SaaS Stories
SaaS Stories is my not-so-secret quest to learn what it truly takes to succeed in the world of SaaS—and I’m inviting you along for the ride! I have the pleasure of sitting down with brilliant minds and industry trailblazers to explore their journeys, uncovering the secrets behind their growth, the gaps they spotted in the market, and what really drives them.
It’s not all smooth sailing—there are challenges, unexpected turns, and moments of reflection where they share what they’d love to change about their journey. Think of it as a candid, insider’s look into the world of SaaS, with just the right amount of curiosity, empathy, and wit.
Join me as I dive deep, selfishly soak up all the insights, and hopefully share a little inspiration with you along the way—one SaaS story at a time.
SaaS Stories
Turning AI into Revenue: GTM Lessons from Galileo’s HR Revolution
Start with a sharp truth: AI isn’t taking your job, but someone who knows how to use it will. From there, we unpack a practical playbook for modern HR with Amy Farner—how to align people strategy with business goals, why data makes work more human, and where AI actually delivers outcomes you can defend in the boardroom. Amy traces the evolution from early retention models and conjoint analysis to today’s AI agents that turn trusted research into answers, plans, and work products.
We go deep on Galileo, the AI agent and AI-native learning platform from The Josh Bersin Company. Instead of generic answers, Galileo draws on vetted content and partner data to give HR leaders grounded recommendations, while Galileo Learn personalises how people upskill—turn a course into a podcast, quiz what you already know, or talk it through with an AI tutor. This is research meeting real-world execution: faster decisions, better implementation, and learning that adapts to the person and the organisation.
We also break down go-to-market lessons that transfer to any SaaS team: lead with original research, don’t sleep on the mid-market, and integrate into the tools people already use so your agent is one click away, not one portal too far.
Looking ahead, roles will collapse, agility will compound, and careers will accelerate. The winning mix pairs power skills—judgment, communication, adaptability—with enough technical literacy to supervise AI and ship work that stands up to scrutiny.
AI's not coming to take your job, but someone who knows how to use AI is coming to take your job. I actually had to Google what your job title at Beloit actually meant. So human capital practice involves advising clients on strategies to manage and optimize their workforce.
SPEAKER_01:It's also about making work more human, more approachable, more satisfying, making that work experience better for all of the people who are going to work in that company. We actually use conjoint analysis, which is a marketing research tool to predict is this person going to leave within the next year? And then how do we drive those things that will help to retain them?
SPEAKER_00:You know, with five years now in the business, what was some of the biggest go-to-market campaigns that really moved the needle for your company?
SPEAKER_01:Don't sleep on the mid-market. We often do focus on the larger enterprises. And yeah, there's absolutely huge opportunity there. But I think there's actually much greater opportunity for impact in small to mid-sized organizations.
SPEAKER_00:What excites you about the future of work in technology now that you know with AI around? I think that AI Welcome to another episode of SAS Stories. Today I'm joined by Amy Farner, Executive Vice President at the George Therson Company all the way in Arizona. Welcome, Amy. Thank you. I'm so happy to be with you today. Amazing. Now you've had quite an interesting career. I was doing some research on you, and I actually had to Google what your job title at the Loik actually meant. So human capital practice, which according to Gemini, involves advising clients on strategies to manage and optimize their workforce by combining both business and people strategy. And that's, I mean, I'd love to know more about that. So business and people strategy, those are two very important things. So scaling a business. What can you tell us about that?
SPEAKER_01:Yeah, I mean, I think that that's really at the heart of everything that I've done throughout my career. And it's where I'm really passionate. So we in the human capital space are very often looking at and how do we optimize our people practices? But those kind of optimization projects really only make sense in the context of what is the business trying to achieve. So my role at Deloitte and at other organizations as well has always really centered around how do we help to create that connection between what the business is doing and how we equip the business with the people, with the skills, with a workforce that is excited, engaged, and committed, reliable, and wants to be pointed at where the business is going. And the particular angle that I've taken on it has always had a little bit of a data spin. So I've worked in surveys, I've worked in workforce analytics. So how do we kind of really make sure that we're bringing data to the table so that we can not just um, you know, kind of make a decision we think this is what's going to work, but really analyze where is our workforce today and how do we bring it to where we need to be in order to be match up the people to where the business is going.
SPEAKER_00:Amazing. And so speaking of data, excuse my ignorance, but tell me a little bit about why that's important and how that interest got sparked as well.
SPEAKER_01:Yeah, so I mean, I think data is absolutely critical. Um, I've always been a very firm believer that um, you know, if you know one thing, you know one thing. If you have one data point, then you really don't know, you can't make decisions off of that. You can't make predict, you can't find predictable outcomes off of that. And where that really got sparked in my career is actually, um, so I started my career in the late 90s, which was uh, if you remember a previous technology uh disruption, the dot-com boom. So uh the it was a fun time to enter the workforce, right? Because you could go stand on a corner and wave your resume, and a VC funded startup would say, oh, you know, it was lovely. But you know, all of these incumbent employers were struggling with this transformation because they were competing with these well-funded startups that were saying, we've got a pool table, we've got really fun work environments. And they said, how do we get people to stay? And so I started working at the time the organization that I was working with started up an employee survey product that was based on a causal model for what are those behavioral and observable factors that predict retention, that predict is this person gonna leave within the next year? And then how do we drive those things that will help to retain them? So, what are gonna be the highest impact opportunities to um to drive retention? We actually used conjoint analysis, which is a marketing research uh tool to do it. It was so much fun because it was just really exciting to say the science backs this up and we're able to create observable change. And we were able to go back a year later and say, well, did the people who we predicted were at the highest risk of departure leave? Yeah, they were, right? So the science works and we were able to then use that information to help drive a positive work environment that would um that was really well aligned with the preferences and needs of that workforce. Um, and I think that's kind of the second piece of it is as I talk about it, it's really exciting for me to get into the data. I I love talking about that analytical piece. But when I think about what makes it all come to life, is that this isn't just about helping companies make more money by, in that case, reducing turnover. It's also about making work more human, more approachable, more satisfying, um, making that work experience better for all of the people who are going to work in that company. Because nobody says, Oh, I can't wait to quit my job. People want to be in a job that fulfills them and they're excited about.
SPEAKER_00:That's true. I'm sorry to hear you say that as well, because I'm a I'm a data geek myself and I just love diving into it. Um, but coming back to what you said about, you know, behavioral factors that can predict retention or people leaving, I think that's quite a big one because you know, I think people are at the heart of the company and they're gonna be, it's the people that determine whether a company is gonna drive or not drive and you know, succeed or not succeed. So I think it's in everyone's best interest to keep their employees for as long as possible, especially if they've spent all that time training them, um, investing in them. So, what are maybe some of those factors that you saw in the data that kind of went, oh, I think this person might be leaving soon.
SPEAKER_01:So, you know, interestingly, um, you know, when we looked at this in 1999, 2000, the number one predictor, believe it or not, of whether someone was gonna leave is that they actually would tell you that they were going to leave. So I didn't do that anymore. But you, but it wasn't, you know, hey, I called my manager and said, I'm out of here tomorrow. But if you ask on a survey, hey, have you engaged in these job search behaviors in the last 30 days, 60 days, 90 days? Um, they're shockingly honest. And so that absolutely helps. But the other thing that we found was that, you know, because employees, and we've been talking for so long about the employee value, pro employer value proposition, you know, if you are putting out there an EVP that is authentic to the organization and that your employees buy into, then that alignment is going to drive retention because people are saying, I'm getting what I signed up for. Um, and so I couldn't say, hey, if you pay people 200% of the market rate, you're going to retain them. Maybe I hope you would, but actually what we find is that pay is a dissatisfier. It doesn't actually keep people happy that long. But what I can say is that if your employee value proposition, for what you're signaling to the market and bringing people in on is, hey, we have amazing compensation, but the lived experience doesn't match that lived experience, then you have a much larger swath of your workforce that's at risk of departure. And so really being able to measure not what I say my employer brand is, but what is the actual employer brand that that is, you know, that is expressed by the experiences of our employees. And then how do we optimize around that? And if that's not aligned with where the business needs to go from a financial, from a product, from a skill, from whatever perspective, then you know, you need to take a step back and adjust that to ensure that you do have a brand that is authentic to the organization and is aligned with what you need to do in order to achieve your strategy.
SPEAKER_00:I completely agree with that. I don't think money, I mean, money maybe motivates people for about a month and then the happiness just starts to decrease quite quickly after that. Um, we've recently implemented that's what I would call clarity, like career clarity for especially for our juniors in the company, where we've kind of laid out what you can expect and the growth opportunities to be in the next five years. And I think that's one thing that that really helps. Because I remember my first ever job leaving it because I just saw no future there. And I was like, I just I don't know what I'm meant to be doing here in the next five years.
SPEAKER_01:You know, I and I'm glad you say that because if you think about, we've been talking for, oh my gosh, it's been probably eight, nine years, we've been talking about future of work and the idea of career path. You know, we're we're getting rid of career paths and we have lattice careers. And as someone who did enter the workforce during a time of very, very structured career paths, that terrified me. Because what I loved was being able to log into work or show up to work physically those days and say, okay, today I'm a senior analyst. And if I want to make it to that next step in my career, here's the job I'm gonna be doing, and here's what I have to do to get to that place. And when we start saying, well, you're really collecting experiences and you can go in any direction that you'd like, that can feel overwhelming, particularly, as you said, for more junior folks in the firm. And so I think that striking that balance to say your responsibility to equip you with the foresight and the knowledge and the skills and the experiences that are going to help you to align to the right opportunity for you.
SPEAKER_00:And so taking a step back a little bit and coming back to kind of your your journey now as vice president at the Josh Burzon company, how have you taken, you know, everything you've learned about data, everything you've learned about HR and applied it now? And tell us a little bit about what the company does, what are the main um product offerings?
SPEAKER_01:You know, at the core of what we do is we help organizations and HR professionals to make better decisions and to drive their people strategies in alignment with the business strategy. So exactly where we started today. Um, Josh has been in this field. So our founder, Josh Burson, has been in this field for over 20 years. Um, and he and I actually met at Deloitte. Uh so that's actually a, you know, kind of a shared, a shared legacy. And when we started the company back in 2019, 2020, really where we were focused on is how can we help to build capabilities for HR professionals and for HR organizations. So we actually started with a learning and development tool that we called the Josh Burson Academy. We've now evolved that. We call it Galileo Learn. It's part of our core product suite. But that's kind of one key component, and that was really the founding key component is how do we help equip this function with the skills and capabilities that they need? Um, on top of that, we also have always, as an organization, and many of us as individuals have been really passionate about doing research. And that really brings that data piece into it. And so, how do we do both quantitative and qualitative research to help organizations set set strategy on critical issues? How do you build your EX strategy? How do you understand how to become a world-class learning and development organization? What are those organizations that are seeing outsized impact, having what are they doing differently, and how can you chart a course to get there? And so from there, we really started partnering with organizations in an advisory capacity, publishing research. But where things really got to get to really kind of started to get very interesting was um with the advent of generative AI. So Chat GPT hit the hit the market. And so we were there, we were writing a ton of research, we were helping to upskill individuals and organizations, we were partnering on advisory projects. Um, but we really, you know, generative AI hit the market. And, you know, Josh said, this is amazing. We need to do something with this. Um, and so we started putting all of that collective wisdom from our team from 25 plus years of research, of insights, of podcasts, of blogs, blog posts, all of these things into an AI engine and saying, well, what can we do with this? And that was really the birth of Galileo, our agent. And so we now have kind of two core products that we've built off of those research and insights. We have our Galileo agent and we have Galileo Learn. And those products are linked. So the Galileo agent essentially is, as I said, it's an AI agent. So an HR professional can go in there and can ask whatever questions they need to help support them. They can enter the prompts to help them to navigate to information. Give me five case studies of financial services organizations that have struggled to recruit early career professionals. And you can pull that out of our content and it can, it'll serve you up exactly as a generative AI tool would, a summary information about it. But you also can flip it to start to do work for you as well. So, for example, write me a job description that's focused on the skills that are most important for data analysts in the finance uh function. And it because we have this tremendous wealth of knowledge, which is based on both our research and insights, but also information that we've partnered with organizations through our trusted content partner program to bring massive data sources on labor markets, on competency and skill models, you know, all of these other pieces that aren't necessarily the research we do ourselves. We're able to find a ton of use cases for that. So, you know, those are the tools is really a learning platform and an AI agent. But at the foundation of all of this is our research and insights, because you could go out to Chat GPT and ask these questions and you're going to get an answer. But it's not necessarily gonna be a great answer. And it's not necessarily gonna be based on trusted content that you can bring to um, you know, to your boss and say, Yeah, I stand behind this. This is a recommendation that I I'm very excited about. Yeah.
SPEAKER_00:I definitely want to do a deep dive in AI, but I'm just gonna close off on the data points. It sounds like you've done quite a lot of surveys, quite a lot of research. It sounds like you've got a lot of data at your fingertips. I just want to ask, what has maybe surprised you the most from learning um everything you've learned from those tools?
SPEAKER_01:I think what's surprised me the most is not necessarily an answer I found in the data so much as the difficulty that we've had kind of often bringing that data to the table. Um, and so I find that in many cases we're still, you know, we're still struggling to say, we're able to build a case that's based on data. We're able to build um these answers uh and really kind of stand behind them based on what the data are telling us. Um, I think that that's as an HR function is maybe a little bit controversial. I think that really mature organizations are absolutely there. They have really robust or um and well-respected data organizations that are a key strategic player in that, in the um, in the in the decision-making process. But I think that for a lot of organizations, that's still a growth point for them, building that comfort, building that data agility, and really making sure that they can um they can advocate for the right answers that they're able to identify.
SPEAKER_00:And so coming back to AI, what do you feel like the HR industry is adopting it at like at a good pace? Um, where do you see the shifts happening over the next five years? This is moving really, really fast. Um I wonder if people are moving at the same pace though, because AI is absolutely learning at a very fast pace, but are people adopting it and are they, I suppose, you know, trusting it at a pace that allows us to get there as well?
SPEAKER_01:In my opinion, I think that the technology has outpaced the human ability to use the technology in many areas, not in every area. And I think what we're seeing is that there are, so first off, there are some low-hanging fruit that just absolutely makes sense. So, for example, if you look at software engineers, that labor market is being completely disrupted by AI. And it makes sense because there's a lot of logic in there. It's something that, you know, is highly trustable. It's very easy to convert that to, you know, we're gonna now use these AI tools and um and reinvent the way that we write code. That is just a perfect fit. Um, and I also think there you have an audience that's very receptive to um to bringing these technologies in. In terms of the HR field, what we're seeing is that there's like a really broad range of adoption. Um, and so it's gonna vary by organization. So, for example, larger, more sophisticated organizations, they have more resources to throw at this. So they have AI task forces, they're able to take a very structured approach, and they have demands from their executive teams and they have sometimes demands from shareholders to show results, and that's gonna create the urgency. But within those organizations, there's still gonna be a range of individual comfort. And I think every organization, even the most mature ones that I talk to are are telling me we've got people who are outpacing everyone else in the organization. They're using AI daily, they're reinventing processes, they're using Copilot Studio to build bespoke agents. We're doing amazing things. And I have people who I'm struggling to get them to open a tool. Um, and so and I always thought that would be like generational, right? Um, but it's not necessarily generational. Um, there are some generational trends, of course, but um, it truly it's it's that's not all that it is. And then I think also across organizations, um, you're gonna see in those smaller and less um less well-resourced organizations, they're maybe not able to bring in those AI tools that are easier to use, right? If you're going to Chat GPT and trying to just hack your own agent together to automate processes and workflows and to reinvent the way work is being done, you have a hard path ahead of you. Versus if you can say, I'm gonna go buy a talent acquisition agent off the shelf and someone's gonna hold my hand and make sure that we are now completely revolutionizing our AI our talent acquisition processes through the use of AI.
SPEAKER_00:Yeah, absolutely. I think ChatGPT, you know, it's a good starting point, but you need to take that um that AI and then obviously structure it in a way that's just gonna work for the way people want to learn, want to absorb um, you know, the the learning capabilities and and the product. Um kind of being being in the hiring space and also, you know, it it sounds like you're you're way ahead with AI. Um, are you finding that people and employers are now, you know, preferring to use AI instead of hiring employees? Or do you see kind of different roles opening up around AI?
SPEAKER_01:Yeah, that's a great question. Um, I don't see, I mean, obviously there's a lot of, you know, press stories around, you know, we're cutting our workforce by X percent, we're cutting our RIT organization, we're cutting our HR organization based on the efficiencies that we found from AI. When I have conversations with folks who are really kind of in the trenches around that, um, I listen, it's happening. And often it's happening where there is a high demand to prove results to shareholders, absolutely. Um, but I think that for the most part, there still is a tremendous value on, you know, getting the right people. You will, you know, if you can hire the right person who's the right fit for your organization, you're always going to want to bring that person in. But what I heard in the second part of your question that I think is really important is how are those roles shifting, right? And so the jobs are beginning to and are going to continue to evolve. And so I think what we're seeing is almost a collapsing of roles. So that instead of having a whole bunch of kind of um subject matter experts, centers of excellence, things like that, we don't need a huge workforce of those. What we need is a very agile um, you know, individual who can work across all of those and do the essentially human part and partner with the business and be the face of this great work that's being done through the AI. And I think it's a a little bit of a cliche I've heard out there, you know, AI is not coming to take your job, but someone who knows how to use AI is coming to take your job. And I think that um, you know, that that's really true. So what we're gonna see is that the the roles I do think will begin to collapse and simplify um with the use of these agents.
SPEAKER_00:Yeah, yeah. I think it's history repeating itself on multiple occasions, but um I do wonder this one's different. I always one that I've got kids and I'm trying to figure out do I teach them technical skills, do I teach them human skills, people skills? What do you think is the valuable skill set of the future? Um, I so I also have kids.
SPEAKER_01:I have one in college, one about to go to college. I think number one is agility. Um that is absolutely key. The the pace of this change is uh intense. And individuals who can keep pace with that change in an area where they're passionate about, whether they are passionate about, you know, technology, about, you know, I mean, listen, some of us are very passionate about human resources, right? But you've got to be agile. Um, and so that is one of those we call them power skills, used to be called soft skills. I think that's really important. There is still a place for technical expertise. Um, so even though perhaps you can use AI to do a lot of coding, there needs to be a human who understands that code. Um, AIs have it, AI has an error rate. How are you catching those errors? How are you accommodating those? How are you implementing new technologies? Because this is not a static discovery that we're gonna now reinvent work and say, we're done. Um, what's gonna happen is we're going to continue to see these tools advance, and organizations are going to have to continue to adjust and adapt to keep pace with this and just absolutely nonstop pace of change.
SPEAKER_00:Yeah, I agree with that. Um coming back again to Galileo, and it sounds like you launched in the wonderful year that was 2019. Um just wondering, you know, with five years now in the business, what were some of the biggest go-to-market campaigns that really moved the needle for your company?
SPEAKER_01:Yeah, that's a great question. So we tend to get some of our biggest go-to-market campaigns are really focused on our research and our insights. That's what people look to us for. So that's been actually just a huge learning for us is the technology is an enabler of the content and the insights. It doesn't replace the content and the insights. So our team of researchers, they are using AI, they're using Galileo on a daily basis. Um, absolutely, but there's humans who are really kind of behind that. And so it doesn't take the place of that. Um, and so for example, we released in uh about two years ago some work on systemic HR. And it's really about how organizations need to evolve their HR models and their HR operating structures and all of the pieces of HR to be more systemic in nature, more interconnected, more data-driven. Um, and that has been really, really powerful for us. Um, I also would say that, you know, Galileo itself has been just really uh absolutely a huge driver for our organization. And the reason for that is, you know, I think two things. The first is Galileo is a democratization tool. So historically, you know, our research, our insights, and all the things that you can do with them were available to people who want to sit down and read a hundred-page PDF. That's a very small group. Um, and so Galileo actually allows users to access that research and insights in a way that meets their purposes. If they just need to dig out that one case example that's going to make a difference and help them prove um, you know, a hypothesis that they have, they can identify that very quickly. So that democratization of information and the ability to very easily share it more broadly across the organization because it's accessible and it's indexed and it's easy to find. I know that sounds like a really low-hanging fruit use case for AI, but that's been very powerful for us. And then the other piece is that, you know, Galileo also is an agent for personalization. So we may write kind of that strategic insight research at the top that says, here's strategically where you should be going. But I was constantly hearing from the organizations we work with, that's great. What do I do next? How do I create an implementation plan? What are the first five things I should do? How do I build the case for this for my CEO so that I can get funding to do what you're recommending here? Um, and historically, you know, we couldn't keep pace with those requests because there is no one size fits all answer to those questions. So by feeding Galileo with the content and expertise that our team has, we can now create much more personalized approaches. Where does it replace a member of our team sitting down with you for an hour and advising and supporting you? No, of course not. But it equips a much broader swath of the organization to have access to those tools and it makes that hour much more powerful because there's so much more that can be done to kind of begin to really personalize the research into how do we operationalize this in my organization?
SPEAKER_00:Yeah. So what I'm hearing is it sounds like you've really optimized your content marketing there because what you're providing is original research. Um, sounds like a lot of templates as well, which you know, HR managers would be searching for. Um, is that right? Is there any other kind of content that you find has worked really well for your target audience? And how did you go about understanding, you know, what their pain points were, what they wanted?
SPEAKER_01:So um learning content, I would say, is the third pillar that I would put there. Um, and so, you know, for us, we are building, and you know, as I mentioned earlier, we started with the Josh Burson Academy. Um, the academy was built on the, you know, a state-of-the-art in 2019 learning platform, but one of our major projects this year has been to move it over to an AI native learning platform that is connected very deeply with the AI agent as well. So, what that means is that our team is now pushing out new um deep dive learning content at a pace that we never could have done previously. And that's really important because I don't think, you know, a lot of people are saying, well, AI gets rid of training. You don't need training. You go to ChatGPT and you ask the question. I believe that there is absolutely a role for structured learning. Um, I believe that most users don't know necessarily when they need structured learning versus the answer to a quick question. They just knew they have a need that's unmet. So if I can walk through what that what that value chain might look like, the user goes to the AI and they're, you know, and says, Hey, I heard someone say the term career pathways in a meeting and I didn't know what that was. So, you know, Galileo, tell me about career pathways. And Galileo will answer the question definitionally. But depending on my role, depending on my need, maybe what I heard in the meeting is, Amy, you're gonna be responsible for implementing career pathways at our organization. In that case, as part of the information that's surfaced by Galileo, I may get recommended a learning course on career pathways that's actually gonna teach me how to implement career pathways within my organization. And I can seamlessly launch into that learning activity. So we think of that as kind of the breakdown between knowledge and learning. And I think that's really important. Um, and then the learning experience in in Galileo Learn is an AI first learning experience. Again, similarly personalized and customized, and a lot of exciting stuff there. So I think that's the the the category of um of content that I would also flag.
SPEAKER_00:Yeah, yeah. It makes sense. I I heard a really interesting um stat once that said, you know, those who out-educate their competitors are the ones that get all the customers. Um, I'm gonna play devil's advocate just for a minute, though. And so for all the organizations out there that are thinking, all right, we need to build, you know, a structured learning content platform that we can attract people with. I mean, what's to stop people just from going to LinkedIn learning or Udemy instead?
SPEAKER_01:I mean, I think that there's absolutely learning content in LinkedIn learning and Udemy. Um, and so uh, you know, I think that those are a great source for general learning content. Um But what we're seeing in the age of AI is that personalization wins every time. And that plays out in two different ways. The first is I want to be able to personalize this learning content to my organization. And listen, I'm using the term structured learning for kind of like that tradition, like there, there's a place for a course, but actually we're seeing, you know, that structure can become incredibly flexible, where one of our clients may come to us and say, I love your course and we'll stick with the example of career pathways. But we actually already have career pathways in finance in our organization. So how do we customize this content so that we can draw on our lessons learned? That ability to do so is really, really seamless because it is an AI native platform. And so that's been a really powerful way for organizations to customize the learning experience and the learning content. Then the other side of that is the personalization on the individual learner side. And so we've done a really good job for years and years and years of saying, you want to learn about something, go click through this training course, watch the videos. And we're delivering the same content to every single person. The ability to personalize that experience through AI is absolutely endless. So maybe I want to learn about career pathways, but rather than, you know, watch videos and page through a course, I think I know some stuff. So I want the platform to create a quiz for me based on all of the learning content that I've that I've consumed previously to test where I am and then only deliver to me the things that I don't know. Or maybe I want the learning platform. I don't really learn very well by watching videos. I learn through having conversations with people. So pop up an AI avatar for me and let me have a conversation with that avatar. And what's really powerful about this is that it's not, wow, we have a whole bunch of different options. It's that all of those options are accessible by the learner. So I the learner doesn't have to say, gosh, I wish I could take that course with an AI avatar, but they didn't put an AI avatar in that one. The learner can say, There's no AI avatar yet. Let me click this button and have what I need for my purposes generated. Maybe I prefer to learn by listening to podcasts. Great. Take this course and turn it into a podcast so I can listen to it on my run this afternoon. That's all very easily possible. Um, and so I think that's really the power that you see through um these AI native platforms. It's not just buying a content library. The content library is key, but it's activated by the technology.
SPEAKER_00:I love that. I think the key word there is personalization because you're right, LinkedIn learning, Udemy, great. But again, I think the word you used there was generic, which true. There's there's no personalization, so to say. I love the idea of turning a course into a podcast because that would be my way of learning. And I know I've experimented with a few AIs where I've plugged in a guide and I've said, turn this into a podcast that I can just listen to on the go. Because there's no way I'm gonna sit there and read, you know, 10 pages of a guide. There's just no time for that. Um, but what are some of the key personalization that you put into these courses? Like, you know, obviously one of them being turn it into this bit of content that you know I want to either listen to or watch or read, depending on my learning style. Another one I think might be, you know, based off learning styles. So some people are tactile learners, others are visual learners. Um, what's other personalization that you apply to that?
SPEAKER_01:Yeah, so what's really cool is that it this is all powered by an AI tutor that has an open-ended box there. So you could ask for whatever you want. Um, create a graphic for me that should, I want to see an infographic that describes the content in this course. Um, create a quiz for me. Um, what are some of the other ones that we've seen that I like? Oh, um, can you give me a specific example? Because this is hooked up to there's the information in the course, but it's hooked up to all of that content that we've created. So if I say, Oh, I'm really interested in the concept here, can you give me a specific example of what this looks like? Um, it could be talk to me about this. So that's really bring up that AI avatar. Um, you know, there's just, I mean, the possibilities are endless. Um, the AI Tutor prompts the user with contextual um suggestions. So as you launch the AI tutor, it might say, because you're at the beginning of the course, maybe you want to take a quiz to see how well you know this, or maybe you want to generate a summary of the course to make sure that it's aligned with what you want to do. But as you go deeper and deeper into the learning content, those contextual suggestions from your AI tutor will shift and change. And they're always accompanied by that free form text box that is just it's that LLM text box that's going to let you ask for whatever you would like. The other thing that um that we're really excited about is the opportunity to create um ultra-personalized um learning pathways. So not just saying I'm within a course and able to customize that, but maybe I'm saying, hey, I'm on a, so I could say I have a six-month journey. I've been told by my boss that if I can really beef up these skills over the next six months, I'll be up for promotion. And I'm really excited about diving deep into these skills. Can you create a journey for me? And, you know, and the system may say, well, you know, how many um, you know, uh, how many courses have you already taken? What experiences do you already have? And so creating that customized opportunity. Um, and I will say we're talking a lot about the platform. I want to be transparent. I didn't create the platform. Um, we partnered with an organization called Sana out of uh Stockholm, Sweden. Their platform actually powers a lot of that innovation. And what we found is that again, that combination of the platform plus the content has been really, really magical for us.
SPEAKER_00:Yeah, absolutely. It sounds exciting. I can think of a few really smart technical people that have had to sit like really difficult Microsoft and Cisco exams. And even though they know everything, you know, they just they're really smart. But when they sit that exam, it just goes wrong. Like they just can't do it, they can't get through that. Um, and studying for it, you know, I've I've seen kind of the videos that they have to watch, they're not that terribly exciting. So having an option where you can learn in your own style in a way that's actually effective is very exciting. I think a lot of people will benefit from that. Um, coming back to go-to-market strategies again and and scaling the business, you know, aside from this wonderful personalization and content, what channels have worked really well for you? You know, have you um tried partnerships, for example? Uh any specific kind of social channels that have worked better? Just for anyone in a SaaS organization just wondering where to begin with their go-to-market strategies, what are some recommendations?
SPEAKER_01:Yeah, so we have um we have we have two ways that we go to market. We have both direct-to-consumer channels and we have business to business channels. And that's been really powerful for us. We were always business to business um for years and years and years. Um and all of us here, you know, many of us have worked together in different iterations in our history, and all of us had that really strong business-to-business experience. And so that's something that's been very exciting as we talk about kind of that democratizing power of the technology, is that now you don't have to work at a great big company that can, you know, that is chosen to bring us in and that has the you know the funding to do that. You could say, I want to go and I want to make this available to myself for my own professional development to help support me in the work that I'm doing. And that's available and accessible to users. So, you know, in terms of the channels and the go-to-market strategies that have worked really well for us, you know, number one, having that hybrid model where we can say, can how can we support organizations who say we want to transform the way that HR is leveraging AI to modernize their and transform their organization? Yes, we can work with you to help you to build that strategy, to give you the tools that will build that strategy to partner with you in that way. But then also on the direct to consumer side, you know, having that dual availability has been really, really powerful for us. I think another thing that I would say is particularly for organizations that are in the um in the HR space, don't sleep on the mid-market. Um, because for those of us who do come from the Deloits of the world, we often do focus on the larger enterprises. And yeah, there's absolutely huge opportunity there. Um, but I think there's actually much greater opportunity for impact in small to mid-sized organizations because they often are starved for those HR resources. And so we found it's been incredibly powerful for us to help amplify what is often an undersized, under-resourced team in these smaller organizations. Um, so I think that's been very powerful. Um, you know, in terms of go-to-market strategy and the direct-to-consumer side, that's been a lot of fun for us because again, it's something we haven't been able to do in the past. And now we're building social media ads and we're able to, you know, kind of think about how do you build um UGC type of ads and things like that. That's fun and also a little scary. Um, but that's been really um, really powerful for us as well, is really just saying how do we break through all of the kind of um the the the influencer noise that's out there um and help us to do that. I think the final thing I'll say you mentioned partnerships. And I don't know if this is kind of where you're going with this, but I I I want to kind of talk on, talk, touch on that a little bit because I think for anyone who's starting up in the in the AI space, this is like a really, from my perspective, a really important point. Right now, we are in an era of agents, agents everywhere. There are so many agents and we are battling for mind space and we are battling for the digital employee experience. And so you really need to think about how do, if you are building an agentic solution for business, you need to think about how is that gonna fit into the mindset of your workers. Because if you're gonna say, you're gonna have to remember every time you do task X, you need to remember to come to me and launch my product and use my product for task X, you've got to be able to integrate that experience. And so we've worked very closely with other technology partners that serve the HR space to say, how can we integrate the Galileo experience so that users don't have to say, I forgot to go to Galileo. So, for example, working with HCMs like High Bob, which um serves the mid-market space, a really fantastic disruptor in that space, um, you know, integrating with uh with them, integrating with ServiceNow, where there's a lot of um of the actual day-to-day work being done by managers and by HR professionals, um, that creates a front end that um gives easy access to Galileo's um benefits.
SPEAKER_00:Yeah, that's a really interesting point, actually, because I think a lot of people, you know, in organizations are probably wondering how do we build our own AI capabilities and agents, but really it makes sense to go and partner with someone who's already done it and just use theirs and just you know, it's gonna get there much quicker, right?
unknown:Yeah.
SPEAKER_01:Well, I think it depends on the organization. A lot of organizations I talk to are saying, yeah, no, we're gonna build our own GPT. Um, but there, what they're looking for is I we want, you know, we want an agent-to-agent transaction so that when a question is asked that is best served by Galileo, our GPT is gonna call Galileo and bring that response in. So we're gonna build that consolidated front end. Some are saying, you know what, co-pilot. That's our consolidated front end. Because guess what? They've already got all of our documents anyway. Um, and so it could be a build strategy for some organizations, but the key is the interoperability and the integrations. As long as you're structuring your solution so that you can flexibly meet the preferences of um of the organizations where they where they really want to centralize that. Um, we don't know who that winner of everybody's eyes is going to be just yet.
SPEAKER_00:Yes. And coming back to go to market, it sounds like diversifying has been a you know a good strategy for you because you've you've kind of touched on the enterprise level clients, but also mid-market. But then you're also doing B2B and B2C. I just want to ask one, close off on with one question on that. And that's have you found that the messaging between B2B and B2C is different? Because it is the same human at the end of the day. They do have the same buying behaviors. Do you find that you have to do completely different messaging to those two and campaigns, or is it the same things kind of work? There are differences.
SPEAKER_01:I would say it's not completely different. Our value proposition remains the same, our brand remains the same, but the messaging does need to change because often the B2C consumer is I am spending my own money. Um, so I need to understand how is this going to help me as an individual be more efficient, be more effective, um, apply AI to apply, you know, AI to the work that I'm doing, learn the skills that I need. Whereas at the B2C level, we're really looking at how, you know, I have to be able to justify this to whomever is my budget approver. So I need to be able to say, not how is this gonna help me, but you know, how is how is building this skill base, transforming these operational processes, whatever it is, how is that gonna move the organization forward? So it's a different kind of ROI conversation. Um, and so we need to be able to show um different levels of value depending on um who's ultimately paying the bill.
SPEAKER_00:Yeah, for sure. Um closing the podcast more on a personal reflection type note. Um you touched on the future of work there for a second. Uh I remember that being such an overused bit of content five years ago, like future of work, future of work. Um, but what excites you about the future of work and technology now that you know with AI around?
SPEAKER_01:I think everything excites me about this because I think that AI takes so I, you know, I'm the parent of kids who are on the cusp of entering the workforce. The world that they are entering is so different. And I think about the beginning of my career and the amount of time that was spent kind of very slowly building skills, very slowly, kind of, you know, working my way through processes that often didn't feel incredibly human because you really, you know, when when you work in in some fields, you're just throwing humans at the work. We don't have to just throw humans at the work anymore. We have an opportunity to really optimize the the work experience for this next generation of workers where we can say, you know, you get to do the things that light you up. You don't have to, you know, pay your dues by doing 20 years of just churning through SPSS analysis and grabbing your output and writing syntax and whatever it is. These tools, and yeah, some of these things may have been automatable 20 years ago, but not every organization had the resources to do so. That democratization factor powered with the transformative nature of AI is going to completely change and accelerate career paths, which is where agility comes in again. I just think that we're setting up this next generation of workers to have such incredibly exciting careers. I am, as a mom and as someone who focuses on, you know, how we can make work better for people, I am really, really excited about that.
SPEAKER_00:Yeah. Yeah. I think a lot of parents are scared though. They're thinking, like, oh no, what we AI around, what kind of jobs are they gonna have? But um, what advice are you giving your children?
SPEAKER_01:So, number one, uh, absolutely down to the fundamentals. So you still need to learn how to keep your calendar up to date in Outlook to respond to emails in a timely manner. I mean, these are skills that I think like you can't lose that. AI, I mean, maybe, maybe Galileo will start responding to my emails, but probably not. You know, and so I think absolutely focusing on those fundamentals um is critical. And then, you know, don't be afraid of the technology. I have one child who's a freshman in in college who's who's choosing to go into an artistic field, and he says, AI can never replace art. And no, AI can't replace art, but you're gonna need to learn to operate in an environment where AI is applied to art and figure out how to work in this environment and create art that you can stand behind using these tools. My other son, all in on AI, all in on technology. Um, and so I think, you know, for him, he's, you know, they the they are both gonna have to a little bit meet in the middle. My my son, who's all in on technology, needs to keep the human in there and keep those fundamentals there. My son, who says, nope, I this isn't, you know, it's it's not art, is gonna need to learn to be a little bit more flexible in his thinking and um and really make sure that he's able to really identify what makes it art and where you can make that art better through the use of of the new technologies and tools. Yeah.
SPEAKER_00:It sounds like you're gonna have a really interesting journey ahead of you to see where each one goes and and and you know, where where the I guess where things go in the end. And I don't know, who does better? I'm very interested to see that as well. Amy, my last question for you. It's a bit of a tradition on this podcast, is if you could go back in time and give yourself one bit of advice, it could be at any point in the past. Where would you go and what advice would that be? Wow, that's a really good question.
SPEAKER_01:I think that for a long time I fought technology. Um, because I started in a very analytical world. I used a lot of technology, um, but I had a tendency to kind of brute force through things because it was really, really satisfying to get, you know, to get through and be like, well, now I understand it because I've done it, I've touched every part of it. That is a very um it it really kind of was limiting sometimes because it limited my capacity, it limited my productivity, and it also kept me from opening my eyes to not just how do I do things faster, but how do I transform? Maybe I can do things I couldn't do previously. It took me a long time to get to that point. Um, and I think now, you know, given the environment that we're in, I, you know, I'm there, but had I gotten there earlier, I wonder what other kind of opportunities I might have been able to take advantage of by saying, I'm gonna, I'm gonna jump in with both feet to um, you know, to do something in a in a new and exciting way versus being like, this is this is the way that just feels really good.
SPEAKER_00:I love that. Thank you. Thanks so much for being on the show. I think we've learned a lot about the the different kinds of learning content, but we can all go away and apply. And I'll definitely be checking Galileo out. Thanks, Damien. Wonderful. Thank you so much. It was a pleasure to chat today.
