The Pretzel Theory of Innovation, with Selina Lehmann, Mahle

In this episode of The Innovation Brief Podcast, host Gabi Matic speaks with Selina Lehmann, Innovation Manager at Mahle and lead of the company's venture clienting programme, about what it really takes to run idea management at scale and what her own academic research reveals about where AI genuinely helps, and where it doesn't.

Selina shares how five years managing global ideation platforms led her into doctoral research on AI and innovation, and how she now combines hands-on practice with published findings on what actually makes ideation systems work.

The episode also explores:

• Why innovation is fundamentally people business, and what that means for how ideas should be evaluated and rewarded
• What venture clienting is, and how Mahle uses it to bring external startup innovation into a large industrial organisation
• The real misunderstandings between corporates and startups, on both sides
• The "content formulation pain", the universal bottleneck in ideation systems that has little to do with creativity
• The five roles AI can play inside an ideation system: inspirer, stylist, matchmaker, analyst, and organiser
• How to sequence AI adoption, starting with people, not tools
• Two possible futures for human creativity and AI inside large organisations
• Why visible recognition often motivates more than financial reward
• The underrecognised history of women in innovation, from Clara Ritter to today

At its core, this conversation is about what actually drives good ideas to the surface, and what gets in the way before AI ever enters the picture.

So, as organisations rush to adopt AI in their innovation processes: are we solving the right problems, or just generating more ideas faster?

Follow Selina: linkedin.com/in/selina-lehmann
Innovation Manager, Venture Clienting at Mahle | Doctoral Researcher, University of Hohenheim

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Transcript

SPEAKER_00 0:03

Welcome to the Innovation Brief, the podcast where we have real conversations with leaders driving meaningful change across diverse sectors. I'm Gabriela Matic, and today I'm joined by a guest who brings a rare combination of hands-on corporate innovation experience and rigorous academic research. Selina is innovation manager at MALE, one of the world's leading automotive suppliers, where she leads the venture clienting program, building bridges between startups and the corporate world to accelerate the new product development and transform internal processes. She spent over five years running idea management across the global sites before stepping into her current role. And she's also an adjunct lecturer and published researcher whose work sits at the intersection of ideation systems and artificial intelligence. She holds a doctorate from the University of Hohenheim in Stuttgart, where her research focuses on how AI can transform the way companies generate, develop, and evaluate ideas. And her work has recently been published in the Journal of Product Innovation Management. So, whether you're learning about innovation or leading an innovation function, managing a venture clienting program, or just thinking about how AI is reshaping the way organizations unlock creativity, this conversation will give you a practical insight grounded in both experience and evidence. Selina, welcome to the podcast.

SPEAKER_01 1:22

Thank you for reminding me. It's actually a pleasure to be here. Or should I say hallo and guten Tag, since I know you also speak German very well.

SPEAKER_00 1:32

Yeah, auf jeden Fall guten Tag willkommen. We don't want our German-speaking listeners to feel excluded, but we will stick to English mostly, so we open up to the wider audience. But um if we need to translate anything and any words, I'm very happy to do so. But well, let's let's start um with you. Tell us a little bit about yourself and your work in Germany and at Male and how you found your way into innovation management.

SPEAKER_01 1:57

So I'm Selina, and I would say I'm very passionate about understanding people and working with people, because for me that is actually what innovation is about. Innovation is people business. And I'm also very curious about new technologies and research, and especially research when it comes to creativity and AI. And my way into innovation management was actually quite accidental because, like many students, I did not know what to study, and actually, I did end up studying marketing, and my interest in innovation developed simply by trying out different jobs as a student. And after my studies, I started working as idea manager at Male, an international automotive supplier, and I was responsible for their ideation platform, so platform where employees could submit ideas to improve workflows but also products. And my role was to make sure that the ideas got evaluated, implemented, and also to make sure that people actually stayed motivated. And I did also implement this platform at different company sites. And during that time, I always quite often heard the same wording from evaluators. They always said, Oh boy, the quality of ideas is not good enough. And that actually made me curious. And I started asking myself, how could we improve idea quality? And this question then led me to start a part-time doctoral degree. And through that I found another passion, namely research. And today I work in venture clienting. That means I bring ideas from outside the company into organization or into my organization I'm currently employed, namely MALE. And I work with internal stakeholders to understand their challenges and I connect them with startups. And that's simply what I'm doing today.

SPEAKER_00 4:10

Amazing. Yes, thank you so much for that introduction. We end up, well, not always in research, but oftentimes in a space where we, you know, um try to find out more and try to find answers to some of those pressing questions. If you were to describe your day-to-day to someone right now leading the venture clienting program, what does that look like? And I'm also curious, how do you keep that researcher in you and the practitioner talking to each other? Do they interact? Do they inform what you're working with day-to-day?

SPEAKER_01 4:49

Yeah, I would say right now, my day-to-day is a balance between very practical innovation work and research. So in venture clienting, a big part of my work is collecting and understanding the pain points of our employees. So we run workshops or we talk to different departments and we try to identify where people actually face challenges in their daily work. So I see our team more as a service entity in the organization, and we help employees solve problems with startup solutions. And those can be very, very diverse pain points. It can be a software solution, but also a coding solution. And this is actually what's so interesting about the job: those diverse pain points and those insights into various different departments of the company. And my research work is a little bit different. I would describe it more as a side passion. So there's this large community of idea managers in Germany. And I really, really enjoy sharing research insights with them. For example, on how feedback can be structured in a way that it leads to better ideas. So for me, actually combining this practical innovation work with research is something I would say it's my Iki, in case you know this uh Japanese principle. It's it's my true passion. Yeah.

SPEAKER_00 6:24

Nice. Yeah, I love that. I I'll I'll have a few more questions around the research side, but let's kind of go step by step on that front. And I'd also love to hear from you, you know, through all these years, you've been inside a large industrial company in automotive like Male. What does innovation actually look like from the inside? You mentioned working with startups, you mentioned you know internal ideas, but often we have this outside perception or people have an outside perception of what innovation in a big corporate might look like. What's reality for you day-to-day?

SPEAKER_01 6:55

So I think there the perspectives uh differ quite a bit. So if you start from the outside perspective, what we as end customers usually see. What do we see? We see a final product, we see the outcome. So let's take a very simple example. Here in Germany, many people love eating a pretzel, either for breakfast, for lunch, whatever. So as a customer. In Austria too, we love pretzels everywhere. So as a customer, I just see the pretzel. So I expect it to be fresh, crunchy, and tasty, of course. But if you look at that from the inside, like from the bakery's perspective, it's a completely different story. Suddenly it's about sourcing the right ingredients, experimenting with the recipe, finding the perfect baking time to get this right texture. And then there might be also regulations. What ingredients you are allowed to use to actually call it a proper pretzel. And then, of course, you can start innovating by adding something on top of the pretzel, like cheese or making it sweet. And that's exactly how innovation also works in a large industrial company. From the outside, we and customers only see the final solution. But from the inside, you see the complexity behind it, the experimentation, the iterations, the constraints, regulations, and also this collaboration it needs to get there in the end.

SPEAKER_00 8:37

Yeah, that makes a lot of sense. And I think collaboration is a key, right? Internally as well as with partners. I'm fascinated by the concept of idea management. So when we spoke first, I was like, that's so cool. Because I think there's lots of companies that claim they do it, but only few that actually do it well. What are some of the biggest surprises you've encountered when you started running idea management at scale, particularly?

SPEAKER_01 9:03

I think what surprised me most is that even companies that claim to have very matrix systems, they actually face the same problems. So employees might feel that their ideas are not taken seriously or that the evaluation time is too long, and those evaluators often very they very strongly struggle with workload or high-quality ideas. And I'm still quite active in networks for idea managers, and that showed me you are not alone, actually. Because we companies or idea managers, we have all the same problem: problem with speed, transparency, fairness. And personally, sometimes I think doing it well is also a matter of communication, because you can say, oh no, oh boy, I only have 50% of my ideas that are getting implemented. Or you can say, Wow, actually, we have a 50% implementation rate. This is amazing. So I think success sometimes also depends on the way you communicated inside your company.

SPEAKER_00 10:19

That's so true. So what would a success look like in your case? Or can you maybe share a success story, an idea on an initiative that genuinely showed what good internal innovation and idea management looked like?

SPEAKER_01 10:33

I actually have an initiative to share that actually helps to drive better innovation. So, from my perspective, actually, with as with any innovation program, key factor is management support. At manufacturing sites where plant managers were truly supportive, the program actually worked much better than at others. And one initiative I really liked was implemented at a site to recognize the ID submitters. So you have to imagine that the site had many, many employees. So finding a parking spot near the main entrance in the morning before the shift started was quite a challenge. The plant manager and the local ID manager had an idea. They created an exclusive parking spot right in front of the main entrance for the employee that submitted the best idea. And then there was this large sign that said, best idea submitter. And I think this is a very, very big honor. So instead of simply rewarding employees financially, they made this recognition visible. And it made the people feel very special, and of course, words spread it quickly, and suddenly more employees were motivated to become this next big idea submitter. And I think personally, this is a very nice idea that helps to drive innovation.

SPEAKER_00 12:09

I love that. That's so cool. Um, and I can totally see how that works because it's those little recognitions, I think, day to day that can make all the difference. And what also strikes me is that the one thing you meant mentioned is the conditions, so the context rather than the idea itself. What made it worth, what made it work was that management support. Do you think that's what separates good programs or good initiatives from those that maybe don't work in the end? Is it mostly that condition they find themselves in, or is there other factors that we would need to look out for?

SPEAKER_01 12:45

I think programs that work better or generate value have understood that it is people business. As an idea manager, you are not only responsible for managing your ideas, you have to manage people. You have to make sure they feel valued, they feel treated fairly, and they stay motivated. So if somebody submits an idea and it might not seem that promising, you should still treat this person fairly. You have to provide constructive feedback and treat them in the same way as you would like to get treated. And there's also long-term benefit from it because people actually learn from feedback and they will submit better ideas in the future. This is something we found out in one of our research papers. So, in the end, the best ideation systems have a high level of empathy for the employees.

SPEAKER_00 13:46

And this is highly important. I mean, uh, I think we could talk about just the idea management piece for hours, but let's jump to venture clienting briefly before we come back to the research and the ideas. So, obviously, a more specific space, and it's not just the ideas you're working with, you're working with external startups who you know you're needing buy-in on, I don't know, I guess almost a higher risk level compared to working on um internal ideas sometimes. For those who aren't familiar, how would you describe venture clienting at Male and why did the company decide this was worth investing in?

SPEAKER_01 14:21

So maybe let's start with the term venture clienting. So it simply means that you as a company become a customer or a client of a startup. And this usually follows a very structured process. So at the very beginning, you have a pain point from a company department. For example, engineers spending simply too much time on manual design tasks. And based on that pain point, you then scout startup solutions and you test those solutions inside the company. And then, if they work out well, you can purchase and scale them. You could even say it's just a more innovation-driven form of purchasing. And at Male, we have invested in venture clienting because simply you cannot do every innovation inside your company. That would be very expensive and very time-consuming. And startups are often faster, they are more specialized, and I also have to admit they are sometimes just more innovative. And so venture clienting brings simply external innovation into the company in a very, very practical way, and it can help make a process better, it can help improve products or develop a new product together with a startup.

SPEAKER_00 15:50

That's really cool. And has there been any successful venture clienting collaborations so far in practice? If you can give any examples of that sort of partnership and you know what it did for MALA internally, that would be awesome.

SPEAKER_01 16:04

Yeah, so we have many successful examples. One example is a collaboration with a startup that led actually to a new product for car workshops. So the solution enables to make a very simple battery diagnosis in a car workshop by only using the charging cable of the electric vehicle. And this partnership is quite interesting because MALE contributed the hardware components and the startup provided the software side. And this is just one example because we also have many successful collaboration examples that help to automatize internal processes, whether it's in engineering, purchasing, so many successful examples are actually available.

SPEAKER_00 16:55

That's so cool. And I love when there's concrete things, you know, that you can point to. And I think that's how you build on it as well, right? It probably was harder in the beginning. The first couple of um projects and partnerships were a little bit harder to kind of get by and for. But as you build that almost, you know, portfolio of look, this is what's worked, and this is the benefits we had from it, that can make a massive difference of scaling that sort of innovation. I love that. What do you think personally? And this is just a question I had now that if you have an answer to it on the spot, but what do you think needed to be true internally at Male for a collaboration like that to actually work? Like, what made the organization ready to absorb that? Does it have to do with the culture at that point that was built? Was it mostly the like? Do you have a sense for what made it work in the end?

SPEAKER_01 17:47

I think it's very hard because I think you have built you need to build up something like that for many years. And what you just have mentioned, having one concrete example with a success story is very, very important to also get this internal trust and to develop this openness for startups. And because of that, I would always say at the very, very beginning, when you start with venture clienting, focus on one particular pain point. So do not focus on uh collecting many pain points and starting many projects, but focus on one particular pain point that has quite a big impact and try to make it right, have a startup collaboration and communicate it across your organization. And I think this is very, very essential to build this trust and culture and openness inside your company.

SPEAKER_00 18:52

100%. And I think you hit the nail on the head with the communication piece as well, because oftentimes, even if there is some collaborations or you know, interesting POCs, if we're not really, you know, venture clienting either way, have been done, that piece, communicating it, showing the success, I think that's usually um underestimated and can make a massive difference for future endeavors. And I think it also removes some of those potentially misconceptions, misunderstandings. You know, internally, technical leaders might have certain views of what they think startups are like and how it is to work with them. And at the same time, smaller startups might look at Male and think, oh, automotive, traditional, not quite sure what that's going to look like. What do you think some of those misunderstandings might be on both sides of startups for a corporate, but also a large industrial player for a startup?

SPEAKER_01 19:50

So let's start with the company, with a large company. Here, people quite often assume startups do not have a ready-to-use product. They imagine the small garage firms that only have a prototype available. And as an outcome, some colleagues they even prefer to wait until their established suppliers, like SAP, introduce the new amazing AI features, you know, instead of working together with a startup. But I always say the startup ecosystem is so incredibly diverse. You can decide on your own, do I want to have an early stage solution or do I want to have a solution that has been already tested successfully with other customers or companies? Yeah, uh sometimes I even avoid the word startup, and I say, oh, it's a solution provider or a supplier, and I'm not mentioning how old uh the company actually is. And then on the other side we have the startups. And the startups, what they misunderstand about uh large companies like MAL is also quite interesting because they assume because we are a billion revenue company business, we have just unlimited budget and we can do everything. But we are also under cost pressure. That means we cannot invest in any fancy tool unless there is a real benefit for us. Either it can be saving money, efficiency, quality, or generating revenue. So the economic times are very, very tough at the moment. But they are not only tough for startups, they are also tough for many established firms.

SPEAKER_00 21:48

That's so true. And I've definitely seen, I mean, we've done a lot of work in, for example, aerospace, not the same as automotive, but you know, some parallels and obviously some collaboration historically. And it's those startups that. That really understands the pains inside the corporate, not just the technical pain point they're trying to solve, but also the context of challenges that they're faced with, who, you know, other startups that come in and make their corporate champion look really good in front of their colleagues because they know, you know, there's pressures around potentially, I don't know, restructuring in certain industries. There's all sorts of um drivers that people might have for why they want to get involved in innovation activity or why they want to drive a product project forward. And yeah, if that understanding isn't there on both sides, that can be really, really tricky. But that's some great insights. And I think you were already, I mean, a real gold nugget earlier around really focusing on one pain point and trying to deliver something of value and then really heavily communicating it, I think is one of my biggest, biggest takeaways from our last few questions. So thank you so much for sharing that. So you recently published a paper in the Journal of Product Innovation Management, and you were exploring how AI can transform corporate innovation or corporate ideation systems. What was the core question you wanted to answer with this? And maybe you know what surprised you most in what you found in that research?

SPEAKER_01 23:13

So the core insights was about AI's role in the ideation system, and that it can be much broader than simply generating ideas. So many companies today have ideation systems in place. It can be an internal system involving employees, or it can be also an outside system involving customers, but many struggle, like how ideas are evaluated, formulated, how they are moved forward. So our research did look at an ideation system as a whole. We asked where can AI truly improve the process? Not by replacing a human or creativity, but by supporting different activities. And our goal was to identify common pain points among stakeholders using ideation systems, so pain points among idea managers, evaluators, idea generators, and actually understand how AI could act as a pain reliever. And this was quite interesting, what we found out.

SPEAKER_00 24:28

Yeah, I can imagine. I mean, you've at that point, you've already been running ideation systems when you started that research. Did the academic findings sort of match some of your lived experience, or did the research really challenge some of your assumptions that you might have had with like early AI kind of ideation?

SPEAKER_01 24:48

Yeah, I think when we started doing the research, there was not much AI out there yet. So not many companies did have AI in their ideation systems implemented. And I must admit, today it's also still an exception because many companies do not know how to do it right, or they do not have the infrastructure yet. And the pains we identified, I think those are just uh generic pains. Um, many, many companies have have, like we have this content formulation pane. So I think it's even not tied to ID management system, but very generic. So in this content formulation pane, for instance, many different stakeholders have. Like as an ID manager, I have to make sure my campaign is properly understood. So I need to make sure to phrase it in a proper way to make it attractive. But as an idea submitter, I have to make sure my idea is properly understood. And also as an evaluator, I need to properly formulate my feedback. So we identified this generic content formulation pain. This was just one of a few pains we identified. And since the study was quite broad and we involved many different companies and we talked to many ID managers, I think the findings are quite generic. Yeah.

SPEAKER_00 26:22

Okay, well, but that makes sense because, like you just um kind of demonstrated, there are so many different players. But I think it's still really interesting to see that pattern and that there is certain pain points that you know run across the whole chain, which makes them important and makes them urgent in a way. You've also in your research mapped five roles AI could potentially play inside ideation systems. So there is an inspirer, a stylist, a matchmaker, an analyst, and an organizer. So if a company is just starting to think about this, which role gives them the quickest, maybe most meaningful win and why? Anything you can give the listeners on the way?

SPEAKER_01 27:05

I think it's quite uh difficult because it it depends on the company, actually. I think what I would always recommend is as a company first do your homework. So that means look inside your organization and identify your own pain points. So, what are the pain points your people struggle most with in the daily work? What is very time consuming, what is frustrating? So, for me as a major client manager, it's it's very frustrating or time consuming to search for startups and to analyze their offerings. So, this is a classical search pain or analytical pain. And inside our research, we figured out that among the people we interviewed, the biggest pain is actually the content formulation pain. Because as an outcome, it will have a big effect on other activities. So if I do not formulate my idea properly, it might not be understood by the evaluator. The evaluator might get angry, but or he has to go back to the idea submitter, ask follow-up questions. And I think this was very interesting because they always said creativity is there, but it's hard to put it on the paper properly. But coming back to your question, I think it's always important to do your homework inside your organization. So first ask the people, make with them creativity workshops, ask them what's time consuming, what's frustrating, and write down these pain points. And as a next step, prioritize them. So, for example, you can prioritize them based on impact or feasibility, and then decide with which one you would like to start first. And for this one, use AI.

SPEAKER_00 29:06

I love that. I also love that there is a big part or big piece of work to be done before AI even gets involved. Because I guess that's some of the worries people have, or some of the things that obviously lots has happened as well in the last few years. But one of the worries is that we have this massive amount of knowledge in some of our leaders or senior leaders in those big um corporates. And AI is, you know, giving people in some ways instant answers to questions that these leaders have needed years to learn about. Um, and as much as I don't fully agree, I think that knowledge is still a lot more worth a lot more than what AI can kind of spit out in a few seconds. It's it's a challenge. It's a challenge amongst you mentioned earlier, there is cost pressures, there is um budget pressures in these big corporates, and it's it's compelling to be able to get to speedy answers. But it cuts out that human creativity, it cuts out that context and that experience, which I think we as humans need to really, really, really fight to keep alive.

SPEAKER_01 30:11

Yeah, yeah. So, what you can also do, I think I'm also a big fan of experimentation because I think at heart I'm I'm still a researcher, you know. So part of me also says simply give people an AI tool and let them try out, let them explore, have them use it, you know. But you must be also careful because if they do not use it properly, it could have a negative effect. So I think experimentation is also good, just trying by doing. But at some point, you also have to follow the strategic route by really thinking about what are the biggest needs, what are the biggest pains, and and having a clear AI strategy.

SPEAKER_00 30:57

But I'm also wondering, you know, I'm thinking about your like your role back in the day, if you think of idea management back in the before AI, what it was and what it might be today. And you mentioned earlier that, you know, innovation, it's a people business. It's all about working with people and not nurturing people's skills. And I think that's becoming more and more important as AI becomes more prevalent because people start potentially worrying about their roles, worrying about their skill set and knowledge, if that isn't communicated properly, if there isn't like almost a rethink of certain potentially jobs given some of those technological advancements. And that's probably the role of that leader, in a way. That's my assumption. But maybe, maybe you you disagree. But I feel like maybe if you were to think about looking at ideas today or looking at ideas back in the day, was more about a mix of how do I nurture the people and find good ideas. Where I think these days it's even heavier on how do I nurture the people to whether they give me good or bad ideas, kind of secondary, but how do I make sure we keep them going and coming?

SPEAKER_01 32:05

I think what we what we see in companies, and I think this is also similar to what we see in terms of journals. You know, um, I have recently talked to somebody who's editor for a journal, and what he sees is there are just more papers and submissions coming in. So since AI has started, they are overwhelmed by journal submissions, and they have to be more critical in what they accept for being reviewed and desk rechecked, actually. And this is also one issue, or I would say it's a challenge we are having with idea management. More ideas are simply coming in because it's just quite easy to generate an idea. You can simply chat with the AI. Maybe you even only need a problem, and the AI can help you getting inspired for a solution. But I think then the role of the idea manager is very, very important because normally the idea manager at the beginning makes some sort of a cross-check. So this is the first gate that decides am I going to send this idea to the evaluator or not? And I think this is very important, and I think this task has even become more essential since more ideas are getting in.

SPEAKER_00 33:39

Yeah, that's a really, really good point. Yeah, this is more time, probably, not just because there's more ideas, but the vetting of all those ideas can take a bit more, yeah, careful, careful attention, um, given how they might have been generated as well. That's really interesting. So let's maybe look in the future. Don't we all love to look in the future because we have no idea what's going to happen, but let's let's make some forecasts nonetheless. Let's say five or ten years you can choose looking ahead. How do you see the relationship between human creativity and AI evolving inside large organizations, like, for example, MALE? And what do you think that means for how we think about building innovation culture?

SPEAKER_01 34:20

Yeah, I think this is a very hard question because I do not have this uh magic uh crystal ball to say what's going on. But I could imagine two extremes. So the first one could be a growing resistance towards AI in creative processes or in IT management. We already see very early signs on this. For example, when content is explicitly labeled as non-AI generated. And one reason could be unproper usage of AI. So when organizations just let people experiment, you know, it can also have unintended uh consequences in the end. For example, like idea evaluators may suddenly get idea descriptions that are overly long, you know, what will happen? They will get annoyed and they decide not to evaluate an idea anymore. So it can be that then there might be the decision to turn off AI again and not use it or rethink its usage, you know. And the second extreme is, and maybe this is far, far in the future. Imagine now you have a very highly connected world where you have a lot of data. So imagine you have a manufacturing environment where all the machines are fully connected, or we have products that continuously generate data with apps. In that world, I'm asking myself how much human creativity is still needed? Could a shop floor not in the end improve itself based on data, or could new product ideas not automatically emerge from apps, for instance? And I think it's also a little bit scary, but this might be something that that could also come to reality.

SPEAKER_00 36:21

I think you're right. And as much as I agree, probably a bit more in the future, probably not as far in the future as we would hope. But let's see, let's see what happens with all of that. I think it's really interesting. It's a really interesting topic. And particularly when we think about innovation, it always ties into this human creativity as well. And one last question on that before we have the wrap-up questions. Do you think there is any skills or traits or whatever you might call them, something like human creativity that AI cannot touch? Something that will stay human?

SPEAKER_01 36:56

I think it's very, very, very hard. You know, AI is based on those algorithms. When it comes to very creative and good ideas, you know, most of my um channel paper ideas I'm having at very, very awkward moments, you know. So recently we had been doing one research that somehow connected to overtrading, to trading business, because my husband actually, he's a trader, he loves trading. And in overtrading, there is this phenomenon that when you made a very, very big win from a trade, you get very confident and you think you can repeat this trade and also make another big win, but the environment changes. And my idea was then because I was talking with my husband about trading business and over-trading, does maybe something similar happen in idea management with very, very successful ideators? And I think AI is not able to like replace such creative ideas from conversations or from inspiration you're having in your in your daily business.

SPEAKER_00 38:20

Very, very true. And I agree, and that's fascinating. We should continue that conversation. I also, in my behavioral science degree, I wrote a paper on um the outcome bias in corporate innovation investment.

SPEAKER_01 38:30

So I can share that with you.

SPEAKER_00 38:33

The grade was middling, but I think this is very interesting.

SPEAKER_01 38:37

So I think this behavioral science is very, very amazing and fascinating. Yeah.

SPEAKER_00 38:44

Yeah, absolutely. Lots of work to be done on that. So, conscious of time, on a personal level, what are you most curious about? And you've touched on some of this, but if you had were able to narrow it down to one thing in your work or your research or beyond, anything that you're currently um feeling like is going to take up most of your brain space.

SPEAKER_01 39:02

What we are currently thinking about doing research is actually how AI will change our learning behavior and also how we will develop in the future. I think this is a very, very interesting question to follow because we often say AI makes us more efficient, we might become better. But how will people actually develop skills in the future when AI has been always there as a sparings partner? And I think this is this is quite an interesting research topic. I will be following with one of my uh my co-authors. He's he's a professor in in Liverpool. So maybe at this point, hi Hong.

SPEAKER_00 39:49

I hope you're listening to that sounds fascinating and so so so important. I think, yeah, it's it's so important, not just, I mean, from kind of learning aspect from like you know, school education, but also learning within a corporate and those skills. Um, that as we mentioned earlier, you know, some of your senior leaders who have not grown up with AI will be retiring at some point, and you've got a younger generation coming in who have just been learning and um absorbing these things in a very different way. So it's a fascinating um research topic. Can't wait to see what that comes out as. And maybe other than your research um sparring partner, um, is there any other innovation leaders, for example, or thinkers that you admire and something about their approaches that resonates with you, someone that people should be aware of that are listening?

SPEAKER_01 40:36

I think I especially admire the female innovators because historically wise, the innovation field has been very male-dominated, I think. And there are many women that did contribute to innovation. Sometimes uh we do not know it. So maybe you know the Rittersport chocolate. Yeah, yes, and yeah, and uh Clara Ritter, she was actually a co-founder of Rittersport, this popular square chocolate bar. And what I admire is actually their strength and their staying power, their creativity, because they achieved a lot in a time where it was quite hard for women. And even today, I believe that we women can be very powerful innovators because we manage so many things at once: work, family, children, social activities. And so we have a lot of key strengths that innovators should have, from empathy, practical problem solving, up to resilience, for instance. So yeah.

SPEAKER_00 41:48

Wholeheartedly agree. Definitely. Some of the most inspiring, you know, young founders I've worked with have been women, um, but also, yeah, like I say, more broadly, we underestimate how many women have really shaped the well world, um, but also um the innovation space we are both in. So, yeah, thank you for sharing that. And finally, as another inspiring woman in innovation, what's next for you? So, how can uh listeners connect with you, learn more about your work, and follow your research potentially?

SPEAKER_01 42:20

Yeah, what's next? I think I always have many ideas, maybe too many, which makes it sometimes hard to choose from. So, one direction I'm currently exploring is actually founding my own business. I'm still shaping what I what this could look like. So it could be advising companies on proper AI usage, but I'm also quite interested in doing something, building a bridge between business and stronger research foundation. So let's see what it will be. And yeah, I think the best way to follow my journey would be definitely to connect via LinkedIn.

SPEAKER_00 43:04

Brilliant. That sounds great. And yeah, if any of those um things we talked about resonated, or you're like, oh Selina, I'd love to chat. All the things that you're planning sound like something that, you know, I would like to have a discussion about, please do find Selena on LinkedIn. And I think that's us with the questions. So thank you so much, Selena, for deep answers, for making the sometimes abstract innovation stuff feel very practical. And we really appreciate you taking the time to join us. Thank you. Thank you too. And that's a wrap on this episode of The Innovation Brief. If you enjoyed this conversation, please subscribe and leave us a review. It helps other leaders and curious minds discover the show. I'm Gabriela Matic. This has been the Innovation Brief, and thank you for listening. We'll be back next time with another inspiring conversation.