Mariia:

[0:01] 80% of AI pilots fail because of the people side, not the technology. So when skills are invisible, three things happen. So you invest in training that doesn't match actual gaps. Your best people leave because nobody sees their growth. or the ones that are really great at AI adoption, they are not supported. And AI transformation stalls because you're deploying tools to teams that aren't ready. And there are many stories nowadays when some companies rushed with AI transformation and they replaced and automated even departments like customer support or development teams and it backfired. So either the customer didn't like that, or the AI agent crushed the code and exposed some very sensitive information. And that's really sad. So AI isn't the threat. The threat is flying blind, while the biggest transformation in a generation, I should say, reshapes your entire workforce. And your skills is this intelligence layer that helps you to navigate this complexity.

Debbie:

[1:26] My guest today has spent her career at the intersection of education, technology, and people, turning a real workplace frustration into a company. Mariia Potupchik spent over four years at Skyeng, one of Europe's largest online English platforms, rising from teacher to head of media production. She then stepped in as Chief Product Officer at Business School Synergy, where she scaled active users five-fold in just six months. She's also a fellow Stanford GSB alum, and today she's the founder of YourSkills, an AI-powered platform built to give professionals skill visibility and help businesses unlock the full potential of hybrid teams. She's building for the future of work and I'm excited to have her here. Maria, welcome to Skin in the Gain.

Mariia:

[2:22] Hi, Debbie. Really happy to be here, and thank you for inviting me.

Debbie:

[2:26] You spent years at the helm of regional giants like Skyeng, Europe's largest online English school, and Geekbrains, which serves millions of users. In environments where you're processing tens of thousands of tasks a month, users can easily become just numbers on a dashboard. Was there a specific moment at that massive scale when you realized that big data was actually making it harder to see the individual person?

Mariia:

[2:58] Frankly speaking, at Skyeng, we hit eight and a half million users, 10 of thousands of lessons every single month. And I was sitting in a product review meeting. I had dashboards everywhere, like retention curves, conversion funnels, NPS scores. Everything looked healthy. But then I went on a customer support call. A woman in a small town learning English to get a remote job so she could support her disabled child. She's been with us for six months. On the dashboard, she was a yellow retention risk and she missed already a few lessons. In reality, her internet was dropping down, so she wasn't at risk of leaving. She was our most dedicated learner. And that moment broke something for me. We have built this incredible data machine that told us everything about behaviour in aggregate and nothing about why individuals made their choices. We were optimizing for averages and averages raise people. That tension between scale and individual is exactly why I'm solving now with your skills in workforce context.

Debbie:

[4:21] I like what you shared, Mariua. It's like the data is the what, but the insight is the why.

Debbie:

[4:28] And that is clearly articulated in your example. Moving from those massive established infrastructures in Eastern Europe to launching your skills from zero in London is a total shift. How has managing those high volume learning machines influenced how you're architecting your own platform?

Mariia:

[4:48] There are, I should say, three main lessons that transfer directly first, Starting with individual, not organization. Because we started as a startup as well, and then we scaled and grew rapidly, we took into consideration the problem and the goals of the individual. And then kind of understood how we can diversify to other persona. But we started with individual, not organization. So every learning path was personalized. Even the gamification was focused on achieving the goal of individual.

Mariia:

[5:32] At their own pace, through the content they liked. So at your skills, every employee gets their own AI passport, a living map of what they can actually do, not just what their job title says on LinkedIn. Second is behavioural signals, and behavioural signals beat self-reporting. So, for example, at Skyeng, we didn't ask students, Are you engaged? Do you like our lessons? We measured it, actually. And we made the decision how to improve based on this. And your skills does the same for skills. So we read the signals from different platforms like GitHub, Jira, and we analyse what people actually do, not what they claim they can do on CVs, surveys, assessments, etc. And the third, scale demands automation. But automation has to serve insight. So processing thousands of data points isn't about efficiency for its own sake, it's about surfacing what humans simply can't see at that volume. Let's say if you have 50 people, you're more or less aware who can do what. But when you have 300 that becomes really difficult.

Debbie:

[6:58] I can imagine. Your skills focuses on workforce visibility, right? So making sure that skills aren't hidden. So what was the specific frustration that you've seen during your leadership years in big companies that convinced you this problem was worth a multi-year commitment to solve?

Mariia:

[7:19] It started with my own experience, so I kind of lived it. I managed a team of over 100 people, and I knew more or less who can do what, who is brilliant at execution, who can handle ambiguity, who was quite an innovator I can rely on. But the moment I moved to another organization or a different division, all that knowledge vanished and I had to start over again. It lived in my head, but not in any system or the system that existed wasn't really good or up to date. So I also care deeply about underrepresented professionals who, for whatever reasons, cannot break into the workforce.

Mariia:

[8:11] And I started my career as a teacher. I even had my own offline school. That classroom experience taught me what it feels like when people are seen versus when they're just a number. So this skill-based approach is a merit-based approach. So talent is everywhere, but unfortunately, opportunity is not. When I started doing customer discovery, I heard the same frustration from every enterprise leader I spoke to nobody could actually see what the people were capable of behind their titles that's where i knew that wasn't just my problem it was systemic worth billions and worth building for yeah for.

Debbie:

[9:00] Sure I think that's a lot of pain point also not just for companies but for employees as well now when you left the big companies to found YourSkills in 2023, what was the specific trade-off you were weighing at the time and what did you personally have to put on the line to make that happen?

Mariia:

[9:20] I traded certainty for conviction. I had senior role, leadership role. I had stable income. I had clear trajectory. On paper, everything was working. Somehow I wasn't satisfied.

Mariia:

[9:37] I already started teaching very early during my education at the university. I founded my own school and scaled it. I even transitioned and scaled different tech platforms, and I understood throughout my journey that each transition taught me that growth happens at the urge of discomfort. And each time when I felt discomforted, that for me was kind of upgrade, and I felt also energized, not in the center of safety. And Stanford crystallized this. Being surrounded by people who had made far bigger leaps that I did gave me permission to take mine. But honestly, the deciding factor was my kids. I am a single mom with two teenagers. And I asked myself, what do I want them to learn from watching me? Being passionate being bold taking risks never giving up I believe these things you cannot teach by reading a book you don't learn this from a book you learn by watching someone doing it and that's actually what I want them to learn from me and to remember.

Debbie:

[11:03] Love that. We often talk about the wins, but entrepreneurship, as you said, is all about being uncomfortable about growth, and it also involves significant setbacks. Is there a specific failure from your past ventures, perhaps during your time in Johnny Hodler or Synergy chapters, that genuinely hurt? And what did it teach you about your own limits as a leader?

Mariia:

[11:27] Yes, I had some. And interestingly, when I'm invited to speak, especially for female events.

Mariia:

[11:37] Usually you have a slide where you have titles and, you know, everything that you have accomplished. And sometimes I like to start saying like I constantly fail I'm very good at failing and in one of my early ventures I made this classic founder mistake trying to do everything myself I was like the strategist the marketing manager the developer the product manager I thought that if I'm indispensable, that it's equal that I'm very effective. And I wasn't. And the venture actually struggled, not because the idea was bad, but because I hadn't built the skills that I needed to navigate all the complexity. And I had also the team with me that I couldn't really put to the work, and that could help me. Yeah. So what it taught me is something I now preach through your skills. So your gaps are not your weaknesses, they are information to act on. So the moment you see clearly, you understand where the gaps you have, you can build around them. That's literally what our platform does, makes invisible skill gaps visible so leaders can act on them instead of guesswork. Okay.

Debbie:

[13:00] You're very much into the Stanford LEAD ecosystem. What was the long-held belief about yourself that you had to unlearn to become the founder that you are today?

Mariia:

[13:11] I had to unlearn that I needed to know everything before I could lead. I think that started from my childhood when everyone corrects you, like, don't jump, you will fall, don't do that, or this happens to you. Then the educational culture in Europe educational culture is like expertise equals authority so you don't speak until you are the smartest person in the room and Stanford broke that i was surrounded by founders by leaders who admitted what they didn't know publicly confidently and they felt okay about that. And I felt like, how could that be? And then went and figured it out in real time. So the best leaders weren't experts in every domain. They were experts in learning fast and building teams that filled their gaps. So that's a great shift from I need to have all the answers to I need to ask better questions, changed everything. And it's why your skills works the way it does. So the platform doesn't judge what you lack, it eliminates what you have and shows you how you can develop it and the path forward.

Debbie:

[14:32] I love what you said about leaders don't need to know all the answers, but have the curiosity to ask the right questions. I think that's valuable. Currently, you're running a lean startup yourself while also mentoring founders at the Stanford Lead Incubator and Startup Accelerator, or LISA.

Debbie:

[14:50] What specific AI tools are you using to operate differently? And what's that teaching you about the future of work that you wouldn't have learned inside a bigger company?

Mariia:

[15:03] This is actually something I leave every single day. So our core team is only five people. Three people are very tech and very AI handy, I should say. And we're building an enterprise AI platform with the same headcount as a coffee show. And that's only possible because of AI. I use AI for everything, drafting pitch decks, preparing conference talks, customer discovery analysis.

Mariia:

[15:35] A market analysis, competitive research, even building prototype, interactive prototypes before we write a single line of production code. And of course, coding. Coding is no-brainer how you can use AI. So what we use are Gemini, Notebook LM, Code, Cowork is my partner in crime. So sometimes it feels like I have been working with a marketing manager, analyst, with a designer, and it's just been, I've been talking to Claude for a few hours. And yeah so I just recently spoke for example at Stanford Me2We conference and my entire speech and deck preparation was ai assisted and here is the insight that's at the core of your skills it's not only about whether you use ai it's about how you use ai the skill isn't just prompting It's knowing what to ask, how to evaluate the output, and when to override it. That's the AI readiness gap we measure. And I'm believing proof that a team of five with the right AI skills can compete with a team of 50.

Debbie:

[17:02] Remarkable to hear that you're able to do so much with just five team member. Wow. Let's break it down to listeners who want to know more about your skills. Like how can they tap into the enormous hidden skills that you can uncover through that platform? What do they need to learn? What's the benefit for them?

Mariia:

[17:27] Yes, from the platform, we start on the personal level. We provide AI readiness scan that is very easy and gives you an understanding

Mariia:

[17:38] where you are in the market in terms of your AI skills. And then you can get your personalized skills map. So it analyses different tools that you use and provides you a map and also guidance how you can develop your skills considering your background and also considering the market situation because some skills become more valuable and others you can adapt to the market as well. So it also focuses on your career, whether it can be your portfolio career, because sometimes leaders have a full-time job, but they are considering, let's say.

Mariia:

[18:22] Starting their own venture or having some pet project or even consulting. It's now a very common thing. So navigating the complexities of such careers, we are helping to guide by showing what skills you have and how you can develop these AI skills. And on the company's level, we provide the same visual, but for employees, right? So we show what is the adoption scale for the company and what should they do in order to reach their goals. And the valuable thing is it's dynamic so there are a lot of systems of record where you track where when people entered your company but there are no great solutions that kind of update what people can do throughout their journey at the company yeah and in our case it doesn't stop Whether you're leaving or pivoting your career, your skills are just developing and we are helping you, guiding.

Debbie:

[19:31] You know, most talent platforms are essentially digital filing cabinets for static resumes or LinkedIn profiles. Your skills argues that the most valuable data is dynamic and invisible, as what I hear from you. Can you share a specific example of a hidden skill your platform has uncovered that a traditional manager would have missed and what the ROI of that discovery looked like?

Mariia:

[19:58] Of course. So here is one from our AI readiness scan that I mentioned, which I run live through my presentation, AI for Human Potential, during Me2We conference at Stanford. It's a 60-second diagnostic that classifies people into four levels, explorer, practitioner, integrator, or orchestrator. What we found was that people that called themselves beginners with AI are often practitioners or even integrators, but because they didn't know that using AI for the things they used, they considered themselves that they don't know anything about AI. They're not developing their skills, but really they are. Actually, we learned that based on their behavior. They are using AI tools daily, like, say, summarizing, brainstorming, debugging their code, but they don't think of it as a skill because nobody ever named it. In a traditional manager view, that person is not technical. In our platform's view, they are an asset who just needs the right opportunity and a small nudge to leverage. And the ROI that everyone is looking for and talking about, especially for enterprise.

Mariia:

[21:27] So you've just identified AI champion who costs nothing to develop and can pull their entire team forward. So multiply that by hundreds of employees, and you're looking at millions in saved, training spent, and accelerated adoption. So that's a good insight I learned.

Debbie:

[21:51] Lately, when we talk about AI in the workplace, the conversation usually defaults to job displacement and anxiety. You know, people fear about losing their job because of AI.

Debbie:

[22:02] But your research suggests that the real risk might actually be something else. Can you share that insight, the idea that the biggest danger isn't AI replacing people, but companies not being able to see what skills their team actually have.

Mariia:

[22:20] Yeah, everyone is talking about AI will take your job and all the headlines make you more stressed. But the data from our enterprise conversation tells a very different story. What's actually happening is that companies are investing millions in AI transformation. So they want to leverage AI, so they have new tools, new workflows, new roles, but they have zero visibility into which employees are ready for this shift and who are not ready or who are silently resisting. For example, what I learned from Cisco, they told that a lot of companies are already monitoring people, adoption, but they have no framework to act on what they see. So, for example, 80% of AI pilots fail because...

Mariia:

[23:23] Of the people side, not the technology. So when skills are invisible, three things happen. So you invest in training that doesn't match actual gaps. Your best people leave because nobody see their growth or the one that are really great at AI adoption, they are not supported. And AI transformation stalls because you're deploying tools to teams that aren't ready. And there are many stories nowadays when some companies rushed with AI transformation and they replaced and automated even departments like customer support or development teams and it backfired. So either the customer didn't like that or the AI agent crushed the code and expose some very sensitive information. And that's really sad. So AI isn't the threat. The threat is flying blind while the biggest transformation in a generation, I should say, reshapes your entire workforce. And your skills is this intelligence layer that helps you to navigate this complexity.

Debbie:

[24:42] The preparedness of the people in terms of managing the AI transformation. is important. If you look at the data coming out of your skills right now,

Debbie:

[24:53] what would you say is the single biggest blind spot companies have when it comes to identifying talent? So if we solve that one issue, how does the future work look different for both the employer and the employee?

Mariia:

[25:08] Great question. There are a lot of conversations about skills-based approach, but still, they're looking at job titles instead of capabilities. And every HR system in the world organizes people by role, by department, and seniority. That has been for many years, and the system is quite outdated.

Mariia:

[25:38] But that tells you nothing about what someone can actually do. For example, let's take two senior product managers at the same company. They can have completely different skill profiles. One might be brilliant at data analysis, AI integration. The other might be excellent at stakeholder management and design thinking. Both are senior PMs. Both are invisible in different way. So if we solve this one issue, if we make skills visible at the individual level in real time, the future of work changes fundamentally. For employers, you stop wasting millions on mismatched training, you retain your best people that are motivated and feel valued, especially with the Gen Z generation that value this specifically, and you retain your best people because they feel seen and your AI transformation actually sticks. For employees your career stops being defined by your last job title and starts being defined by what you can actually contribute that's a world where talent wins not credentials and this is something I’m really excited about i am.

Debbie:

[27:02] As well if we can just do away with the roles and the titles and really look at hidden skills, bringing them to the surface and see the full potential of an individual and employee. And as you said, it also stops the company from wasting unnecessary resources on a one-size-fits-all training.

Mariia:

[27:24] Yeah, and it brings more, you know, equal opportunities. Like recently, Elon Musk said, it doesn't matter what your gender, background, religion is. What matter is how good you are at your job and what your skills are. And that kind of relates to what I'm building.

Debbie:

[27:46] Mariia, we always like to leave our audience with something they can use tomorrow. Given everything we've discussed today about hidden skills, AI, and workforce visibility, What is the one diagnostic question a leader should ask themselves today to get their organization AI ready?

Mariia:

[28:04] I want to leave every leader listening with one question. Do you really know which of your people are already using AI effectively and which one are pretending to? Because here is what I can tell you from all the enterprise discovery conversation. Every leader at, let's say, Google, Microsoft, Big3, Cisco, SAP, and many others admit they don't actually know. They have adoption metrics, who logged into Copilot, how many hours they spent using ChatGPT, but they have zero insight into skills quality. So logging in is not the same as being AI ready. So if you can't answer that question, you're making every AI investment decision blind. You're training people who don't need it and ignoring the one that really can benefit from it. So my real challenge, stop measuring adoption and start measuring readiness. And that's the question I think is worth asking.

Debbie:

[29:16] Stop measuring adoption, but start measuring readiness. I think that's very insightful. Mariia, thank you so much, not just for the insights on AI and workforce visibility, but for the depth you brought to this conversation.

Mariia:

[29:30] Yes, thank you so much, Debbie. I'm really excited and I hope that would be really valuable. And, you know, because I'm all in, I think this is very important to consider nowadays, especially with AI scaling so fast and pushing people to catch up. So thank you for these really insightful questions and happy, happy to stay connected.

Debbie:

[29:56] It your skills is a very timely tool especially nowadays with our ai driven world to our listeners if you enjoy these conversations take a moment to rate and share the podcast it helps us to grow this community of leaders I’m Debbie Go thanks for listening and keep putting your skin in the game