Webit 2026: Who will win the AI decade?

This closing discussion at Webbit 2026 delves into the pivotal question of who will emerge as the leaders in the AI era. The panel, consisting of industry experts, emphasizes the importance of rapidly adapting businesses that effectively integrate AI into their core operations. They explore factors such as trust, infrastructure, and regulatory frameworks that influence success in AI implementation. The conversation highlights the competition between the US and China, the challenges European economies face in keeping pace, and the necessity for organizations to clarify their strategic objectives. The speakers also address the implications of AI on human employment and societal structures while advocating for a balanced approach between technology and human talent.

And now we arrive at the final conversation of Webbit 2026. Sophia, after a full day of ideas, strategies, warnings, opportunities, and visions for the AI era, we close with one defining question. Who will win the AI decade? This is not only a question about technology. It is a question about power, infrastructure, trust, regulation, capital, talent, leadership, and execution. Because the AI era is no longer simply beginning.

It is already reorganizing economies, industries, governments, healthcare, infrastructure, and human behavior itself. The countries, companies, and leaders who move fastest now and who build responsibly, adapt intelligently, and earn trust will shape the next decade. To guide this final discussion, please welcome our moderator, Marina Techa, anchor at Nova TV. Joining her on stage, Kristoff Campich, chief executive officer of Saitel Digital, Desessie Sevdina, managing director and head of

strategy at Marsh, Sandepan Palmik, data and AI technical lead at datab bricks, and Peter Baltajv, executive and CS board chair at Oracle. Together, they will explore what separates AI winners from AI losers, whether Europe can still become an AI leader, how smaller and more agile economies like Bulgaria can move faster, and what the world may look like by 2030. Please welcome them to the stage for our

closing discussion, who will win the AI decade. Good afternoon from me again. I'm very glad to be here with all of you for our final discussion. I know that you already got the chance to talk and to hear to some of our speakers today, but now it's our uh chance uh to uh close up everything that we've heard so far. And of course you will also get

a chance to ask your questions if you still have some left. As you already heard, who will win the AI DK? This will be the core question that we are going to discuss in the next half hour. So let's start with this very question. Where do you think AI leadership will be decided over the next decade? It will be the companies that uh adapt fast, companies that

adopt fast and companies that um make AI part of their core operational system. Also company that would be able to integrate culture because a lot of companies are constitute of different generations. So we have Gen Z, millennials, uh we have baby boomers even. So they adopt and understand AI in a different way which then means that um without again I I mentioned something earlier without human without

the human intervention it wouldn't work. Uh but then there would be a different approach based on what generation we're talking about. because some of them will adopt uh some of them already use because it's part it's an extension of their the way they see things all together not only professionally. So that is a pivotal moment um and again reiterating the the structure or the the the the

maturity model would be human AI human AI. >> Thank you. Is this also your formula for the way that AI is going to work in the future or you have a different answer to the very same question where the AI future will be decided? >> I think uh you know I think I think the organizations who will succeed with AI will treat AI as an operational initiative

rather than a technical initiative. uh and what I mean by that is we as a workplace to integrate AI need to change our foundations on how we work in an organization. So whether it is uh building the right foundations uh for AI to consume. So giving AI the right kind of data the context the knowledge it needs to operate within our um having it understand our culture

uh you know and having it understand how we operate as a business and build those capabilities that can be repeatedly executed to onboard new AI use cases. >> Okay, thank you. You haven't used the word human as you did. What would be your answer to the questions? Are we taking the humans into this uh equation or we are leaving it behind for now? >> I think the

humans will come with it. uh ultimately my view and maybe the way my company's perspective is is that yeah you have to have a clear strategy. I know I'm the head of strategy so uh maybe I'm biased but I I do think you you know ultimately strategy is a coherent set of actions um that you put together as a firm or as a country as a research

laboratory and you're seeking to respond to a certain impetus or catalyst as to why. So I think the those that win with AI uh like my peer here said is really how is it going to work as part of your day-to-day your workflow your operations how does it enable you but I think you really have to be clear with the why uh the how will come because

we've always had industrial revolution then we had internet cyber now we have AI it is a tool so if you're going to win ahead in a generation it's more of how you're going to use it and why ultimately otherwise you might just be one of thousands and thousands that just have it. So I think the why is really important. >> Are these also your core questions or

you have a different answer to this one? >> I have a bit of a different view on all of it. Um I think I have a very simple answer to it when you you ask what what I think will be the next decade um where it will happen. So instead of saying companies will implement that for sure humans will be important let's hope we will all be

around in 10 years time uh no one knows in my opinion it was very simple it's going to be a race between the US and China Europe will be left behind and no one knows what's going to happen because what you could see now is um what is needed is a ton of money a ton of power energy which Europe has no uh plan to start or

has no clue. They start a task force in the in the European Union and hope something will happen. What we saw with an entropic that was the first time that one model was switched off for non- US citizen. So the people underestimate what it means if you don't build your own AI infrastructure, if you don't build your own uh data centers, if you don't build your own

power generation, you will be just left behind because of course now the models are building up. They're going to get stronger and stronger, but there will be a time when you won't need the data anymore because the models will be there. What you will need is to power uh the energy to do that. And I don't see that happening in Europe at all. That's my maybe controversial

view, but that's what I what I see what is happening. >> I feel this disagrees on that. Am I correct? >> I I wouldn't say it's a huge disagreement. I do know what you mean. I think um ultimately Europe still has today the high one of the high counts of data centers. Definitely the US has the highest uh number of them. Then it's Europe and the Middle

East and then now Asia and Asia Pacific will be growing at a faster rate uh than maybe we are. So certainly I think the European um you know energy transition though is top of mind. I think it's critical and I do think they understand the wattage that's needed to power this. But I >> Yeah, but it's it's not you can't switch on nuclear power plants in 10

days. >> Germany was very proud that they shut them down. Um not in a little bit of a trouble there. Um I think if you want to be a leader there um then you need to uh change the infrastructure completely and you need the to change the educational system because in the end who's who are the bright minds? The bright minds are are those people who maybe

are at university now or will be going to university soon. And what's happening is all the smart kids um bugger off to uh San Francisco and join one of the companies there. I mean I can give you one example. I don't know who knows about Peter Stein of Open Claw from Austria. So he was he did a big revolution with all his agents. You heard of him

I guess. So what did he do? you joined open eye in San Francisco. So because why you have a completely different tax system, why would you want to live in a high tax uh uh country if you can work from anywhere and that's what the people underestimating also in Europe. Yeah, you need to be attractive for the young people. Um because if you don't have a manual

labor, you can do the work from everywhere and I don't see that anywhere here. Sorry, don't >> Would you stand for Europe or it's already decided here? I've got a couple of couple of points to make. Um data it's a it's a hype on data center builds at the moment. Europe has a lot of I agree with you. Europe has a lot of um a lot of

data center builds initiatives at the moment. America leads Yes. Texas in particular but because of taxation and that's what America did attracted uh that's what Texas did attracted a lot of investors huge companies because of taxes. But I'd say one thing a slightly different focus on the data centers piece with AI and the advancements of AI there will be a moment where there won't be need for

so many data center infrastructures right now. >> So there's a hyper at the moment a lot of funds and a lot of companies are investing in data centers but there'll market will be oversaturated and at some point all that infrastructure will become obsolete. So we need to be aware of this and then why America is one of the biggest in data center data center field is because

of the regulation because it's one country one regulation. Europe is super fragmented. We have in America have California law for for for data privacy. Here we have GDPR but we have no capital market. >> Yeah. Yeah. So there's a lot of there's a big fragmentation from a regulatory perspective which then means more challenges. to adopt, adapt and deploy. >> Yeah. Know I agree on the data centers

like um we invested in a project will which wants to decentralize uh with old mobile phones where you can build your own rack. That's what Google is is currently going down that road as well. But that's going to be I don't know for what is needed that there will be a lot of mobile phones needed. Yeah. But I just don't see the innovation here in in >>

Okay. If you if we step Okay, you can answer and then >> very quickly. Go ahead. Yeah, there's an innovation. Take energy sectors as as an example. AI is plugged into uh can be plugged into some of the some of the company's operational backbone to reduce consumption of energy uh and switch on switch off some pivotal processes. What that means um for for that companies they may

jump start that company may jumpst start into the national grid or companies like national grid. for them to be connected. So that already provides effectiveness and efficiency powered by AI. So that's what I'd say on that. >> If we make a step back from the future and look at the reality because I guess there are still a lot of companies who are not ready to implement AI

at all. Not speaking about data centers or the future of this technology in their companies. uh tell me what do you think is the biggest readiness gap that you feel that the enterprises are facing before they at least try using K in AI in their in their companies. >> Yeah. What I see day-to-day when I work with my customers is defining success is a really tricky thing.

You put a CEO, CTO, CFO, CRO together in a room and let them describe what success means for a particular business in initiative. Everyone has a different opinion and each of these opinion are correct from this that person's perspective. So what happens ultimately is you come up with some success metrics or some definition of success which doesn't align with each and every leader and that kind of

trickles down into the further downstream decisions and the technology that you build. So I think the readiness gap that I see is defining success very clearly that can be measured over time and can be uh built upon uh you know in a in a in a in an incremental fashion. >> Thank you. Speaking about defining success, can you define the successful companies who will win in this

AIDK that we keep on talking about? Yeah, I think for me the successful companies that could implement AI are definitely those that um maybe have that communication, that internal alignment. Like speaking of government, that's probably not what they're known for. uh but companies can achieve that uh at scale and align on what success is where should the AI come in the parameters as to why they would

implement AI which I mentioned earlier um I think you know when I look at our firm and uh similar competitors we all have very similar offerings we are all implementing AI I think the danger actually is rushing to be first trying to say we've got this, we've got this and you know sending out the press releases constantly week by week is what we see. I think that's

the danger where you will stumble as a farm because I think you will lose a line of sight as to what what was the success um that we were seeking uh why why did we invest? I think speaking on investment, not only is it very costly for governments to make sure the infrastructure is in place, it's very costly for companies to spend money on AI or other

technology tools. We make human capital decisions and then we make the uh uh expenditure on technology, IT, etc. So for us, every single um dollar or euro counts and that's what we're always thinking about. why are we doing this? I think if you don't have that clear uh coherent system internally and why something fits and works for you, um that's that's probably where I think companies will

fail. But those who s are successful, they have a very clear vision as to why they implement something, how it enables them. It's very then difficult to replicate. So I think when we talk about strategy, it's always about competitiveness. Why should someone come to my firm as opposed to my competitor that can offer something? But it's that almost intangible coherence and that's where you win because we

may offer a product, we may uh offer consulting services because I have the human experts, but they may be enabled by AI that it's just so hard to uh replicate that combination elsewhere. you speak about this competitive advantage and how far do you think AI can be and assure this competitive advantage and not the opposite? >> Well, I think it's just one one one point where when

when when you ask before what what do you think is going to be the most successful companies in the future? I mean always the same the one with the highest revenues and the one with the highest market cap. Yeah. I mean SpaceX or Antropic is trading on hot air at the trillion with everyone with a lot of opium there. You never know. But I think what the

people underestimate, you had a slide that Marsh has 95,000 employees. How many of that are in middle and back office? 60,000. >> 70,000. In 3 years, four years, 5 years, there won't be any back office anymore middle man. uh mid office in any of the insurance companies banking where you have like now twothirds of the people doing very manual jobs which won't exist anymore. Of course, the

profit will skyrocket at at this time. But the problem, you all of a sudden have an army of unemployed people with in their probably I don't know 30s between 50s and you don't know what to do with them. And I think this is the much bigger issue which we are facing. I mean the success metrics will always be the same as long as we're in a free

market society. The question is if AI will exist in a free market society in 10 years time. This is something I can't answer but I have heard a lot of talks where some very smart AI people have a very doom and gloom scenario which says if this continues on this log scale and very few people can think exponentially I can't but those people can and what they

see could be a very different future what we're seeing right now >> because Peter you said that humanism is a very important word in this uh equation. Uh does it sound the future scenario the way that Crystal described it? >> I don't want to be on a negative side. Um I firmly believe that the grip we have the grip on this right now as a process and

as a to what extent we let it run. There's always going to be the uh the desire for someone to be faster, bigger, better, well positioned that we cannot control. You're right about the fact that the back office will probably uh be mostly automated in in it's happening now actually with banking. But then there's also the component of adaptability and there's also the component of how do

we use our transferable skills as people that may have been impacted by that and then how do we what do we make of that by using AI AI and this is probably an HR problem rather than a uh an AI problem because HR specialist would need to think how do how do I equip and arm my my my my my labor force. >> But I I think

sorry >> to be competitive. >> Just just one thing. I think it's not even an HR problem. I think it's a societal problem. I >> I agree actually HR won't solve uh the army of middle management not knowing what to do >> probably. I'm thinking business-wise, but then we can expand that into it's a society problem. Um but if we look at something else, there's industries that

have uh scarcity of labor. um that's that doesn't need technology and for example low-killed labor in the UK um there's there's scarcity of that people that build buildings and businesses will always need a physical space of whether that's I don't know places we live in and etc. So there's going to be a bit of a shock like anything industrial revolution created a shock right but people people

didn't cease to exist they just transferred and one of we talked about that earlier one of the biggest advantage of us as humans is our adaptability and ability to evolve so I mean future is not dark in my opinion but let's see >> but let's be honest do big companies care about this uh army of unemployed people that Christoph just talked about and are companies the ones

who are going to solve the societal problems I guess. No. So, uh where should companies in your perspective direct their uh their goals to care about the people that are working for them at the moment or invest in uh technological solutions that would move them forward as a company? Um I so I'm I'm on the when when you bring human into AI and like we talk about

whether AI is going to replace the human workforce and I'm I'm kind of in the cliche camp really. So so like I I always uh I'm I'm very bullish that humans will evolve with how as AI gets into the work space and what that means is we will bring in new skills and new roles. Yes, there will be shock. There will be layoffs and we are already

seeing it. But gradually I'm I'm already seeing a lot of young people working with AI bringing in really fresh ideas in every business and I wonder like how they have how fast they have caught up. So I think uh when it comes to businesses investing in technology versus human talent, I think it needs to happen in a balance. Yes, technology will come in. But how do we

ultimately what I believe is technology is for the societal improvement and progress. What leaders need to decide on is what success looks like in that front. We work backwards from business workflows. We into deciding where technology will take a part in that business workflows but where humans will take a part and override some of those decisions that AI make as well. >> So it's it's it's a

balance that needs to be hit. You spoke a lot about the disadvantages that the Europe is facing at the moment, but do you think that smaller economies like ours here in Bulgaria also have some competitive advantages or we should prepare for the worst here? >> No, I don't think so. >> Expand, please. >> No, I mean, look, it's I I look, I come from Austria. We're roughly

the same amount of people, roughly the same economy. Maybe we're still a little bit richer, but in the end, it's pretty much the same. Yeah, you've better food here. It's more tasty. Wine is same, I guess. >> yours is good as well. >> Yeah. No, you can see. But the thing is, no, there's no advantage of being a small country. There's no zero. It's like you don't

have the you can't invest in in infrastructure as needed. You need to be in a bigger uh environment for those kind of um for those kind of things. I mean I I I repeat myself when I say what you need to do is um try to push universities, try to research and try to keep the the people here. But I mean you probably have have many example

of people um going are very smart going to university there getting an offer from Silicon Valley and off they go. they you know you can't keep them here >> yeah but still now there is a trend that more and more people are coming back for a smaller country like Bulgaria just because you can also now work from your home thanks to the technologies >> yeah but it's

it's also one thing is is like where you have the concentration of minds like in Silicon Valley and they tried to re recreate it in in in Europe but it it never it didn't happen anywhere like because people think yeah let's to um Silicon Valley in I don't know where London or whatever or Frankfurt or whatever it just you need it's it's a so look the Americans

say and I'm not American you're not American either. >> I am. >> You are. So you probably you should answer that. It's like okay you have three failures then you post about your failures at dinner parties and then you go to your first startup and then you s succeed. In Europe you have one failure you get shot in the foot because it's a shame. That's the the

Americans have a mentality of w winning at all costs. The Europeans are, you know, they're shy. They're, you know, they they they want to be nice and polite and it's a change is needed to be successful. I don't know if it's possible or not. You should answer that for Bulgaria. >> Can uh Europe and Bulgaria do something in terms of being uh faster and more competitive and

more interesting, let's say, from from a technological point of view? >> Yeah, sure. um you know I think there is a tension that we should be mindful of always whether it's in business or innovation it is the short term and the long term right so I know the short term and I spoke about that earlier it is very frustrating at times how slow it may feel uh

how long it takes especially because Europe has a lot more compliance in the US you know I think it would be hard to change quickly our cultural differences you know me ba being based in uh London for a while. Of course, there's cultural differences. As American, I'm very optimistic. I want to go fast. I don't like anyone saying no to me. >> Um but I think uh

as a European, of course, I know that the long term is that yes, the compliance is built to protect people. Uh there's social benefits that Americans do not have, right? So um there's pluses and minuses where Americans probably would wish that they had some of the benefits and the security uh of their um you know benefits and lifestyle and pensions and etc that uh Europeans have. So

it is a very capitalist society. We don't necessarily have that in Europe. It doesn't mean that there's no innovation right there. Businesses continue to grow. I think there's very very intelligent people. So, I think me coming back from 10 years old to I'm not going to say my age, but I'm in my 30s now. Um, but I can see the progress and how um, you know, I

I do see people returning to Bulgaria. I see a lot of foreigners even today that have actually moved to Bulgaria to start up businesses in technology. uh I have friends who run global startups who have offices in Bulgaria because of the software mindset and that science and mathematics education. So I don't think uh it's a lost cause. I think it's the frustration of Europeans are a bit

more we think of the long term and how is it secure? Is it safe? Is it going to work? Americans are very shortterm focused. So it's like go go and then let's just see how it goes. But if something goes wrong then a couple year years they'll have to say oh we have to stop this and now there's regulations and laws in place. >> Okay. Because we

have only four minutes left. Can you one sent I just want to add one thing. I think it can it can easily be fixed because what the people underestimate is the European market is bigger than the American market. We have like I don't know 380 people whatever million people and you need a common capital market because of the scarcity of capital what America has. Yeah. and a

reg and you need to break down the the the regulatory burdens then it could work. But good luck for um >> impossible to happen anyway. I got your point. I think we all did. Uh so we have four more minutes. So uh one minute each for our last question. What do you think is the one thing that each leader in this room should do or invest in

in the next 12 months as to prepare for the AA I think if you look at it from an executive perspective, you you talked about the fact that there's no common opinion about um what's the strategy going to be and I think that this is the key to success aligning on the business objectives and looking at the business outcome almost projecting it and then working reverse engineer

the whole the whole process to achieve it. So I think that this will be the key uh and then again a key belief that people are the driver of that call me knife I don't know but also at the same time touching on the topic previously it's all about the choice yes there's always going to be better places for us to work there's always going to be

better opportunities somewhere else but there's a point and I I come from a position where I've chosen to be somewhere else rather than the country I was born in. But at the same time, there was always coming a moment where you want to create something rather than to to to take. Um so I think that at some point choice becomes personal and if it comes down to

us having ability to make a change. Um I think that we should do that. >> Okay. Your answer. >> Yeah. So uh I regularly work on technical projects. So I'll give you technical answer to this. Um I think uh to be successful uh you need to define success metrics. What success means on a particular initiative? You have to build the measurement infrastructure to actually measure that in

an ongoing basis. So I call it the data to decision loop. What that means is that in your organization, do you have the data to trace back the decisions that you make and have you can you look at the data and actually decide what you want to decide on on a particular business initiative and only then once you have these two pieces success metrics decision loop you

think about the technology that comes last don't think about the model in the beginning it's just an API access away to use a model if you have a measurement infrastructure you can actually measure which model works better for different use cases. I think so start from success, build the measurement architecture and then choose technology and create this loop so that it can be the foundation for success.

>> Okay, thank you Desi. Uh my response would be maybe give as a leader give your team time or give yourself time in the next 12 months to really think about um you know I'll stay on the topic of AI but think about where do you need it educate yourself and don't be a blocker for your team and your colleagues to bring AI in um I think

the leadership you know the seauite executives of uh Marsh globally um there's hours spent on AI and educating so that we don't block those below us the younger generation or just those are more curious and work with it dayto-day uh the worst thing that you can do is actually block teams from being innovative uh bringing ideas to the business looking at a particular uh problem to be

solved. It's very easy for us to come top down and say, "Oh, just buy a model." And everyone gets it. That that just doesn't solve much. It's not as innovative either. So, I for the next 12 months, I would encourage everyone just to make sure that you're educating yourself by helping your teams get educated, find expertise, seek out content, and then have that success story really mapped

out uh and and really think about where you can invest in the future. >> Okay. your last sentence. >> Yeah. I mean I would make it even more simple. I think um what what you should do is um look after yourself because this generation or people around here at this age will live for a very long time um due to changes in healthcare. Also AI will help

for that. pursue your passion. Be it the yoga teacher, tennis coach, because in the end people um will like to hang out with each other, not with robots or uh chatbots. And um don't worry too much um because no one knows what's going to happen anyway and do what you enjoy. >> Okay. Thank you very much to all four of you. Before we move to the robots

that are about to conquer the stage in a minute or two, I would like to give two minutes for questions in case there are some questions. Be brave. Come on. You have the best experts now on stage. Someone >> Everyone is tired. Yeah, >> they know everything. That's why they don't ask questions. Okay. So if there are no questions from the audience then uh please applaud our

guest at our last um section of the conference. I think they did great and uh I hope they will answer your questions afterwards in case you are brave enough to ask them afterwards. Thank you very much once again. Thank >> Thank you. Thank you. >> The AI decade has begun.