Speaker A
So I would kindly invite to the stage my dear panelists Audrey Vanson and Margarita.
Panel discussion on innovation, technology, and AI focusing on leadership, implementation, and future trends across continents.
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Key Takeaways
- Leadership and organizational culture are more critical than technology in successful AI implementation.
- Involving teams early and managing change effectively reduces resistance and increases adoption.
- AI is rapidly transforming industries, but practical deployment remains a challenge for many companies.
- Global innovation dynamics require understanding regional strengths, compliance, and collaboration opportunities.
- Future AI trends will focus on world models and teaching AI through physical reality rather than language.
What the video covers
- The panel features experts Audrey Vanson and Margarita discussing innovation and technology with a focus on AI and its global impact.
- Patricia Gonzal introduces key statistics highlighting the rapid growth of AI funding, SpaceX IPO, and breakthroughs like AlphaFold in healthcare.
- Audrey Vanson emphasizes that successful AI implementation depends on leadership, organizational readiness, culture, and change management rather than technology alone.
- Leadership should embrace AI as a tool with curiosity rather than fear, empowering teams and involving them early in design and decision-making.
- Change management is critical, with resistance from employees being a major cause of failure in AI projects.
- Margarita discusses the challenges of moving innovation from lab research to practical, everyday applications, especially in emerging technologies like 6G and quantum.
- The panel touches on data governance, compliance, and the importance of integrating these into AI strategies.
- Discussions include the global dynamics of AI innovation, particularly between the US, China, Europe, and Africa.
- The panel highlights the importance of collaboration, regulatory frameworks like GDPR, and the unique challenges faced by different regions.
- The conversation also covers the future of work, AI sovereignty, and how organizations can better prepare for technological disruptions.
Chapters
- 00:00Introduction and Panelist Welcome
- 02:22AI Breakthroughs and Industry Trends
- 04:35Challenges in AI Implementation
- 06:46Leadership and Organizational Readiness
- 09:04Importance of Change Management
- 13:04Innovation from Lab to Market
- 17:58Data Compliance and Governance
- 18:43Global AI Innovation and Regional Perspectives
- 21:42Future of AI and Work
Full Transcript — Download SRT & Markdown
Speaker A
Okay. Are we hug? Yes. Uh yes, you can. Hi. So good afternoon, everyone. It is my pleasure to welcome you to the innovation and technology panel. Uh, one of the coolest topics, one of the most engaging topics, but also a panel that
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has majority female today. So congratulations. [applause] My name is Patricia Gonzal. I work on innovation and technology in Geneva with an international organization. Um, but as been said previously, I'm here representing the Young Diaspora Council.
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And joining me here today are three people who don't only talk about technology. They build it, they fund it, and they deploy it across two continents. Welcome Audrey. Welcome Vanson. Welcome Margarita.
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So let me set the stage and the context here around innovation, technology and obviously AI. Uh, and let me start with three numbers.
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SpaceX had the biggest IPO in history just one month ago, 75 billion, a number that just a couple of years ago was inimaginable.
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Uh, AI is crowding and sourcing 61% of the global venture capital funding, an amount that totals 259 billion, a double in three years or just from three years ago, and unicorns are totaling or the value of unicorns is
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totaling 7.5 trillion, uh, more than two trillion increase in one year. So the money and the financials are increasing as we speak. But science is also keeping pace. AlphaFold, for example, uh, the AI, uh, company incubated inside of DeepMind
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just decoded two years ago 200 million proteins. Uh, so decades of lab work are now being condensed into weeks or even years, and this has huge implications in the healthcare field. Um, and the implication was obviously that the Nobel
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Chemistry Prize went into AlphaFold and its founder. So things that looked like sci-fi just two years ago now feel like the daily reality. And we believe that the next wave from what we're seeing in the industry as well with the World
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Economic Forum top 10 trends report is that the next wave is going to be world models. So you're teaching robots, you're teaching factories on how to learn AI not through language but to physical reality. So this is a bit of
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the context set. At the same time, we have here a bit of a paradox because outside the tech is going faster and faster but inside we're still adapting a bit more slowly and companies are having some trouble turning AI into results. Uh,
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every week we hear as well about sovereignty in AI. We hear a generation asking about work and what the future of work will look like. So our job in this panel is separating a bit the signal from the noise. And let's start with a
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topic that every executive knows well: implementation. So welcome Audrey again. You're the CEO of Systemic Logic. You grew the company from eight employees into 200 people. Uh, you work across financial services and banks in Africa and globally. So you see
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this problem or these issues with implementation and operationalization daily, uh, with MIT, for example, saying that only 5% of AI pilots reach production in value. What in your opinion separates the companies that you work with, uh, from the ones that make it
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work in terms of AI and technology and the ones that get stuck? Thank you so much, first of all, for the organizers for getting us here and to you. It's always fun when I'm moderated by younger Gen Z because it means it is
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the right panel. So thank you for this. What makes it work and what makes it not work? Um, it's a conversation that I continuously drive every time I'm engaging with the C-suite, with different executives because it really has to
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start away from the technology to the organization. So the issues that we already know. So what I'm going to say here is not new issues such as leadership, organizational readiness, the culture of the organization and more important the integration of
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change management in that process or not. So let's start with leadership. For the companies that have the privilege of engaging, it's a leadership that's embracing of both what they know and what they don't know. So an integrated approach to the starting point for most
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of us here is to ask the question: Do I understand what AI is because it's actually the tool or am I scared of what AI I'm hearing my team engaging me around? Because if you understand it as a tool, you walk into
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those conversations around asking a different question: Are we organizationally ready for this tool? So I spend a lot of time trying to help us, but a lot of my clients move away from the fear and more to the curiosity. So
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the leadership component is key because it means that you're directing the resources correctly. The second thing is the tools need to work with humans. So people are a critical component to that.
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Trust your organization to hire the best people. Financial services are well known to drive both a leadership component in understanding the governance components of it but also have the resources to hire the best. So we go and hire the best and that my
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clients have succeeded have hired the best and understood that we need to empower those that are coming to do the work and understand both in terms of the selection of the technology as a tool and the implementation of that
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technology. An example of that, um, in terms of forgetting that that's important: if you don't involve your team around the design phase, it means that you're imposing a decision and I, I repeat that very slowly. You're imposing a decision from
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your boardroom discussions that around what tools to use as opposed to understanding both the opportunity, the risks and the decisions that are required to impact change. If I come back to the issue of change management itself, more than 70% of my clients where it has
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failed versus where it's worked, it's a resistance from their own people. We prepare our teams to expect the change but not be the change around AI and the models. So in summary around that I would urge us all until I come
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back that I haven't mentioned anything about the tech. I haven't said AI. I haven't, I haven't spoken the jargon. I haven't spoken about the percentages. Just simply what will make you succeed is a leadership that embraces the awareness
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of the shift vis-à-vis the readiness of your organization. Number one. Number two, an organization that empowers its people across the organization to make the decisions around the partnerships with the vendors that you choose to work with, but also
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understanding the design and more important: are we ready? Because being ready is the difference between having the right data governance and not having the right data governance. Being ready is the difference between being able to, uh, identify the, go, the, the, the, the
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transactional need from a customer point of view which you're not aware of but the people at the bottom actually understand that. And then finally from a change management point of view is making sure that the culture you embed
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is one where the ideas don't always come from you. It's not the tech, it's the people and it's the organization. Thank you very much, Audrey.
Speaker A
Round of applause. [applause] So leadership, culture, change management beyond the technology in itself. And it's interesting that you mentioned compliance and data compliance as well because this is a topic that we will focus on, uh, in the next, uh, part of
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the panel. Margarita, back to you. Um, you are leading innovation strategy at Altis Labs, Portugal's top patent filer. Um, the lab focuses on Geni 6G and quantum. You see it from the ground.
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What does it take for an innovation to move from lab into everyday use? Thank you, Patricia, and thank you to the council for the kind invitation to be here again in this wonderful event. We were talking before the panel that we
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decided to be consistent with the idea of respecting, uh, and honoring, uh, the linguistic and cultural differences that we have in the diaspora. So I will be delighted to have the role of changing to Portuguese during my intervention. Um
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although I will be using a lot of buzzwords and some expressions in English. Um, start Antigga.
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Yes. Incremental Natural skin for organized. Longterm innovation shortterm businessoriented approach. Thank you very much, Margarava. And and you're right, there's a lot of cross uh cross functioning uh between what you just said and uh and what Audrey just
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said as well. And it's important in your area to balance the shortterm needs versus the long-term needs. Um so even for the builders uh the adoption is a journey. Let's let's bring Vanson's view as an investor. You are the managing
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director of chapter 54 the first accelerator that brings EU scaleups into Africa. It's part of part uh and as you mentioned as well part was one of the early investors in uh in wave uh one of the first unicorns in in Africa. So we
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see a lot of these conversations in AI and innovation and technology gravitating around the US and China giants. But I would be curious and I think the audience would be curious here as well to see what dynamism do you see
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with the ventures with the entrepreneurs with the startups that you're working on? What are you know things that they're doing in from a startup lens that big companies can learn from?
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So it's true that at chapter 54 uh we have the pleasure to to work with European scaleup startups wanting to expand into Africa. Every year we work with 10 to 15 companies which means that we we we have a good vision of what are
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the needs and uh what works and don't works when you are a European scaleup expanding and the continent and things were a little bit blurry okay I would say until the beginning of the year but now the things are clearer um
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I would say that the most successful companies uh which are related to AI are B2B companies Um and to to be relevant in AI, you have access to you have to process data. And the most performing companies in Africa are
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companies which have an access to proprietary data. And I would I would go even further. I would say that the key uh is to have access to proprietary and even physical data. I'm going to give you two examples. The first example it's
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a Portuguese startup uh called Brainer. They are based in LRA. Uh they have designed a very smart solution for the food industry for the bottling industry and uh thanks to an access to the information coming from from the
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equipment of these food manufacturers. They can process this information and they can improve the productivity of these companies. and they already have some clients in uh in Africa and last time I discussed with them they were on their way to Mozambi and it was just a
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few hours ago. A second example is one of the companies that we accelerate uh at chapter 54 and here is going to be a little bit painful for me because I'm going to talk about football. So this company it's a sport company uh whose
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business angel is the legend Michael Owen. Maybe you have noticed that more and more football players uh they have trackers between their shoulders. Okay.
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And uh this company that we accelerate it's a Bulgarian startup called Barin Sports. They equipped all the major clubs of Eastern Europe, Central Europe, Greece uh and uh and Turkey. And by combining the GPS information from the trackers and the data science that they
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have built uh they are able to decrease by 40% the risk of non-cont injuries because most of the football players they are hurt not during the games but during the trainings or because they train too much. Okay. And now uh their
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solution is used by some academies in Morocco and once again by uh in Mozambique by the national team. So uh AI is one thing but if you want to have a competitive H you have to secure an access to uh the data and the
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proprietary data of your end client. Thank you so much Vona and very timely example with the World Cup just happening right now on the football front and actually also very timely example because the next topic that we're going to discuss is this
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sovereignty topic and sovereignty is attached to data is attached to privacy as well. So whenever we we open a newspaper at least in Europe uh whenever we hear a politician or a governor speak we immediately see this sovereignty and
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tied to the sovereignty is also open models. Um so sovereignty is not just about the LLMs, the large language models, the open AIs, the clouds. It's actually around the infrastructure as well, the chip makers, who provides the compute, who has the energy, who has the
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data. And this has been a bit of a worrying topic. Um and I'm curious as well to see how that is tackled, how that is approached uh in Africa. But it has been a a worrying topic because uh
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more than half 75% of the AI venture capital concentration is in the US 6% in the EU and 5% in China. Uh and around AI concentration I mean this infrastructure layer as well. So we see two trends here. One of them is around open models
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uh and people saying open models is the way. Llama deep are examples. The other way is around national models and we have an example of that is Mistral. Uh the other example more recently is Amalia in Portugal with our
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prime minister calling it uh an important step to strategic autonomy. Now conscious this topic is controversial but this topic is also very much in the newspaper daily. So I wanted to bring it in um in here and perhaps starting with Margarita. You
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work at an European infrastructure company. What does European tech sovereignty mean in practice uh for you?
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And do you think uh open models like Amalia have a fit in it? Um, who knows?
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Standalone topic. Guarantee ownership data 6G. G. Eugene. Vendors competitive. infrastructure digital transport underwater connectivity.
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Um, camp. Fore speech. Fore continent. Africch. Thank you so much for that very rich perspective and also for a reminder including for me that sovereignty has been here for a long time uh and sovereignty not only in AI and in Claude
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and thank you very much for pointing as well for specific examples of what Altis is doing in this area and opening as well here the door for collaboration perhaps anyone in the audience that is is happy to have a further conversation
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with Margarita in this area. I wanted to bring the conversation back to the other side of the Mediterranean um and ask perhaps Monsson and Audrey a bit of the same question that is is sovereignty discussed as intensely in in the African
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uh ecosystem. um how present is especially in the area of financial services for you Audrey this this question of data sovereignty and compliance specifically because it's a very complianceheavy heavy industry and are open models perhaps an opportunity for for African financial services
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and I think I think for today's purposes and the audience um also debunking what we're saying is important um for everyone out there picture this every single data piece information that you put into your phone, your computer that you engage
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with, anyone that's gathering information from you is not owned or is not sitting in your country. Imagine how that makes you feel. So that's a starting point. So the risks around the conversation around sovereign the so sovereignity is from an
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African context even more frightening because to be able to be prepared around how to deal on an open component one has to realize back to the issue of data what the implications would be if that picture went blank.
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Issues of risk, cyber risk become a factor around that issues. Every single aspect of being and living is a challenge in a continent where just the basic data governance is almost non-existent. South Africa has 61 data centers. We won't even talk about
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the climate implications of those data centers. So when you talk about where actually the data resides and the governance around that yes those conversations it's a yes and no that those conversations would take place in an institution an organization but
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mostly no. So banks as an example possibly yes because banks are the most regulated financial services are all about managing risk effectively. So the conversations might take place because there's a compliance component that comes to it. There's a
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regulatory component that comes to it, but we need to move beyond the regulation and bring it down to the basics, the practicality of when you wake up that day and you have no control of every single information of your
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citizens. Now, it sounds like doomsday, but it's a reality. So, don't so let we can paint big words here, but let's be realistic around that. So, where does the the the the pathway then [clears throat] come through for those
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conversations around EU Africa? um uh component. It means that we need to have be having conversations around how we create partnerships, collaborations, build highways of information to partner. Margarita, I was listening to you and I want to partner with you. I
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want to figure out how we engage. I'm welcome. Because in those partnerships, we will also take away the monopoly.
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So yes, in the banks the conversations take place from a compliance point of view. But then enters the second part of the debate which is should I be allowed to own my information because open sourc is really in a simple layman times
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means that you can now build create gather your own information if I'm at bank keep it with me I have access to it whenever I want to. That sounds great but we've been doing that also for the longest time but we created
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risks that came into that as well. So cyber security risks that emerge is because we are we think we have data leaks but we 90% unstructured data meaning that I have multiple information of the same thing of you and the same
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business with no single view of you as a customer. So, it's much easier for a white hacker, dack hacker to come in and clone me and choose to be me because we've created spaces of information that are unstructured and introduced risk in
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a risk management business model. So my parting words on that I can't emphasize strongly the collaborative approaches.
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I can't emphasize even more the opportunities at an individual level because sovereign issues and open issues require us the consumers to stand up as we do with every single one of our governments and demand that the right decisions are made around my
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information. Interesting that you mentioned this unstructuring of data and increased cyber security risk tied to open models.
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Obviously the builders of this open source models don't mention this upfront. Very interesting perspective as well from the financial services front and from what you see on the upwind models front. Fans I wanted to bring the conversation of sovereignty to you
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conscious that you deal with builders every day. What are you seeing in this ecosystems of of builders? Is this a topic being discussed? Does this open opportunities for the startups and for the entrepreneurs that you're working with?
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Yes, it opens opportunities for European companies. Why? Let's imagine that you are an African regulator and you have to deal with you have to design a new regulation on data protection on AI who are going who are you going to follow?
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Are you going to copy paste the US model? Are you going to copy paste the Chinese model? Neither. So you are going to uh to copy paste the EU model which is the fruit of a compromise and uh it
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creates a lot of opportunity uh for European companies. Uh maybe it was not designed on purpose but GDPR is a very good EU export product because it has been uh replicated in a lot of African countries and it creates a room for Euro
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companies which are by design compliant with these models. one of the companies that we accelerate. It's not about GDPR.
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It's about EID. Uh they were certified in Europe, the Kenya uh copy pasted the EU regulation. So now this company operates for uh players uh corporates on the Kenyan and very soon on the Ugandan market. So we should not be ashamed of
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trying to regulate uh this um these big giants. That's my first comment. And the second comment it is that we are talking of financial services but you know the innovation doesn't come from banks except maybe South Africa but out of
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South Africa innovation is driven by fintech mobile money operators. uh keep in mind that 74% of the mobile money transactions in the world are in subsaran Africa and these players who have less legacy than the banks uh uh consider the data
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the the data questions the question of AI not as a constraint but also as a way to get a competitive age versus the legacy players. So the uh the world is not changed Africa is not changed by uh
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atariaba bank or uh muscle bank in Egypt. It is changed by wave a company we have invested in in Sagal. It is changed by moneyoint in Nigeria. It is changed by EMPA in Kenya. Vona, I was smirking. I don't know if you saw it
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when you mentioned that GDPR was one of the best uh you know regulatory inventions because in Europe we're now going through a phase where we're classifying everything and I'm being very unpartial and unbiased here as overregulation.
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Um but I do believe that there is a big risk here when you take out the authority or the ettos of these companies that are by themselves a bit regulatory in nature and bring that to let's talk about this big companies or
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these big AI companies that bring that regulation to the AI companies so that they have to regulate themselves. I think there's a bit of a risk there. So it's interesting that you bring that perspective on GDPR and centralization
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of regulation as well. Um thank you so much for your perspectives on the infrastructure front. We are going into the last topic that is one that interests hopefully all of you that is jobs. Uh it's uh a topic that uh
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raises many questions in an age of massive disruption in an age where LLMs are um and agents are being trained to operate maximally and efficiently in the workforce.
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um what is going to happen with the younger generation and also with the current generation and perspectives vary. Uh Daram the CEO of um of entropic said just two years ago that half of the entry-level white colored jobs will be
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massively disruptive disappeared in the span of five years. Dennis sister said the opposite just one year ago. Um so there is this perspective here massive disruption at the same time as there is a perspective that is a bit more
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moderate including the report published by the world economic forum on the future of jobs uh that points that 170 million will be created uh with 92 million jobs displaced by 2030 but importantly that 40% of the skills that
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we consider core skills now will change. And then we have the skeptics or sometimes called the doomers that predict that you know everything will change completely. Massive disruption, massive unemployment. But then sometimes this is tied this end of the work
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predictment is tied to every major technological uh disruption that we've seen before. So there's a variety of perspectives. Um and I wanted to focus this topic initially in the Africa continent as well because we are seeing that 10 to 12
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million youths are entering the workforce yearly. You have one of the youngest workforces right now uh entering the job market in an age where AI is completely or partially let's say redefining entrylevel work.
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Von, you um see this on the ground with with founders as well. What jobs do you see that are being created by by companies that uh that you deal with?
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So I have two hats. So we are an investor in Afghan startups, okay, who are creating some local jobs and we accelerate European companies into Africa. So uh the answer is going to be different each time. regarding the
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companies that we invest in in Africa. Okay. And we invest they hire local people. Uh but it's not the most interesting when you invest into these companies you build an ecosystem which is going to contribute to the formalization of the uh of the economy.
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Uh we have mentioned wave for example this big fintech in Sagal and Iost okay wave they have their own stuff but it is not the most interesting. The most interesting it is that now you have hairdresser, gross keepers who have
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access to a formalized job maybe not a wage but to a formal job with um um a credit uh with a credit history and uh it is much more powerful than the jobs created by the start the startups themselves. Okay. Uh
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so that's my first comment regarding the companies that we bring from Europe to Africa. The question is different. Uh it's so easy to find good bookkeepers, good marketing guys, uh good uh digital marketing guys, but there is something
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for which we suffer. It's so hard to find a good B2B salesperson in Africa.
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The guy who is able to sell a software to the managing director of a smallme, it's so hard. Uh so if you if you have some profiles to share with me whatever the country I take them uh and uh maybe
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AI will be a solution for this to to spot that kind of profile or to upgrade these people uh but today it is my main pain and the good news when you are in Africa and when you work it is you don't have all
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these speeches of AI is going to kill my job. It's a very European point of view and that's why it's it's a refresh to work on the African continent.
Speaker A
Thank you very much. I I think that that point of view is also shared uh in the in the US around the massive uh disruptions and of course polarization of different ends of the spectrum of what that actually means. Um actually
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curiously B2B salespersons or salespersons in in general according to research are are the ones that are going to be not replaced uh by this disruption at least what we see from now from the analysis. Bringing it back to Audrey um
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you grew a company from eight people to 200 plus people. How has AI changed the roles you hire for? Um, and what do you tell a 22year-old joining your company today?
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I think this the starting point there um is a reminder a key reminder that machines and humans have to work together. So that's that's been always an operating principle around the growth. The second part for me the journey around uh the growth component
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was the realization that um every year that went on I knew less than the youngsters that were graduating and we need to be quite humble about that. So I have a very uh diverse young team. Um probably um I bring down that median
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quite drastically um in my 50s. Um and the realization for that was also an appreciation that also the skills that I bring to bear over 25 years 30 years of experience are also assets in this journey of building the workforce of the
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future. So in how I've integrated the skills, it's both the techies, so the traditional business analyst, data scientists, and Vincent will chat because I do believe you're looking in the wrong places. I could find you the skills that you're looking for. And I
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and I'll tell you why. Uh because I think the the I believe the traditional approach to recruiting has to come out of the completely out of the table. Uh you have to partner very early on with institutions around. I'm so privileged
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that we're here again and the starting h speaker yesterday uh who was a director of where this beautiful piece of architecture we're sitting uh was speaking about a multicultural approach to making sure that students from all over the world attend this beautiful
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novel uh institution that we're in partnerships with such institutions I did very early u some of our key universities uh and making sure you identify that key talent it doesn't matter what they're studying because you have to marry
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uh the sciences, life sciences and the human sciences in the teams that you put forward for every two developers. I have either um a human scientist in in form of yes uh could be an a literature major or a historian or anthropologist. uh and
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why you ask because um the combination of those skills mean that the integrity uh from a governance from an ethics point of view and an experience in terms of the biases and eliminating the biases in the work that they're done. So I've
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learned a lot around making sure that you have a team that allows the questioning irritates the engineers and the software developers absolutely irritates them but they've come to appreciate that over time. If you look at uh what I would then tell a
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22-year-old today, back to your your point, in fact, I'd be curiously what I always do with them. I curiously ask the same question over and over again. What are you scared of? Actually, we are the ones in these rooms that are scared of
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them losing their jobs. They're not scared of it. They're not looking at the world as it is. They're curious. They want to sell you the next idea and and innovate. And that has humbled me. Ask some of the young ones what are they
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scared of and they'll teach you something. I enjoy them. [applause] A positive and refreshing perspective here on workforce disruptions. And we're going to end this topic with Margarita as well on the same line of you belong to or you work with me and altis
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Portugal in this um disruption that has started already a few years back. Do you see roles generally changing? Has there been work created that wasn't there three years ago?
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Um New hiring possibilities from new jobs. Customer service, network design. Fore in particular. for engineering, AI people.
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in particular. Collaboration design developers. Chief Responsible AI. General and administrative Thank you very much um for also pointing at concrete examples of roles and skills that you see shifting in terms of prioritization and in terms of importance.
Speaker A
Also very interesting to see uh the concrete example that you mentioned of the telephone assistants and operators that obviously the role has been completely repurposed from from decades ago. Uh and I would end with a sentence that you said uh just now that is
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history teaches us to not be afraid because things like this happened before. But I would also add that history teaches us to be pre-prepared and prepared for this disruptions. So obviously we are at time I believe. Do we have time for a couple of questions?
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Two questions from the audience. Yes or no? Yes. No. Okay. Well, thank you very much uh for participating.
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Thank you very much for being here. [applause]
Topics:innovationtechnologyartificial intelligenceAI implementationleadershipchange managementdata governanceglobal innovation6Gquantum technology
