🎧 If U Seek is back! We are kicking off season 2 with a fresh set of conversations at the intersection of UX, research, and the very real people behind it all. Whether you’re listening on your commute or sneaking in an episode between meetings, we hope these new stories spark ideas and keep you inspired.
We sat down with Kostas Giannakis, Head of Product Design & Research at Next Insurance, to explore one of the biggest questions in design today:
How is AI actually changing the way teams work, collaborate, and create? From speeding up research and prototyping to redefining team structures and team rituals, Kostas shares how his team is experimenting, adapting, and rethinking in the current design environment influenced by AI.
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Preview
In this episode:
- How AI is shifting design from “pixel pushing” to strategic thinking
- Why fast prototyping is changing the way teams work together
- AI’s role in research, from transcripts to interviewer bots
- Why junior roles might be disappearing
- Why Kostas avoids the word “manager” (and what he says instead)
Transcript
Kostas: [00:00:00] We weren’t sure how people will react talking to an AI interviewer, we were surprised to see that, people seem to be very comfortable, doing so. In some cases they’ve said that they feel like more comfortable actually sharing something because it’s an AI interviewer, it’s an actual human.
So they may be like more honest, let’s say. In their responses.
Useberry Ad: What we seek shapes what we build. This is If U Seek by Useberry.
Hello Kosta, Welcome to If U Seek. I’ve been looking forward to this one. Your story is a fascinating mix of serendipity, exploration, and intentional craft from studying economics, transitioning to AI where you found your passion for human computer interactions. Your work spans multiple industries, and now you’re leading product design and research at Next Insurance [00:01:00] driving innovation in a highly complex and regulated space.
What really stands out is your ability to lead through change, whether that’s. Adopting emerging tools like ai building high performing cross-functional teams, or making design a strategic force inside companies. So there’s a lot, and I’m excited to get into it today especially how you’re thinking about the evolving role of designers, team culture, and the very real ways AI is shaping our work.
Are you ready to share some thoughts?
Kostas: I’m ready. Hi Nicole. I’m stoked to be here. Thank you. And thank you Useberry team for having me. Yes, let’s do it.
Nikol: Cool. Okay, so let’s start with what’s on everyone’s radar, the rise of ai. You’ve led teams through different waves of tech change, I’m sure. [00:02:00] And with ai, we’re seeing a new layer of complexity from the speed to evolution to the way it challenges how we define design itself.
So how do you see it affecting the design world today?
Kostas: Wonderful question. I tend to think about this not so much about the design world specifically, but overall how the product development process works. This is a lot about how you, we bring people from different functions to work together, and whether it is design or product management, engineering, data science, marketing, you name it, AI is leaving its mark on each of those functions and essentially influences how we work together.
One area where I see that this is changing, the dynamic of how we work together is getting ideas out of the door a lot faster. So generally looking at the design process, I feel like it’s been flipped on its head and I. Where [00:03:00] before it was like, we would start from the discovery to lofi designs to iterations, and then at some point having confidence into more high fidelity prototyping.
Not all that is pretty much flipped on its head and designers themselves or either even other functions being able to bring their ideas to life and expedite stress related discovery process with very. Life, like real applications that you can quickly test with your target audience and then inform the process subsequently.
So that is a really exciting development, in my opinion, and one that really creates space for design to really sign in their, like being drivers of, the strategic thinking behind the work and focus less on things that have to do with. Pushing pixels and prototyping, because all those things now can be done a lot faster and in some cases a lot, no, a lot easier as well.
If I compare [00:04:00] this to the world today, or let’s say before AI or without, I. Using ai. Our experiences, like what we usually tend to give users to play with and for us to gain insights are typically like, click through prototypes. So like we give them some flows and they will have, go click and they will start to do tasks.
And then we’ll assess how usable those experiences are. And now if I look at what we do here at next, the experiences we create for people. They’re not just clicks. We require input from them and therefore the experience are more dynamic. And that’s a current limitation we have with, let’s say we’re, when using a tool like Figma to put a prototype together, it works, but it’s not the same thing as having an actual experience where you can.
Type in something. For instance, select from, different components and modes of interaction. You can do those things, but it takes so much more time in doing [00:05:00] that in a tool like that versus now maybe using tools like V zero bolt and so on, and you can just bring those ideas to life very quickly.
That’s a big area where I see AI making an impact and leave. Its mark.
Nikol: Okay. So there’s been a lot of conversation about AI replacing designers, not just within design circles, of course but across the tech industry. What is your take on this?
Kostas: It’s been a lot. Yes. And going back to what I was saying earlier, you can argue the same thing for every other function, right?
Do we, will AI replace. Product managers, will AI replace engineers? So in general I am I’m fairly optimistic about, where things are going. I think at the highest level, when I look at design teams and their structure and their size in the world where. AI becomes more prominent in the way we do [00:06:00] things.
I expect that, teams will remain relatively flat in my opinion, if not somewhat, a little bit smaller in size. And I’ll explain what I mean by that. If you think about it, again, going back to like product development, I think in my opinion there are like three large buckets of work that we do. The most critical one.
The most important one is, strategic work. Big zero to one features or like new products we bring to life. Things that are very, highly complex to build or to find solutions for highly ambiguous as problem spaces. I. Then there’s a bucket of work, which is more feature level work.
Maybe you have already have an existing productive feature. You’re like, you’re trying to optimize something like, you know something is not working well, you’re trying to fix that, or you are providing more value in an existing problem space. And then you have a bucket of work, which is even addressing, let’s say, technical and design debt and doing [00:07:00] some foundational work to support everything else. So when I, when I look at those three different buckets of work, the area where I see that still is not so much, if you like, I. Appended by AI is the large strategic efforts, and that is where I anticipate to see more the role of, design continuing to drive those initiatives.
So in this. AI powered world. I’m looking at this as sifting our energy essentially from the low level pushing pixels. Going back to what was what I was saying earlier, what, some other people may see designers doing into the more strategic real of work, but that’s not easy for every designer to do.
And when you look at the spectrum of, different skill sets and different levels of designers, it’s usually like the more senior designers who can do this. So I see where I think I believe things are going is that teams [00:08:00] likely from a structure point of view will be comprised primarily from more like senior folks on the team because that’s what the expectation will be from design to provide that strategic thinking, facilitation efforts, the opportunity to, create empathy, all those things that you know we’re doing very well. But the parts of the work will be more execution oriented, like prototyping polishing, like all those things. They’re they will be so easy to do or maintain with AI in the mix, which creates less opportunity, I think for more entry to mid-level designers or for someone who’s like earlier on their career stage.
So that’s one prediction I’m making that, teams will likely tend to be more senior level concentrated. Which I think is an interesting challenge in my experience, the more diverse the team is and the more diverse it is and there’s like a healthy balance between the different levels of team members, it has the better because that [00:09:00] provides opportunities for growth, provides opportunities for people to challenge each other, not necessarily from the same starting point.
So overall, I feel like it’s a healthier mix. To compare, to have a more like concentrated team structure. So that’s a, that’s something that I believe, design leaders like myself, we have to face the challenge in on how we influence the direction of how teams are being built and are being structured in in this world.
Nikol: Okay. You say that juniors, let’s say the entry level. We’ll need to jump up to the senior position. It’s like a loop. I think so. And loops tend to, roll, so it just needs to keep on rolling. I think it’s, yeah, it’s a never ending thing, it’s yeah, it’s very interesting and it makes a lot of sense what you’re saying and I think many listeners will find that reassuring, let’s say and but also challenging.
But in the best way, I guess we in the best way. Yeah. Yeah. [00:10:00] Yeah. Up next are there specific tasks or processes your team used to handle manually that are now being automated or supported by ai? What kind of impact has that had on output? On roles on team expectations? You talked a bit that a bit on that a bit but if you can Yeah.
Give us some more insight.
Kostas: Yeah, absolutely. And I’ll say for the most part, I think it’s more like supported by ai, not so much automated at this stage, although we, I think we have like good examples of how we can automate some things with ai. But it’s been like a, now maybe a little over a year.
I think that we’ve really dipped our toes into leveraging ai power tools and just, being curious about it, which I think that’s a very important mindset to have in this world, is to exhibit curiosity. Go with let’s check it out. Let’s see, does this work for [00:11:00] us?
And let’s develop a point of view versus relying on. Someone else’s, or friends we know, we see out there in the market. So when I look at the. Breadth of things we do. I’d say research is definitely an area that’s has seen the most impact from ai and where we see like daily, essentially support from from ai whether it is to help design research studies or whether it is to use it to analyze recordings data transcripts, you name it, and just, just being that.
Called pilot in a way where it speeds up essentially the process of developing good insights to a lot further inform, what we do at the company. That’s I’d say that’s the biggest, area where we see AI supporting our work. Today on the more the design side of things as I mentioned, we’re just entering like the world of prototyping more.
[00:12:00] This like new tools and again, getting to more real lifelike applications that we can test with customers or prospects in in our case copywriting is something that we see a strong AI being a strong companion to designers, although, I must say I find it very valuable as a tool, but still, it needs not just this, but everything we do with AI needs.
That level of supervision, someone with the right expertise to see it through the end. You can’t just take the output of AI and just use it the way it is. It’s I think, very dangerous to do I agree. So in the case of research, it’s an actual, like researcher of the team who you know, is using that tool but ensures.
That there’s no bias in that. There’s, there are no made up things. So we’re building if you like guardrails on how to ensure that the output from AI is actually something that is reliable and can be trusted. So to the example of copywriting, I still feel we have like good options to be [00:13:00] generated and, but at the end of the, at the end of the day, we’re working with an actual copywriter to really.
Come up with the right, copy or messaging that we need to involve in an experience. And these are the, like a few examples quick examples of how AI supports our work today at next.
Nikol: These are great examples. It’s one thing to talk about AI broadly, that you hear a lot about it.
These things the kind of things that of that are concrete. And they shift what, what happens on the ground, let’s say. All right, real quick before we jump back in. You know how product teams are always trying to move faster and research teams are trying to move smarter?
Useberry actually helps you do both. It lets you run quick remote user tests, and honestly, they’re just as easy to run as they are to share. No bottlenecks, no endless waiting around, and definitely no more guessing. It’s just research that moves at the [00:14:00] speed of product. Check it out at useberry.com. Okay.
Now that we’ve explored some of the big shifts, I want to turn the focus to something more human, the culture behind the work. What have you found works well when it comes to building or maintaining a strong team culture? Great question. And I love the focus on, being human at the end of the day, that’s all there is.
Kostas: So for me it’s things are really simple, although not easy to to do. But I think what I’ve seen as the main areas to invest in building and maintaining, great team culture is creating that space for psychological safety and leading with intentionality and transparency. This is for me, like this is a one way street.
There’s no other way to do this. You have to [00:15:00] do things intentionally. You have to create, to show genuine care for people to come across in a very authentic way. One thing that really. Stuck with me over time when I was empowering design at Gusto a few years back. Gusto is a place that is obsessed with how, we treat people across the board, whether it is employees like, our, customers and so on, and as.
Almost developed its own like vocabulary of how to address certain situations. So for example, at Gato, there’s no human resources team. No one talks about human resources or no one is talking about people as their, like numbers on the spreadsheet or resources and so on. No one typically you, we’re called managers, right?
People who manage teams. But Augusto, that word doesn’t exist. That term doesn’t exist. So if you the manager is being replaced with, people empower [00:16:00] or people management is people empowerment and managers call the pe. All those like things are put in place. And everyone is really obsessed with those things to ensure that, like this is how you, so you care about someone, essentially.
And it’s those like little details that really make huge difference, I think in someone’s experience and motivation and feeling, great in their role and where they are. So that’s something that I really first encountered there, but then I carried it over since then it’s been now.
Probably four or five years have passed from that point in time. I’ve never used the words, I manage people ever or always. If you ask me, I’ll say, because I like, what do you do? I would say, I empower a team of designers and researchers, for example. And that always, I’ve noticed that, clicks with people. People will tell me, Hey yo, you, I notice that you say, the word empower. What does that mean? And so on. And that this sparks curiosity in other people, right? So that’s why I [00:17:00] think this little details do make a big difference.
But yeah, at the end of the day is about treating people. As the humans, they are creating that space where people can be themselves, open up themselves so you can have that genuine interactions with them and. It’s not always gonna be about positive stuff. The work is a place where conflict can happen.
Lots of tension can arise from cross-functional collaboration or we, between like team members. All those things can co, can crop up, but that’s where great culture really shows up in those moments. How do you, how have you set up, the team to manage those situations? How do you handle conflict?
How do you ensure that people can speak up and, resolve things in good positive ways? And it starts with us. We need to lead with transparency and just, solve the path forward in those cases.
Nikol: The word empowerment really stuck to me. It’s like you are [00:18:00] inheriting it, so it’s like it’s becoming part of you. Exactly. That’s how I felt it. Yeah. Very nice. Very interesting.
Kostas: It’s a contagious, in a way like to me no you hear it now, you use it, and then it’s, it goes like that.
Nikol: Yes, exactly. Okay. Have you faced any specific challenges in preserving team culture?
You, you touched a bit upon that, some conflicts or that, I guess they make you stronger as well. What used to come easily that now takes more effort, perhaps,
Kostas: I’d say in my experience, when you have a chance to build a team from the ground up and I’ve had that chance in a couple of occasions in the past, it’s way easier to both build and also preserve the team culture because at the end of the day is, you.
You together with the team have built that. And over time it’s, it becomes [00:19:00] easier if this is something that you have all contributed to over time. But that’s not always the case. There have been many cases also in my career where. I’ve, let’s say, inherited a team. There’s a team in place already and I’m stepping in to continue empowering and growing the team.
And it, in those moments, it’s a lot different than a team that you have helped say from the from scratch in this case. So in those situations is, you know what I found handy if or. Helpful to preserve team culture in those situations is first of all, to understand what the team culture is. So you’re stepping in into a new role.
You are inheriting this theme. You are most likely at a new company. So you must, step back and just, get to know your people. Be very observant about, hey, like what is the culture here? See, like what are things that you opportunities that you can find to improve the culture further or things you want to change, and then yeah, [00:20:00] slowly work your way into making those changes happen.
I find that in those situations it’s more challenging to do so because a lot of it hasn’t been your, let’s say, contribution or work. So it’s important to understand where things. Are what makes people click already and then build upon that. And you may have to forget about what might have worked in the past there, different teams, different companies.
Something that from your playbook that has worked in another place or for another team may not be applicable in another team that you find yourself empowering. Yeah. So being flexible around that is really key. So be curious and just look out for signals all the time. In today’s world, we have many tools that can help us find opportunities to make things better for people.
If you look at employee engagement surveys, which are very common within within workplaces, but also again, going back to what I was saying earlier about, leading [00:21:00] with intentionality and leading by example, it starts with, with with us again for me it’s I intentionally make myself.
Vulnerable to everybody else that I work with, whether it is my team or my constructional peers whoever it is at the company. I constantly, will ask for or push people to give me like constructive feedback. Just, like all my mistakes or seek opportunities always to find out where can we do better?
Where can I be better in helping others in terms of building that, strong team culture. I.
Nikol: Yes that’s that’s, let’s say real insights and honest insights, let’s say. So being vulnerable pushing to get even the negative feedback I guess that’s real, really important.
Kostas: That’s the most important thing. For anything, constructive feedback is the best you can the best you can get.
Nikol: Yeah. Do you have any rituals or small practices that help your team stay [00:22:00] connected? Or inspired, motivated, even seemingly small things, how you start a meeting or celebrate a win, it could play a big role.
Kostas: During the week, we have a couple of regular design critique times Design critiques are very interesting forums. So usually they can be really good, but they can also like, be really bad. We use a specific framework to make design critiques more more effective. Like one, one thing I’ve seen and observed in critiques in the past is that usually they tend to be dominated by.
People with loud voices, like people who are more, maybe they’re more extrovert oriented, maybe more strongly opinionated. And it tends to become like, maybe like you have a room of seven, eight people and it becomes like a debate between two people. And that’s not what you want at the end of the day.
We have adopted a framework called Thinking Hats. And if you Google it [00:23:00] up you’ll see there’s plenty of literature around it. But essentially what it does is that it provides structure to the format of a design critique. And most importantly, it gives everyone a voice and everyone a specific mindset, if you like to use when providing feedback for a specific.
Design or experience that we’re critiquing. So for example, you there’s a hat, like the white hat where you get, everybody gets to ask clarifying questions. There’s the yellow hat, which I think is the positive feedback. Everyone needs to provide at least one positive feedback for the design.
There’s the black hat, which is the constructive feedback about design. And there are different hats or mindsets to which continue the process and that. Levels, the playing field it, so it’s, so it doesn’t become now, okay, like someone will dominate the conversation because this can’t happen.
We have to go around the room, we’ll collect feedback from everyone. So you see those, let’s [00:24:00] say undesired behaviors not showing up anymore. And it tends us to focus more on the feedback and nothing. Nothing else really. And one of the things that I usually do there, because oftentimes like I, I feel that if I say something because of my role, some people may think that, okay, if Kosta saying something may tend to agree with that right.
And I dunno if it’s happening, but I don’t want that to happen. So something that I do is that, and I usually say it in front of the room is that I go last because I don’t want people to call or what they want to share because they’ve heard my opinion about something or my feedback about something.
And the other thing we do there is that basically we have opened up this to every. Basically pretty much everyone, but typically it’s engineers will be there, PMs will be there, and that makes for a much better collaboration and critique process.
Nikol: An example comes to mind. [00:25:00] So this is let’s say a real setup in in the outside world, not in a work environment that, you just go out for a coffee with a few friends.
If everyone can talk and everyone can participate actively, you feel part of the group. I don’t know if it’s if you’ve ever felt it or, I’m sure people will understand this, but that some people dominate a conversation, but when it’s all, everyone has a voice it’s more interesting. You wanna stay more, you’re having fun. So yeah. Great example.
Kostas: Yeah, agreed.
Nikol: Nice. I’d love to hear how AI actually fits into your team’s day-to-day work. Can you walk us through a real example of how your team uses AI in your work today? Whether it’s user research the interviews or something else.
What does that process look like? Yeah. As I mentioned earlier, I think user research is probably the area that [00:26:00] we’ve seen the most impact from ai, or I’d say the area where we very actively use AI pretty much on a daily. On a daily basis, we found that it’s a great companion tool to what, the researchers and designers do.
Kostas: So the example that comes to mind is how I think we’ve been able to scale and up level our research practice through ai. And that involves a couple of things. One is. Just using tools like, charge GPT or another like LLM to help analyze large, data sets, transcripts, all those kinds of things help with the structure of and design of studies.
But one really interesting area that we’re almost a year running this, we started with a pilot, but we quickly saw really great results from that, and we ended up adopting this as a regular tool. In our research process is using AI for interviews. So we’re talking about conducting [00:27:00] interviews with target customers, prospects.
We usually work with small business owners or insurance agents in the world of next and talking to them. And hearing from them is super critical in what we do in order to understand their pain points, in order to understand where we can provide value and offer value to them. But interviews are not easy to do.
They take time and you can’t just do a large number of them easily without this taking like forever to do. There are so many touch points that you want to get someone’s perspective and input to help implement insights. So that’s where we found, like around a year ago, this small startup gen building, an AI interviewer product, and we decided to give the go and see how it works for us.
And it has worked really well. It’s also been fun to be part of the. Of the process and, help that team build a better product by giving them feedback about what works, what doesn’t work, what we would like it to [00:28:00] see doing and other things. But we use a gen way to essentially interview different target customers at different touch points along their either like product experience or even outside of that.
That’s to be clear this is not replacing us doing actual interviews with with people. It just allows us to do more of that and at a larger scale, and then also an opportunity for us to compare, like what do we learn from human to human interviews and what do we learn from an AI interviewer interviewing another human?
And do those match are we learning the same things, does AI work in those situations? And what we’ve learned is that it, for the most part, it works really well. But as I was saying earlier, there are areas where you need to be careful about and you need that expertise and supervision to ensure that you leave out the parts that they may be.
Inaccurate if you like or not so much valuable at the end of the day. [00:29:00] We’ve also observed a few interesting things by doing that. For example, we weren’t sure how people will react talking to an AI interviewer, would they even do it? We were surprised to see that, people seem to be very comfortable, doing so.
In some cases they’ve said that it’s more, they feel like more comfortable actually sharing something. Because it’s an AI interviewer, it’s an actual human. So they may be like more honest, let’s say in their responses. But on the flip side, one thing we observed is that when someone is responding to a question from an ai interviewer, they tend to be less verbose.
So they will serve, they don’t have an issue like serving something, but they will serve less or they will be like they will use like just a few words to give like a response back. And these are things that in a scenario where like it’s a human interview, you might probe more into something, right? Or as a researcher, you may this might be an opportunity for you to dig in more.
Whereas the AI interviewer. We’ll go to the next question, for example, or the [00:30:00] next part of the script, missing that opportunity. So there are still like, things to make it better. And then it’s, it comes back to how you prompt the study, how you train the interviewer to do better in those situations.
But it has been a very interesting journey doing that and something that we’ve seen, been very impactful, at least I would say for quick surveys. You need to talk to someone for a few minutes. Not like deep complex, situations, but for yeah, for, but for quick feedback and input.
That’s been a very highly successful story for us.
Nikol: Yeah I really how you broke that down. It’s the AI in the team is getting really real. I see. It’s it’s becoming a part of our life so much and it’s really helpful. You can accomplish so many things easier, faster.
Very interesting. Okay. Let’s wrap up with something. Let’s say last thing, so I want to end on a reflective note. This isn’t [00:31:00] about what tool is next or what method is trending. It’s about what sticks. So of all the things designer and research have taught you about people, about systems, even about yourself what lesson keeps showing up?
Something that continues to shape how you lead create or, simply how you move through our world.
Kostas: Thank you for, creating the space for that. As I think more about it, it comes down to just, leading your life with, in intentionality. Take every moment and make it count.
I guess the lesson for me is that my measure of fulfillment, so to speak, is that I’ve been in a moment with someone. And I’ve made it a valuable moment and experience for them and for me. I did my best to show up the best I can be there, be [00:32:00] present, and yeah, just have a. Great outcome at the end of the day, not only by the way I measure that, like how I feel, but to leave that moment and know that somehow know or feel that the person that I had the interaction with, they got what they needed.
They I, I helped them in some way move forward. So that’s my that’s what I really invest my energy if I can. It’s not always easy, but that’s the lesson I. Continuously come back to and reflect upon how do I feel? How do I think I believe that the other person feels or felt?
Yeah, so leading with that intentionality is what is basically the key lesson to me. And just, be human.
Nikol: That’s such a powerful note to close on. Thank you for sharing something so personal and enduring.
Kostas: Absolutely
Nikol: Kosta, Thank you so much for this conversation. What really stands out is how clearly you connect the [00:33:00] strategy and the humanity parts whether it’s around AI leadership or culture.
Yeah. Thanks so much, Nicole. It’s been a pleasure. I had a wonderful time. Thanks again to you and the team for giving me the opportunity to be part of your podcast series.
All right to everyone tuning in, we’ll drop links in the show notes to learn more about Kosta’s work and how to connect further.
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