. On Zuckerberg, he claims Meta is chaotic, data-sneaky, and legally exposed (e.g., $750M New Mexico suit), and predicts Meta will focus on consumer AI agents (WhatsApp/Facebook/Instagram) while he worries about trust and business use. On Galileo, he says it’s moving from HR assistant to multi-platform agent via MCP, connected to SAP/Workday/Oracle data, with “30 golden prompts” to reduce hallucinations. Notable examples include HR use cases (behavioral interviews, skills evaluation, salary benchmarking) and frontline work research (72%+ of workforce; 800 job titles; levers via store/line managers).
Written by AI. May contain mistakes.
Discussion on Workday's potential acquisition by Silver Lake and its AI strategy.
“The SANA acquisition, the Paradox acquisition, the other acquisitions and the company's announced strategies for AI are exceptionally strong, lots of revenue potential.”
Insights into Zuckerberg's chaotic leadership style and Meta's focus on consumer AI.
“Okay, so that's that, and I'll keep you guys informed on my knowledge of this, or at least perspective.”
Updates on Galileo's capabilities and its transformation in the AI landscape.
“When you look at the HR 2030 reference blueprint, one of the elements of it is the personal AI of each individual person in your company.”
Learn about the approach to building a knowledge base and collaborating through AI.
“those conversations, those situations, those industry dialogues are part of our knowledge base.”
Explore the significance of frontline work and its impact on the workforce.
“Now, frontline work, which I won't spend too much time on because this podcast is a little bit long already, is 72 % of the workforce in the United States.”
Discover the human capital-centric aspects of frontline work and its ROI.
“value apart and showing you where the levers are.”

Get the gist, explore an idea or ask about something said.
On The Josh Bersin Company, what are the key points of this episode?
Automatic transcript. May contain errors.
0:00Josh Bersin: Good morning. I want to talk about two elephants in the room today and a little bit on a third. The first is Workday. The second is Mark Zuckerberg's 6 ,500-word essay. And the third is What's Going On With Galileo. So start at the beginning. Most of you who are in the ATM market saw the news that Workday is potentially talking to Silver Lake about going private. The stock went up by about 15 to 20 % the first day. And I suppose many people are not sure what that means, but let me give you my perspectives briefly. And I have no inside information whatsoever, but I do know Workday very well. Workday's stock has been slightly ticking up for the last three to six months because it's beginning to become clear, it certainly is clear to me, that Workday's AI strategy has a lot of potential.
0:48Josh Bersin: The SANA acquisition, the Paradox acquisition, the other acquisitions and the company's announced strategies for AI are exceptionally strong, lots of revenue potential. And as I talked about in the last podcast, the HCM HR market is very, very healthy. Very healthy. I talked last week or last podcast about the growth of the number of jobs in HR, the importance of HR. And even though people keep talking about new HCM platforms being reinvented with AI. It's going to take a long time before anybody does that. And most likely that will be Workday in some fashion. So what the PE guys tend to do is they tend to buy undervalued assets.
1:33Josh Bersin: They usually think of a software company as an asset. Silver Lake bought Qualtrics, so they've done this before. They own Achievers, so they understand the market. And the price to sales ratio of Workday today is half or a third that of the AI companies. So if somebody were to buy Workday and not mess with it too much, accelerate its direction, which is already pretty strong, and help the company grow, they could double their investment in three to five or to seven years, however long their time frame is. Some PE firms have very long timeframes, some don't, but Silver Lake bought Skype, for example, and others.
2:13Josh Bersin: So they have a pretty good track record of buying nascent tech and then watching it grow. This is not nascent at all. This is very different. So my guess, and I can't really guarantee that this is true, but just what I would do is I would, if I was buying a company like Workday, really do everything I can to accelerate its existing strategy to move into AI. And from all the work we're doing on HR 2030, this is a huge opportunity to transform business, not just HR, to transform business. I can't speak to the finance part of this. I don't know Workday's level of sophistication there, but in the HR domain, they have a big opportunity.
2:54Josh Bersin: And let's just hope that Silver Lake sees it the same way I do, and they see this as an upside potential, not a big cost-cutting cash generation move. Okay, so that's that, and I'll keep you guys informed on my knowledge of this, or at least perspective. Second comment, Mark Zuckerberg. Now, I've tried to work with Meta over the years. I've been in and out of there for various things, and it always struck me as a company that was very chaotic in its internal operations. A lot of smart people, a lot of very savvy product strategies and technologies, but not a company with a strong direction. Rather, a company that does a lot of knee-jerk reactions to market opportunities and hates having competitors.
3:38Josh Bersin: They buy their competitors and they steal IP and other data from their competitors. They're now getting sued for, I don't know,$750 million they have to pay to this state of New Mexico. And there's going to be, I guess, 49 others, I would guess, for Instagrams and Facebook's damage to teenagers and younger. And that's just beginning. So that's a little bit like what happened to the tobacco companies where they denied and denied and denied and denied until finally, you know, it just hit. So, and of course, if you go back to the election fraud and what happened in the UK where they leaked data, they're very surreptitious and sneaky about collecting data and what they do with it and not always being honest about it.
4:24Josh Bersin: And right now, Zuckerberg seems to be good friends with President Trump. So, you know, they're getting plenty of free reign to do what they want. And they were not well positioned for AI for no particular reason, just because they weren't in the enterprise businesses that AI was going after. They were in the consumer businesses. So what they're probably doing, and this is certainly what I would do, is focusing on consumer, which is really where they live and thrive. They have WhatsApp. They have billions of people using their platforms. and look at a way to build a highly personalized AI agent to superpower the personal experience you get on Facebook and Instagram and soon enough probably WhatsApp.
5:06Josh Bersin: And that is a trillion-dollar opportunity for them. Now, why? Because if you had an AI in your consumer life that was that powerful, and of course Google could do this too, and they probably are working on the same thing, You could use it for coaching, job searching, buying things, finding people, talking to people, learning, going to the gym, deciding what your medical issues are, getting a better night's sleep. You know, all this stuff that this AI could do. And in Zuckerberg's essay, he talks about that stuff. And I don't think it's a secret. Those are things we all would love to have our AIs do for us.
5:44Josh Bersin: You know, there's this kind of crazy little tool from Google now that reads your emails. I forgot what it's called. and gives you advice on your potential future fun things to do based on your emails, which my emails don't have much fun in them, but some people's do. And that type of technology applied to your consumer life would be fantastic. I mean, to just give you a small example, I get up early and I go to the gym and do all sorts of things to try to stay healthy. And I use an Aura ring, which I found to be very useful. I gave up on my Apple Watch. and the data and the information it's capturing is just spectacular.
6:25Josh Bersin: And it's a very early stage device. So if Meta does that, they hook it to your glasses, they start capturing your location, how fast you're walking, how much sleep you get, etc. It's a huge opportunity for them. But do they have the focus or the track record or the moral foundation to do this safely? I think I would trust Apple to do this. I would trust Google to do this. I would trust Microsoft to do this. By the way, Microsoft probably eventually will do this in the business world because we will have personal AIs in business. That's really what the co-pilot is. And you'll see that in the HR 2030 framework.
7:03But I don't personally trust Meta, but that's probably where they're going. And the reason I even bring it up on the podcast is that for the business world, we have exactly the same opportunities. When you look at the HR 2030 reference blueprint, one of the elements of it is the personal AI of each individual person in your company. And in a company where we have clear performance objectives and there's clear boundaries as to what's personal and what's not, the traditional old-fashioned, maybe legacy way of dealing with people is we interview them, we have meetings with them, we talk to their bosses, we survey them, stuff like that.
7:44That's how we measure and evaluate and improve the experience and the productivity tools and the business processes in our companies. But we can't get under the covers of each person. It's just too hard. And each person is held responsible for their own performance and their own behaviors. If the business AI, the personal business AI, let's assume it's the MS co-pilot, but, you know, this will be invented by somebody. took your emails and your location and your meetings and your work product, which, by the way, is all in the Microsoft graph, and periodically scanned through it and looked for your skills and looked for what was changing.
8:21That's really valuable information for the person or potentially for the manager or potentially for the company. And it would not necessarily be used for nefarious reasons. It could be used for coaching and development and decisions about who's ready to do what new job. I mean, the most important capability in business in a company level now is redeployment and reskilling of the workforce. Everything is changing. And if people can't move or don't want to move or don't know how to move from point A to point B, that holds a company back. And I, you know, I know this at the senior levels of most companies.
8:59There's lots of discussion about strategy and operations and plans. but it all succeeds or fails at the individual employee level. And if we can help our employees move to the directions that the company is trying to go, and a lot of times the employees know what they're supposed to do, but they don't know how to get there from here, from their own personal situation. That's huge. But I do get very worried about the Zuckerberg view of this. And he also, of course, proposes public policy, things that are mostly in self-interest and other things. So that's my perspective on that for those of you that want to think about it over the weekend.
9:38Okay, third thing, Galileo. I talked about this a little bit last week. We're going to be redefining what Galileo is later in September when we launch the next release. Those of you who use Galileo, and I know a lot of you do, there's more than 10 ,000 people using it and probably a thousand or so companies or more. the capabilities of a tool like Galileo are layered. The first, I'd say, generation or definition of Galileo is it was an AI agent or AI assistant for HR. And it is spectacularly good at that. And we've benchmarked it now against CLAWD and OpenAI off the shelf. And it's exceptionally good for most of the tricky and difficult and day-to-day things you want to do in HR, everything from creating behavioral interviews to evaluating skills to benchmarking salaries, all that stuff.
10:30Then we realized that in the new world, we needed to move Galileo to multiple platforms. So we've built a new version of Galileo that you can hear more about that works on all LLMs through MCP. So you can plug Galileo into whatever AI you have, and that level of intelligence is available to the decisions and actions of that agent. So that could be CoPilot, that could be Claude, that could be Gemini, that could be the ServiceNow stuff, SAP, Workday, SANA, obviously already, et cetera. And that means that Galileo can act on corporate data. So instead of giving you advice and counsel like a consultant, it can give you advice and counsel based on real data in your company.
11:15So we've hooked it up to SAP, we've hooked it up to Workday, and we have a really incredible simulation of this where you can ask Galileo questions about your team or your organization or your company and look at the data in your company and it'll give you great, amazing perspectives, analysis, and advice. By the way, that's where People Analytics is going to. The third stage, so we've opened it up to that and we've built into Galileo a framework so that Galileo knows how to interpret the data entities from Oracle, SAP, and Workday because that data is publicly available. The third stage is that Galileo is embedded into the AI that your employees use because your employees, regardless of their level or managerial role, have questions and things they want to look up and things they want to do and, you know, tactical stuff that they try to use the company Portal for that Galileo is perfect for.
12:10So in the new model where we're now implementing Galileo in some big companies, it plugs into the co-pilot or it plugs into whatever AI you have. And all of a sudden, everybody in the company has access to this trusted intelligence. And that leaves me to the last word, trust. We have been benchmarking Galileo with what we call 30 golden prompts. We have 30 detailed prompts we use to benchmark Galileo across different platforms. And it is very surprising how much hallucination, fabrication, misattribution, and out and out, I don't know if the word lying makes sense, but just incorrect things come out of the generic LLM frontier labs.
12:49And that's because they don't focus on this domain like we do. And so they crowdsource all sorts of opinions and stuff when you ask them questions about management and leadership in HR. So that's the third piece. So in a sense, we are moving into a business model for us of delivering the research that we've developed for years in a very consumable form for many, many things, for your employees, for your managers, for your HR department, for your EX platforms, for your employee portals, etc. Now, the reason I even bring it up is most of you think of us as a research and advisory firm, and that's what we are.
13:29And so the flip side of all of this interpretation and articles and blogs and speeches and things that we do is the way we do research. And I won't get into the details of this yet. I'll talk more about it later in the year, maybe next year. But we're also transforming how we do research. When you come to our conference or join us on The Big Reset or join the GHRE as a Josh Burson Institute certified HR person, or give us a call about your own situations. We are here to help. And those are those points of light, those conversations, those situations, those industry dialogues are part of our knowledge base.
14:10We don't obviously take any proprietary information or use your strategies in any public way. But a lot of what we have in our corpus
14:20Josh Bersin: is tacit knowledge from years and years of independent advice and counsel and advisory services. And so what we're going to do next in our business here, and you'll see more of this rolling out later this year, is find new ways for you to collaborate with us through AI, not only about AI, so that you can get better information in your industry. And one of the ways we're doing this right now is in the area of frontline work. Now, frontline work, which I won't spend too much time on because this podcast is a little bit long already, is 72 % of the workforce in the United States. It's more than 72 % globally.
15:00And frontline work includes about 800 job titles, firemen, truck drivers, nurses, retail workers, restaurant workers, people who work in factories, people who deliver things, airline flight attendants, people that work at the front desk in the airline, even The pilots, in a sense, are frontline work. And some frontline work jobs are low-skilled. Some of them are high-skilled. We have a really robust model of five levels or five types of frontline work that you can look at.
15:31Josh Bersin: And so what we're doing in frontline work now is we're really doing a lot of interviews and case studies and surveys about the business of frontline. And the work that we're doing that's going to be announced in October at Workday Rising, because we're doing this in partnership with them, is to explain the business of frontline work. Because the business of frontline work is a very human capital-centric business. For those of you who work in white-collar jobs, you have direct access to the revenues of the companies in an indirect way. When you're in the front line, you are directly contributing to customer experience, customer service, customer retention, and revenue.
16:12Josh Bersin: And so things like attracting, retaining, engaging, skilling, aligning, coaching people have much higher returns on investment in front line than they do in traditional corporate headquarters stuff. And most of that capability is delivered by store managers, line managers, supervisors, plant managers, not by HR. So what we're doing in the business of Frontline is we're really taking this supply chain of value apart and showing you where the levers are. In a sense, what we're going to be doing is writing the book Irresistible all over again for Frontline. So if you want to hear more about this, come to the Frontline Summit at Workday.
16:58That's where we're going to start really introducing what we've been doing. And stay tuned for more on this. And if you're in a company that has a lot of frontline workers, please reach out to
17:06Josh Bersin: us and we'll talk to you more individually about what this is all about, what we're doing, how we can help you, and obviously hear what's on your mind. Okay, so that's a little bit of an update for the weekend. And we'll continue with some other really cool podcasts coming in the next couple of days. Talk to you soon.
Today I discuss Workday and the potential Silver Lake buyout, Meta’s personal AI strategy and it’s potential for business, update on Galileo, and our new research on frontline work. Most of today’s podcast is “analyst perspectives” but lots of direction is now clear.
The GHRE Global HR Excellence masterclass starts in September: if you want a 12 week in-depth “Masters Degree” level dive into HR, talent, leadership, and AI (with hands-on and new tools), as well as business school level case studies, join us! (Sign up here.)
Additional Information
Mark Zuckerberg blog on personal AI
The Business of Frontline: Five Types Of Frontline Work
Galileo Suite: HR Intelligence For You, Your Employees, and Your Company