Good morning, good afternoon, and good evening, everyone, wherever you are joining around the world.It's a real pleasure to being part of, you know, together with you, this woman and tech community, a community that's actively shaping the future of technology with the female strong. Let me briefly introduce myself. This is Omi Khoruju. I'm joining to you today from Dublin, Ireland, and I work, intersection of AI privacy and cybersecurity, helping organizations build systems and not compliant what truly trustworthy and increasingly complex road, you know, everything is changing nowadays. But, today, of course, it's about AI governance, insucy, balancing risk, and adaptability of innovation. I just try to give to you the background stories of what we are talking about, especially in AI about emerging technologies in boardrooms.

We've got just twenty minutes, you know, that. So I just wanna jump the top topic fastly. So we are no longer living in a world where systems are simply connected. We are living in a world that is interconnected, but not aligned. The and the enter of everything, the center of the seats AI, not just as a tool because lots of people think it's just a tool, just a platform, it's just technology, but after all, it's something that shaping the decisions and brings critical question. If technology is a part of decision making today's, how do we build trust in these systems and making those everyday daily and business decisions? If we continue this next generation in information environment, truly when you are searching about, you know, next generation information environments, in the past, I don't know, maybe we can say five years ago or three years ago, we just can say, oh, it's an Internet and Internet never forgets.

And if you are sharing anything, any data, any information on internet, it means that, yeah, you're connected all over the world. And let me, let, let, let me suggest one book about that. I really like this Friedman book. He's calling it world is flat. So maybe it was right, but nowadays, we are using AI. So that is why we are calling that next generation information environment. According to NATO's strategic communication center of excellence, reports they're selling, we are saying that we are operating, and in in what describe this next generation information is not just evolution of, communication technologies. It is a structural transformation in how information is created, distributed, and operationalized. So in here you can see a contest of ecosystem. Information is no longer natural because in the past we were maybe you remember that we were calling all datas are generic and the raw data and the synthetic data.

But today, we are calling all of them structural data and infrared data. It means that all AI tools and AI applications just trying to collect all your information from you. And they're just trying to reflect back to you this infrared data. They're just interpreting you, how you are behaving, what is your emotional differences, your facial recognition, recognitions, everything is a data to feed this kind of systems. And of course, state and non state actors actively manipulated because nowadays you're living in a one country or one continent and your local legislation generally trying to put some very domestic rules to manage technologies, but after all, look around you. US in other side, China, European side, and in other Asian countries, all of them is just trying to prepare their own frameworks. So it means that state and non state actors actively manipulate it.

I mean that when you're creating any rules on your Internet, on your emerging technology systems, after all, tomorrow, you have no idea how you can manipulate it when you're using your applications. So it depends on your government. It depends on your location. And information nowadays are engineered. It designed, optimized, and continuously adapted in real time. This means we are no longer consuming information as a reflection of reality. We are interacting with systems that actively construct or interpretations of reality for us. I just trying to mean that when you're reading something, when you are just trying to swipe or just, you know, putting it like any visuals, sometimes they are not just a reflection of reality. Sometimes you're liking something, you're swapping something that created by AI, but using our very tailor made information or data. And of course, we are saying lots of we are hearing and saying, and every day, we are just trying to consume that kind of information about AI agents and agenting AI.

It's not the same thing because it's a big confusion. I think nowadays, people generally thinking it's the same meaning, but not because AI agents are created on behalf of, different platforms. They can repeat your work, and that is why every day, we are just saying something, asking to each other, are we losing our job? And agenting AI is different thing because it is creating an environment. And if you wanna use some different platforms, it's just giving back to you a big platform technology to create your own data or AI technology. And, of course, an algorithmic battle because AI systems right now generated content and not accurate, curates visibility and personalized exposure and interact with each other scale.

This creates what can only be described as an algorithmic environment, a space. Maybe we can say attention becomes currency, visibility becomes power, and influence becomes and measurable strategic assets. So in here, you can see AI systems compete for attention. Machines influence other machines. Information dominance, algorithmic advantage. So all all of them is just trying to give backstory about the machines are not today enabled communication. They are generated decide and influence. And here you can see fragmentation of reality and trust because fragmentation of reality, the hyper personalized content, parallel individual experience, and no shared truth baseline. It means that when you are using any contaminant information on the AI systems, it means that it can be synthetic or manipulated data. So today, we are calling that data poisoning and adversarial inputs and outputs distorted with reality. And what does it mean?

It means that all different AI agent systems, all different AI platforms can include your own companies or your corporate companies, cybersecurity, privacy, or governance systems. So today I need to divide into some different area because in the board level degree, we generally just trying to understand what is the benefits from AI because lots of companies and lots of managers, directors, or, you know, board level personalities had no idea about AI technologies.

But after all, they have to be part of, especially, that kind of, you know, new era. But they generally just asking which technology is right and fits their companies. So nowadays, we are seeing lots of that kind of, you know, bad decision because suddenly without understanding their infrastructure maturities, They generally just trying to embed AI systems, embed AI technologies, embed AI chatbots, whatever you wanna say. And suddenly, after they experienced, you know, some data breaches, some adversarial systems or software problems on their systems, they could understand that, oh, they've got a penetration point or jumping point in the middle of their infrastructure, but when they embed this AI technologies, it is just exposed material world.

So the crisis of knowledge authority is another thing. Trust shifts from institutions to AI systems and competing through the engines. Today, our biggest problem is understanding the reality and the fake information. So lots of companies like Microsoft, like Meta, like Facebook, all that kind of companies which are working and creating their own businesses on the top of our datas. They are right now just trying to filter information and understand the content differences. And the social impact, of course, we generally so tend to speaking about the technology background, the technical stuff, cybersecurity, and privacy. But after all, when you're just trying to understand the background stories of local legislation especially, most of the things just affecting social impacts.

So today, declining institutional trust, cognitive cognitive manipulation, polarization, and fragmentation, all of them is just affecting all people around you. And today, maybe you heard, maybe you are not, but one of the most important description about the democracy is data democratization. Because when we are creating an AI systems, we generally just trying to hear some words, some majority like US, like China, like you, but we generally couldn't listen, couldn't understand. Sometimes we are just ignoring lots of data from another part of the world. So that is why we are calling it as a new gods, like the superintelligence because kind of systems generally knows everything better than you, always had an answer to your questions and always trying to oversee what is the things that's going on around you. But after all, if data democratizations is not on the board, it's not a new god. It sees a tyranny.

So data democratization is one of the biggest feature problem to all of us. So information is no longer neutral. It is engineered. And the global perspective, look at in here, I just try to put to the main players, flags on the picture, but after all, it's so obvious that every day we are hearing the news on the TV, you know, when you're just trying to read some articles every day, they are changing their ideas.

But when the big player change their ideas about technology, they generally causing another war around the world. You know, that because the new biggest power right now is not just the force military things. Of course, the technology power, of course, AI, and of course, emerging technologies are on leverage. So in here, you can see a world that no longer operates as one fragmentation is not now the new normal. It means that ultimately, digital trust across regions build a very different foundation. In EU, of course, last three years, we are just speaking about just talking about EU AI act, risk based digital sovereignty.

And we're just trying to get the background stories about how can we manage AI risks. They give us four different levels, and we just try to prohibit something, the high high levels risk. AI systems generally just trying to, you know, control every day. We still do not have any major and the mandatory audit about that. But every day, they are just trying to represent and put different kind of directives to support the legislation. If you ask me, of course, you based on human rights and regulatory, positions. Of course, this is the best of especially for the humanity. But after all, we still lack of awareness about lots of things. And on the other hand, in US, on speed, innovation, and private sector is our majority.

And winning the race, winning the AI race, America's AI action plan. So it means that after all, America just trying to find a way to, you know, getting this race or winning the, you know, this war. And in The US, on speed innovation and private sector strength, meaning to, maybe they can say AI action plan, US generally just trying to find a way to support in different sectors and never trying to use, maybe the humanity power or human dignity. They generally just putting the capitalism system on the top of everything. So in China, on the centralized control and public infrastructure, global AI governance action plan, China actually creates a perfect framework to their selves. But after all, it's so obvious. I just try to summarize everything in here.

The US says move fast and fall not fall behind because after all, this is the one of the biggest winning race around the world. And China says align with state and global harmony because they just wanna observe, understand, and put the government on the top of everything. And in here, European part, we say is protect rights and build trust first. And in here, you can see there are the red dots just trying to show to you what kind of countries right now have different AI legislations and the global landscape of AI regulations. And why the question is why traditional governance has failed because fragmented regulations across regions, siloed risk management for AI, for privacy, for cybersecurity, and static policies in dynamic AI environments. Because lots of companies, lots of institutions still still thinking that they can manage AI kind of emerging technologies and dynamic platforms with static policies and the legislations. No.

We cannot do. Then go and write lots of different white papers and try to manage that kind of manipulated information. You cannot. So that is why everyday you're just saying multidisciplinary work is everything. Your legal team, your compliance team, your cybersecurity software team, they have to work together. This harmonization is the majority for all over the world. And what must change? First of all, integrated governance, align AI, privacy, cyber risk, break organizational silos, and continuous oversight, monitor AI across it is this is a life cycle. You cannot say just, yeah, yeah, in the set one, we control everything and tomorrow everything will be go like that. But no. Because every day, every technology is manipulated, especially in AI. It is learning itself. We created AI, but it creates itself again and again in just one day.

And from data to decision, of course of course, it's the biggest thing because today, when you are trying to write an email, when you are creating white paper, when you are creating any reports on your business, and every day when you are just trying to decide to go any restaurants with your boyfriend, your wife, husband, whatever.

So the decision making, one of the biggest outcomes, the AI driven technology. So we have to be trained our people. We have to aware about the risks. And in here, you can see why I'm saying something about multidisciplinary work because especially from board level, the risk compliance community, ethics advisory community, digital governance community, audit community, internal and external audit community, and all different kind of service lines.

You need all of them because when you implant, when you integrate any AI systems in your business, you cannot say, oh, the procurement service don't use it or other domain, you know, leaders stop using AI. Everybody using in your company. So domain specific communities chaired by domain leads is a must think. And the emergence of AI governance as giving provinces the need to coordinate between commercial functions and compliance driven functions is a musting for our company. And in here, you can see there are different percentages from different continents, from different location all over the world because the contribution of AI governance functions globally to innovation and business growth. You can see the percentage in here. Of course, the biggest percentage is going especially to, Africa kind of countries and South America kind of company countries, or continents. Because when you're just trying to strict legislation, when you're trying to put, big mandatories, we generally just, you know, slowing down a little bit innovation.

But you we cannot sacrifice cybersecurity or privacy because of innovation. In the future of trust, what's ahead and what this means? What's ahead? We will see lots of increasing fragmentation, AI driven uncertainty, expanding attack services, you will see this year, next year. And what does it mean to us? To us becomes competitive advantage. Governance becomes a differentiator, not just for us all over the world, and ethics becomes a strategy. My time is up. Thank you very much for listening to me. If you have any question, please reach out to me on LinkedIn or women in tech platform, and have fun and enjoy the conference all day long. Thank you very much.